diff --git a/data.dvc b/data.dvc index 7e85424..444b4c8 100644 --- a/data.dvc +++ b/data.dvc @@ -1,5 +1,5 @@ outs: -- md5: 13997760d0604f1af3b3e385f3a8c14c.dir - size: 411277969 +- md5: e2b5b53d6baf9c78120c5fe4af533268.dir + size: 411278067 nfiles: 321 path: data diff --git a/tags b/tags index 34142f5..2a62908 100644 --- a/tags +++ b/tags @@ -45,6 +45,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 0 .dvc/plots/scatter.json /^ {$/;" o array:layer 0 .dvc/plots/smooth.json /^ "rev"$/;" s array:transform.0.groupby 0 .dvc/plots/smooth.json /^ {$/;" o array:transform +0 .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s array:scopes 0 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 0 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 0 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -114,6 +115,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 0 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 0 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 0 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +0 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +0 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +0 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +0 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +0 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +0 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +0 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +0 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +0 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +0 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 1 .dvc/plots/confusion.json /^ ""$/;" s array:spec.transform.0.groupby 1 .dvc/plots/confusion.json /^ ""$/;" s array:spec.transform.2.groupby 1 .dvc/plots/confusion.json /^ ""$/;" s array:spec.transform.1.groupby @@ -130,6 +141,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 1 .dvc/plots/linear.json /^ {$/;" o array:layer 1 .dvc/plots/scatter.json /^ {$/;" o array:layer.0.layer 1 .dvc/plots/scatter.json /^ {$/;" o array:layer +1 .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s array:scopes 1 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 1 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 1 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -199,6 +211,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 1 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 1 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 1 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +1 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +1 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +1 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +1 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +1 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +1 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +1 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +1 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +1 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +1 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 1. Anchor sorting and filtering Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/README.md /^## 1. Anchor sorting and filtering$/;" s chapter:Step by Step Detection 10 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 10 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss @@ -269,6 +291,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 10 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 10 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 10 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +10 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +10 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +10 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +10 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +10 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +10 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +10 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +10 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +10 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +10 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 100 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 100 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 100 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -878,6 +910,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 11 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 11 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 11 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +11 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +11 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +11 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +11 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +11 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +11 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +11 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +11 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +11 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +11 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 110 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 110 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 110 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -1487,6 +1529,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 12 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 12 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 12 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +12 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +12 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +12 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +12 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +12 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +12 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +12 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +12 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +12 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +12 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 120 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 120 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 120 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -2096,6 +2148,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 13 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 13 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 13 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +13 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +13 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +13 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +13 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +13 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +13 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +13 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +13 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +13 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +13 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 130 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 130 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 130 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -2705,6 +2767,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 14 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 14 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 14 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +14 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +14 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +14 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +14 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +14 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +14 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +14 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +14 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +14 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +14 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 140 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 140 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 140 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -3314,6 +3386,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 15 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 15 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 15 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +15 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +15 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +15 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +15 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +15 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +15 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +15 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +15 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +15 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +15 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 150 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:accuracy 150 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:loss 150 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:val_accuracy @@ -3423,6 +3505,15 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 16 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 16 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 16 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +16 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +16 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +16 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +16 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +16 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +16 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +16 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +16 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +16 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 160 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:accuracy 160 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:loss 160 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:val_accuracy @@ -3532,6 +3623,15 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 17 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 17 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 17 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +17 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +17 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +17 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +17 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +17 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +17 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +17 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +17 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +17 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 170 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:accuracy 170 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:loss 170 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:val_accuracy @@ -3641,6 +3741,13 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 18 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 18 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 18 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +18 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +18 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +18 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +18 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +18 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +18 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +18 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 180 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:accuracy 180 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:loss 180 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:val_accuracy @@ -3750,6 +3857,13 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 19 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 19 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 19 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +19 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +19 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +19 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +19 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +19 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +19 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +19 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 190 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:accuracy 190 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:loss 190 Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" n object:val_accuracy @@ -3861,6 +3975,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 2 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 2 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 2 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +2 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +2 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +2 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +2 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +2 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +2 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +2 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +2 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +2 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +2 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 2. Bounding Box Refinement Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/README.md /^## 2. Bounding Box Refinement$/;" s chapter:Step by Step Detection 20 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 20 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss @@ -3921,6 +4045,13 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 20 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 20 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 20 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +20 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +20 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +20 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +20 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +20 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +20 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +20 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 21 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 21 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 21 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -3980,6 +4111,12 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 21 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 21 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 21 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +21 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +21 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +21 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +21 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +21 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +21 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 22 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 22 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 22 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4039,6 +4176,11 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 22 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 22 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 22 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +22 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +22 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +22 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +22 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +22 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 23 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 23 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 23 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4098,6 +4240,11 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 23 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 23 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 23 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +23 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +23 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +23 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +23 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +23 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 24 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 24 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 24 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4157,6 +4304,11 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 24 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 24 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 24 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +24 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +24 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +24 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +24 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +24 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 25 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 25 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 25 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4216,6 +4368,11 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 25 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 25 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 25 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +25 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +25 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +25 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +25 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +25 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 26 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 26 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 26 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4275,6 +4432,10 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 26 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 26 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 26 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +26 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +26 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +26 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +26 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 27 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 27 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 27 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4334,6 +4495,10 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 27 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 27 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 27 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +27 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +27 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +27 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +27 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 28 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 28 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 28 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4393,6 +4558,9 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 28 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 28 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 28 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +28 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +28 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +28 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 29 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 29 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 29 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4452,6 +4620,9 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 29 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 29 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 29 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +29 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +29 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +29 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 3 .dvc/plots/confusion.json /^ {$/;" o array:spec.transform 3 .dvc/plots/confusion_normalized.json /^ {$/;" o array:spec.transform 3 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss @@ -4523,6 +4694,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 3 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 3 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 3 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +3 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +3 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +3 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +3 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +3 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +3 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +3 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +3 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +3 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +3 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 3. Mask Generation Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/README.md /^## 3. Mask Generation$/;" s chapter:Step by Step Detection 30 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 30 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss @@ -4583,6 +4764,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 30 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 30 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 30 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +30 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +30 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 31 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 31 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 31 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4642,6 +4825,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 31 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 31 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 31 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +31 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +31 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 32 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 32 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 32 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4701,6 +4886,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 32 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 32 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 32 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +32 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +32 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 33 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 33 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 33 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4760,6 +4947,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 33 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 33 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 33 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +33 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +33 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 34 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 34 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 34 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4819,6 +5008,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 34 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 34 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 34 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +34 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +34 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 35 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 35 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 35 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4878,6 +5069,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 35 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 35 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 35 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +35 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +35 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 36 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 36 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 36 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4937,6 +5130,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 36 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 36 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 36 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +36 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +36 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 37 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 37 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 37 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -4996,6 +5191,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 37 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 37 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 37 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +37 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +37 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 38 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 38 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 38 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5055,6 +5252,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 38 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 38 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 38 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +38 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +38 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 39 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 39 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 39 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5114,6 +5313,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 39 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 39 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 39 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +39 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +39 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 4 .dvc/plots/confusion.json /^ {$/;" o array:spec.transform 4 .dvc/plots/confusion_normalized.json /^ {$/;" o array:spec.transform 4 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss @@ -5185,6 +5386,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 4 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 4 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 4 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +4 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +4 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +4 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +4 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +4 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +4 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +4 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +4 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +4 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +4 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 4.Layer activations Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/README.md /^## 4.Layer activations$/;" s chapter:Step by Step Detection 40 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 40 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss @@ -5245,6 +5456,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 40 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 40 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 40 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +40 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +40 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 41 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 41 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 41 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5304,6 +5517,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 41 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 41 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 41 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +41 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +41 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 42 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 42 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 42 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5363,6 +5578,8 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 42 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 42 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 42 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +42 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +42 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 43 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 43 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 43 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5422,6 +5639,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 43 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 43 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 43 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +43 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 44 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 44 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 44 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5481,6 +5699,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 44 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 44 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 44 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +44 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 45 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 45 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 45 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5540,6 +5759,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 45 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 45 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 45 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +45 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 46 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 46 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 46 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5599,6 +5819,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 46 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 46 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 46 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +46 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 47 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 47 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 47 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5658,6 +5879,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 47 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 47 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 47 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +47 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 48 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 48 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 48 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5717,6 +5939,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 48 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 48 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 48 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +48 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 49 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 49 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 49 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5776,6 +5999,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 49 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 49 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 49 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +49 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 5 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 5 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 5 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5845,6 +6069,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 5 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 5 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 5 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +5 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +5 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +5 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +5 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +5 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +5 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +5 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +5 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +5 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +5 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 5. Weight Histograms Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/README.md /^## 5. Weight Histograms$/;" s chapter:Step by Step Detection 50 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 50 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss @@ -5905,6 +6139,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 50 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 50 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 50 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +50 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 51 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 51 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 51 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -5964,6 +6199,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 51 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 51 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 51 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +51 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 52 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 52 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 52 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6023,6 +6259,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 52 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 52 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 52 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +52 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 53 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 53 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 53 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6082,6 +6319,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 53 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 53 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 53 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +53 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 54 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 54 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 54 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6141,6 +6379,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 54 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 54 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 54 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +54 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 55 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 55 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 55 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6200,6 +6439,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 55 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 55 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 55 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +55 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 56 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 56 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 56 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6259,6 +6499,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 56 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 56 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 56 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +56 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 57 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 57 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 57 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6318,6 +6559,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 57 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 57 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 57 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +57 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 58 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 58 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 58 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6377,6 +6619,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 58 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 58 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 58 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +58 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 59 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 59 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 59 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6436,6 +6679,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 59 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 59 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 59 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +59 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 6 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 6 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 6 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6505,6 +6749,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 6 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 6 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 6 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +6 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +6 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +6 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +6 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +6 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +6 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +6 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +6 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +6 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +6 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 6. Composing the different pieces into a final result Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/README.md /^## 6. Composing the different pieces into a final result$/;" s chapter:Step by Step Detection 6. Logging to TensorBoard Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/README.md /^## 6. Logging to TensorBoard$/;" s chapter:Step by Step Detection 60 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss @@ -6566,6 +6820,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 60 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 60 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 60 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +60 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 61 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 61 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 61 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6625,6 +6880,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 61 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 61 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 61 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +61 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 62 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 62 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 62 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6684,6 +6940,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 62 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 62 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 62 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +62 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 63 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 63 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 63 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6743,6 +7000,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 63 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 63 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 63 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +63 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 64 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 64 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 64 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6802,6 +7060,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 64 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 64 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 64 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +64 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 65 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 65 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 65 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6861,6 +7120,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 65 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 65 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 65 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +65 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 66 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 66 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 66 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6920,6 +7180,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 66 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 66 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 66 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +66 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 67 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 67 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 67 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -6979,6 +7240,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 67 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 67 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 67 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +67 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 68 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 68 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 68 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -7038,6 +7300,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": 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/^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 69 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -7097,6 +7360,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 69 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 69 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 69 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +69 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data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 76 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 76 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 76 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -7579,6 +7859,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 76 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 76 Detector/Version_2_Detector/history_classification_model_v2_100e.json 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/^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 79 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +79 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 8 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 8 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 8 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -7825,6 +8109,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": 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SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +8 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +8 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +8 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +8 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 80 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 80 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 80 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -7884,6 +8178,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 80 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 80 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 80 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +80 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 81 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 81 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 81 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -7943,6 +8238,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 81 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 81 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 81 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +81 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 82 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 82 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 82 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -8002,6 +8298,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 82 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 82 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 82 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +82 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 83 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 83 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 83 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -8061,6 +8358,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 83 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 83 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 83 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +83 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 84 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 84 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 84 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -8120,6 +8418,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 84 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 84 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 84 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +84 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 85 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 85 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 85 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -8179,6 +8478,7 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 85 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:lr 85 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_accuracy 85 Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" n object:val_loss +85 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i 86 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 86 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 86 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -8484,6 +8784,16 @@ $schema .dvc/plots/smooth.json /^ "$schema": "https:\/\/vega.github.io\/schem 9 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:lr 9 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_accuracy 9 Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" n object:val_loss +9 data/Blood SmearAnalysis/BAND CELLS/annotations.xml /^ $/;" i +9 data/Blood SmearAnalysis/BASOPHILS/annotations.xml /^ $/;" i +9 data/Blood SmearAnalysis/BLAST CELLS/annotations.xml /^ $/;" i +9 data/Blood SmearAnalysis/EOSINOPHILS/annotations.xml /^ $/;" i +9 data/Blood SmearAnalysis/LYMPHOCYTES/annotations.xml /^ $/;" i +9 data/Blood SmearAnalysis/METAMYELOCYTES/annotations.xml /^ $/;" i +9 data/Blood SmearAnalysis/MONOCYTES/annotations.xml /^ $/;" i +9 data/Blood SmearAnalysis/MYELOCYTE/annotations.xml /^ $/;" i +9 data/Blood SmearAnalysis/NEUTROPHILS/annotations.xml /^ $/;" i +9 data/Blood SmearAnalysis/PROMYELOCYTES/annotations.xml /^ $/;" i 90 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:loss 90 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_bbox_loss 90 Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" n object:mrcnn_class_loss @@ -9125,6 +9435,7 @@ D Classifier/classification_aniket.py /^D = 1$/;" v D Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^D = 1$/;" v D Detector/GradCam_Prototype/evaluate_model.py /^D = 1$/;" v D Detector/Version_2_Detector/train_SegModel_v2.py /^D = 1$/;" v +D WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ D = ndimage.distance_transform_edt(mask)$/;" v DATA_DIR Classifier/Classifier_model_v4/classification_aniket.py /^DATA_DIR = 'PBC_dataset_normal_DIB'$/;" v DATA_DIR Classifier/classification_aniket.py /^DATA_DIR = 'PBC_dataset_normal_DIB'$/;" v DATA_DIR Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^DATA_DIR = 'PBC_dataset_normal_DIB' # 302410 images. validate accuracy: 98.8%$/;" v @@ -12098,6 +12409,7 @@ H Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^H, W, C = 360, 360, 3$/; H Detector/GradCam_Prototype/evaluate_model.py /^H, W, C = 360, 360, 3$/;" v H Detector/Version_2_Detector/train_SegModel_v2.py /^H, W, C = 360, 360, 3$/;" v H Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^H, W, C = 360, 360, 3$/;" v +H_2 WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^H_2 , W_2 = int(363\/2), int(360\/2)$/;" v IMAGES_PER_GPU Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/config.py /^ IMAGES_PER_GPU = 2$/;" v class:Config IMAGES_PER_GPU Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/balloon/balloon.py /^ IMAGES_PER_GPU = 1$/;" v class:InferenceConfig IMAGES_PER_GPU Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/balloon/balloon.py /^ IMAGES_PER_GPU = 2$/;" v class:BalloonConfig @@ -12162,6 +12474,7 @@ Model_V2_Gradcam Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^def Model_V Model_V2_Gradcam Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^def Model_V2_Gradcam(H,W,C):$/;" f Model_V2_Gradcam Detector/Version_2_Detector/train_SegModel_v2.py /^def Model_V2_Gradcam(H,W,C):$/;" f MyNet exp/demo.py /^class MyNet(nn.Module):$/;" c +N WaterShedAlgo/find_avg.py /^N=len(imlist)$/;" v NAME Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/config.py /^ NAME = None # Override in sub-classes$/;" v class:Config NAME Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/balloon/balloon.py /^ NAME = "balloon"$/;" v class:BalloonConfig NAME Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ NAME = "coco"$/;" v class:CocoConfig @@ -12270,6 +12583,7 @@ W Detector/GradCam_Prototype/evaluate_model.py /^H, W, C = 360, 360, 3$/;" v W Detector/Version_2_Detector/train_SegModel_v2.py /^H, W, C = 360, 360, 3$/;" v W Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^H, W, C = 360, 360, 3$/;" v WEIGHT_DECAY Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/config.py /^ WEIGHT_DECAY = 0.0001$/;" v class:Config +W_2 WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^H_2 , W_2 = int(363\/2), int(360\/2)$/;" v [4K Video Demo](https://www.youtube.com/watch?v=OOT3UIXZztE) by Karol Majek. Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/README.md /^### [4K Video Demo](https:\/\/www.youtube.com\/watch?v=OOT3UIXZztE) by Karol Majek.$/;" S chapter:Projects Using this Model [Characterization of Arctic Ice-Wedge Polygons in Very High Spatial Resolution Aerial Imagery](http://www.mdpi.com/2072-4292/10/9/1487) Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/README.md /^### [Characterization of Arctic Ice-Wedge Polygons in Very High Spatial Resolution Aerial Imager/;" S chapter:Projects Using this Model [Detection and Segmentation for Surgery Robots](https://github.com/SUYEgit/Surgery-Robot-Detection-Segmentation) by the NUS Control & Mechatronics Lab. Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/README.md /^### [Detection and Segmentation for Surgery Robots](https:\/\/github.com\/SUYEgit\/Surgery-Robot/;" S chapter:Projects Using this Model @@ -12295,8 +12609,10 @@ __init__ Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^ def __init__ __init__ Segmentation/build_data.py /^ def __init__(self, image_format='jpeg', channels=3):$/;" m class:ImageReader __init__ exp/demo.py /^ def __init__(self,input_dim):$/;" m class:MyNet _bytes_list_feature Segmentation/build_data.py /^def _bytes_list_feature(values):$/;" f +_class .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s _convert_dataset Segmentation/build_voc2012_data.py /^def _convert_dataset(dataset_split):$/;" f _int64_list_feature Segmentation/build_data.py /^def _int64_list_feature(values):$/;" f +_module .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s _parse_requirements Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/setup.py /^def _parse_requirements(file_path):$/;" f _remove_colormap Segmentation/remove_gt_colormap.py /^def _remove_colormap(filename):$/;" f _save_annotation Segmentation/remove_gt_colormap.py /^def _save_annotation(annotation, filename):$/;" f @@ -12316,6 +12632,8 @@ abs_grad_y Detector/MSBlobDetector/Sobel_Maker_2.py /^ abs_grad_y = c abs_grad_y Detector/MSBlobDetector/test.py /^ abs_grad_y = cv2.convertScaleAbs(grad_y)$/;" v abs_grad_y Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ abs_grad_y = cv2.convertScaleAbs(grad_y)$/;" v abs_grad_y Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ abs_grad_y = cv2.convertScaleAbs(grad_y)$/;" v +access_token .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s +access_token .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s object:token_response accuracy Classifier/Classifier_model_v2/history_classification_model_v2_150e.json /^{"loss":{"0":2.8016490936,"1":2.4731841087,"2":2.2225644588,"3":2.0351891518,"4":1.8644064665,"5/;" o accuracy Classifier/Classifier_model_v4/history_classification_model_v4_150e.json /^{"loss":{"0":2.7692947388,"1":2.3991117477,"2":2.1364119053,"3":1.9868150949,"4":1.8946658373,"5/;" o accuracy Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" o @@ -12352,22 +12670,31 @@ all_imgs Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^all_imgs = glob.glo all_imgs Detector/MSBlobDetector/Sobel_Maker.py /^all_imgs = glob.glob('..\/samples\/*')$/;" v all_imgs Detector/MSBlobDetector/Sobel_Maker_2.py /^all_imgs = glob.glob('..\/samples\/*')$/;" v all_imgs Detector/MSBlobDetector/test.py /^all_imgs = glob.glob('..\/samples\/*')$/;" v +all_imgs WaterShedAlgo/find_upper_and_lower_patches.py /^all_imgs = glob.glob('masks\/*.png')$/;" v all_superimposed_img Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ all_superimposed_img = []$/;" v all_superimposed_img Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ all_superimposed_img = []$/;" v all_superimposed_img Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ all_superimposed_img = []$/;" v all_thres Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ all_thres = []$/;" v all_thres Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ all_thres = []$/;" v all_thres Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ all_thres = []$/;" v +allfiles WaterShedAlgo/find_avg.py /^allfiles=os.listdir(os.getcwd())$/;" v ancestor Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^ def ancestor(self, tensor, name, checked=None):$/;" m class:MaskRCNN annToMask Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ def annToMask(self, ann, height, width):$/;" m class:CocoDataset annToRLE Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ def annToRLE(self, ann, height, width):$/;" m class:CocoDataset +annotation_xml data/dataset.py /^ annotation_xml = minidom.Document()$/;" v +annotations data/dataset.py /^ annotations = {}$/;" v +annotations_root data/dataset.py /^ annotations_root = annotation_xml.createElement('annotations')$/;" v apply_box_deltas Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def apply_box_deltas(boxes, deltas):$/;" f apply_box_deltas_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def apply_box_deltas_graph(boxes, deltas):$/;" f apply_mask Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/visualize.py /^def apply_mask(image, mask, color, alpha=0.5):$/;" f args Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/balloon/balloon.py /^ args = parser.parse_args()$/;" v args Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ args = parser.parse_args()$/;" v args Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/nucleus/nucleus.py /^ args = parser.parse_args()$/;" v +args data/dataset.py /^args = parser.parse_args()$/;" v args exp/demo.py /^args = parser.parse_args()$/;" v +arr WaterShedAlgo/find_avg.py /^ arr=arr+imarr\/N$/;" v +arr WaterShedAlgo/find_avg.py /^arr=numpy.array(numpy.round(arr),dtype=numpy.uint8)$/;" v +arr WaterShedAlgo/find_avg.py /^arr=numpy.zeros((h,w,3),numpy.float)$/;" v as .dvc/plots/confusion.json /^ "as": "max_count"$/;" s object:spec.transform.3.joinaggregate.0 as .dvc/plots/confusion.json /^ "as": "xy_count"$/;" s object:spec.transform.0.aggregate.0 as .dvc/plots/confusion.json /^ "as": "percent_of_max"$/;" s object:spec.transform.4 @@ -12383,6 +12710,8 @@ auc Classifier/Classifier_model_v2/history_classification_model_v2_150e.json /^{ auc Classifier/Classifier_model_v4/history_classification_model_v4_150e.json /^{"loss":{"0":2.7692947388,"1":2.3991117477,"2":2.1364119053,"3":1.9868150949,"4":1.8946658373,"5/;" o augmentation Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ augmentation = imgaug.augmenters.Fliplr(0.5)$/;" v auto_download Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ def auto_download(self, dataDir, dataType, dataYear):$/;" m class:CocoDataset +avg WaterShedAlgo/colour_thresholding.py /^avg = cv2.imread('Average.png', cv2.IMREAD_COLOR)$/;" v +avg WaterShedAlgo/colour_thresholding.py /^avg = np.array(avg)$/;" v ax Classifier/classification_aniket.py /^ ax = axes.flat[i]$/;" v ax Detector/MSBlobDetector/Blob_Detector_Grayscale.py /^ ax = axes.ravel()$/;" v ax Detector/MSBlobDetector/Blob_Detector_Sobel.py /^ ax = axes.ravel()$/;" v @@ -12417,6 +12746,10 @@ axes Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ fig, axes = plt.sub axes Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ fig, axes = plt.subplots(1, 3, figsize=(9, 3), sharex=True, sharey=True)$/;" v axes Detector/MSBlobDetector/test.py /^ fig, axes = plt.subplots(1, 3, figsize=(9, 3), sharex=True, sharey=True)$/;" v b Aniket_MASK_RCNN/color_palatte.py /^ b = cell_col[2]$/;" v +b_max WaterShedAlgo/find_upper_and_lower_patches.py /^ b_max = im[..., 2].max()$/;" v +b_max_list WaterShedAlgo/find_upper_and_lower_patches.py /^b_max_list = []$/;" v +b_min WaterShedAlgo/find_upper_and_lower_patches.py /^ b_min = im[..., 2].min()$/;" v +b_min_list WaterShedAlgo/find_upper_and_lower_patches.py /^b_min_list = []$/;" v bandwidth .dvc/plots/smooth.json /^ "bandwidth": 0.3$/;" n object:transform.0 base docs/Hematopoiesis_simple.svg /^ inkscape:window-maximized="0" \/>$/;" i batch_pack_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def batch_pack_graph(x, counts, num_rows):$/;" f @@ -12450,6 +12783,7 @@ blobs_log Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ blobs_log = bl blobs_log Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ blobs_log = blob_log(image_gray, max_sigma=80, num_sigma=10, threshold=0.1)$/;" v blobs_log Detector/MSBlobDetector/test.py /^ blobs_log = blob_log(image_gray, max_sigma=70, num_sigma=30, threshold=0.001)$/;" v bloseg README.md /^# bloseg$/;" c +blurred WaterShedAlgo/test_ws.py /^blurred = cv2.GaussianBlur(gray, (3, 3), 0)$/;" v blurred_thresh Detector/MSBlobDetector/Sobel_Maker_2.py /^blurred_thresh = cv2.GaussianBlur(total_thresh,(5,5),0)$/;" v box_refinement Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def box_refinement(box, gt_box):$/;" f box_refinement_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def box_refinement_graph(box, gt_box):$/;" f @@ -12465,6 +12799,7 @@ c Detector/MSBlobDetector/Blob_Detector_Sobel.py /^ c = plt.Circle((x c Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ c = plt.Circle((x, y), r, color=color, linewidth=2, fill=False)$/;" v c Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ c = plt.Circle((x, y), r, color=color, linewidth=2, fill=False)$/;" v c Detector/MSBlobDetector/test.py /^ c = plt.Circle((x, y), r, color=color, linewidth=2, fill=False)$/;" v +c WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ c = max(cnts, key=cv2.contourArea)$/;" v calculate .dvc/plots/confusion.json /^ "calculate": "datum.xy_count \/ datum.max_count",$/;" s object:spec.transform.4 calculate .dvc/plots/confusion_normalized.json /^ "calculate": "datum.xy_count \/ datum.sum_y",$/;" s object:spec.transform.4 call Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^ def call(self, inputs):$/;" m class:DetectionLayer @@ -12484,6 +12819,7 @@ class_names Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^class_names = [$/;" v class_names Aniket_MASK_RCNN/MaskRCNN_3/model_test_slide.py /^class_names = [$/;" v class_names Classifier/Classifier_model_v4/classification_aniket.py /^class_names = [$/;" v class_names Classifier/classification_aniket.py /^class_names = [$/;" v +class_names data/dataset.py /^class_names = os.listdir(args.input_dir)$/;" v class_weights Classifier/Classifier_model_v4/classification_aniket.py /^class_weights = class_weight.compute_class_weight($/;" v class_weights Classifier/Classifier_model_v4/classification_aniket.py /^class_weights = {i : class_weights[i] for i in range(len(name_dict))}$/;" v class_weights Classifier/classification_aniket.py /^class_weights = class_weight.compute_class_weight($/;" v @@ -12494,12 +12830,18 @@ classifier_layer_names Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ clean_name Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^ def clean_name(name):$/;" f member:Dataset.prepare file: clear .dvc/plots/linear.json /^ "clear": "mouseout"$/;" s object:layer.0.layer.1.selection.label clear .dvc/plots/scatter.json /^ "clear": "mouseout"$/;" s object:layer.0.layer.1.selection.label +client_id .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s +client_secret .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s clip_boxes_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def clip_boxes_graph(boxes, window):$/;" f +cluster WaterShedAlgo/k_means_clustering.py /^cluster = KMeans(n_clusters=5).fit(reshape)$/;" v +cluster WaterShedAlgo/make_colour_cluster.py /^ cluster = KMeans(n_clusters=25).fit(reshape)$/;" v cm Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^import matplotlib.cm as cm$/;" I nameref:module:matplotlib.cm cm Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^import matplotlib.cm as cm$/;" I nameref:module:matplotlib.cm cm Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^import matplotlib.cm as cm$/;" I nameref:module:matplotlib.cm cm Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^import matplotlib.cm as cm$/;" I nameref:module:matplotlib.cm cm Detector/utils/GRAD_CAM.py /^import matplotlib.cm as cm$/;" I nameref:module:matplotlib.cm +cnts WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ cnts = cv2.findContours(mask_1.copy(), cv2.RETR_EXTERNAL,$/;" v +cnts WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ cnts = imutils.grab_contours(cnts)$/;" v coco Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ coco = dataset_val.load_coco(args.dataset, val_type, year=args.year, return_coco=True, a/;" v color .dvc/plots/confusion.json /^ "color": {$/;" o object:spec.layer.0.encoding color .dvc/plots/confusion.json /^ "color": {$/;" o object:spec.layer.1.encoding @@ -12572,6 +12914,9 @@ counter Detector/MSBlobDetector/Sobel_Maker.py /^counter = 0$/;" v counter Detector/MSBlobDetector/Sobel_Maker_2.py /^counter = 0$/;" v counter Detector/MSBlobDetector/Sobel_Maker_2.py /^counter = 1$/;" v counter Detector/MSBlobDetector/test.py /^ counter = 0$/;" v +crop WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ crop = res[H_2-max_r:H_2+max_r,W_2-max_r:W_2+max_r].copy()$/;" v +cv WaterShedAlgo/water_Shed.py /^import cv2 as cv$/;" I nameref:module:cv2 +cv data/Blood SmearAnalysis/BASOPHILS/test.py /^import cv2 as cv$/;" I nameref:module:cv2 data .dvc/plots/confusion.json /^ "data": {$/;" o data .dvc/plots/confusion_normalized.json /^ "data": {$/;" o data .dvc/plots/default.json /^ "data": {$/;" o @@ -12585,6 +12930,8 @@ data_generator Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def data_g datagen Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/parallel_model.py /^ datagen = ImageDataGenerator()$/;" v datagen Classifier/Classifier_model_v4/classification_aniket.py /^datagen = ImageDataGenerator(rotation_range=30,$/;" v datagen Classifier/classification_aniket.py /^datagen = ImageDataGenerator(rotation_range=30,$/;" v +dataset_class_dir data/dataset.py /^ dataset_class_dir = os.path.join(args.input_dir, class_name)$/;" v +dataset_class_dir_output data/dataset.py /^ dataset_class_dir_output = os.path.join(args.output_dir, class_name)$/;" v dataset_train Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ dataset_train = CocoDataset()$/;" v dataset_val Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ dataset_val = CocoDataset()$/;" v dataset_val Aniket_MASK_RCNN/MaskRCNN_3/mask_rcnn3.py /^dataset_val = BloodDataset()$/;" v @@ -12643,6 +12990,8 @@ display_instances Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/visualize.py /^def display_table Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/visualize.py /^def display_table(table):$/;" f display_top_masks Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/visualize.py /^def display_top_masks(image, mask, class_ids, class_names, limit=4):$/;" f display_weight_stats Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/visualize.py /^def display_weight_stats(model):$/;" f +dist_transform WaterShedAlgo/water_Shed.py /^dist_transform = cv.distanceTransform(opening,cv.DIST_L2,5)$/;" v +doc data/dataset.py /^ doc = minidom.parse(os.path.join(dataset_class_dir, "annotations.xml"))$/;" v domain .dvc/plots/confusion_normalized.json /^ "domain": [$/;" a object:spec.layer.0.encoding.color.scale domainMin .dvc/plots/confusion.json /^ "domainMin": 0,$/;" n object:spec.layer.0.encoding.color.scale download_trained_weights Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def download_trained_weights(coco_model_path, verbose=1):$/;" f @@ -12683,6 +13032,7 @@ erosion Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ erosion = cv2.er erosion Detector/MSBlobDetector/test.py /^ erosion = cv2.erode(seg_map_conf,kernel,iterations = 5)$/;" v evaluate_coco Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^def evaluate_coco(model, dataset, coco, eval_type="bbox", limit=0, image_ids=None):$/;" f expand_mask Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def expand_mask(bbox, mini_mask, image_shape):$/;" f +expires_in .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" n object:token_response extract_bboxes Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def extract_bboxes(mask):$/;" f facet .dvc/plots/confusion.json /^ "facet": {$/;" o facet .dvc/plots/confusion_normalized.json /^ "facet": {$/;" o @@ -12745,6 +13095,8 @@ fig Detector/MSBlobDetector/test.py /^ fig, axes = plt.subplots(1, 3, figsize fig Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ fig = plt.figure()$/;" v fig Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ fig = plt.figure()$/;" v file Classifier/classification_aniket.py /^file = results.iloc[5]["Filename"]$/;" v +file WaterShedAlgo/get_colour_cluster.py /^file = open('colours_cluster.txt', 'rb')$/;" v +file WaterShedAlgo/make_colour_cluster.py /^file = open('colours_cluster_25.txt', 'wb')$/;" v filename Classifier/classification_aniket.py /^ filename = results.iloc[img_idx]["Filename"]$/;" v filenames Classifier/classification_aniket.py /^filenames=test_generator.filenames$/;" v files Classifier/Classifier_model_v4/classification_aniket.py /^ files = glob.glob("PBC_dataset_normal_DIB\/" + class_name + "\/*")$/;" v @@ -12754,6 +13106,8 @@ files Classifier/classification_aniket.py /^files = glob.glob("{}\/*\/*.jpg".for files Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^files = glob.glob("{}\/*\/*.jpg".format(DATA_DIR))$/;" v files Detector/GradCam_Prototype/evaluate_model.py /^files = glob.glob("{}\/*\/*.jpg".format(DATA_DIR))$/;" v files Detector/Version_2_Detector/train_SegModel_v2.py /^files = glob.glob("{}\/*\/*.jpg".format(DATA_DIR))$/;" v +files_from_folders WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ files_from_folders = glob.glob('{}\/*'.format(folders))$/;" v +files_from_folders WaterShedAlgo/make_colour_cluster.py /^ files_from_folders = glob.glob('{}\/*'.format(folders))$/;" v filter .dvc/plots/linear.json /^ "filter": {$/;" o object:layer.1.transform.0 filter .dvc/plots/scatter.json /^ "filter": {$/;" o object:layer.1.transform.0 find_last Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^ def find_last(self):$/;" m class:MaskRCNN @@ -12762,6 +13116,8 @@ flat Detector/MSBlobDetector/Blob_Detector_Sobel.py /^ flat=seg_map_conf.flat flat Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ flat=seg_map_conf.flatten()$/;" v flat Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ flat=seg_map_conf.flatten()$/;" v flat Detector/MSBlobDetector/test.py /^ flat=seg_map_conf.flatten()$/;" v +folder_name WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ folder_name = image_names.split('\/')[1]$/;" v +folders_list WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^folders_list = []$/;" v format .dvc/plots/confusion_normalized.json /^ "format": ".2f"$/;" s object:spec.layer.1.encoding.text forward exp/demo.py /^ def forward(self, x):$/;" m class:MyNet fpn_classifier_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def fpn_classifier_graph(rois, feature_maps, image_meta,$/;" f @@ -12790,6 +13146,10 @@ g3990 docs/Hematopoiesis_simple.svg /^ transform="matrix(1.9502456,0,0,1.950 g4054 docs/Hematopoiesis_simple.svg /^ id="g4054">$/;" i g5932 docs/Hematopoiesis_simple.svg /^ transform="translate(260.95162,13.807107)">$/;" i g8255 docs/Hematopoiesis_simple.svg /^ transform="matrix(2.0258328,0,0,2.0258328,-769.98839,-568.96806)">$/;" i +g_max WaterShedAlgo/find_upper_and_lower_patches.py /^ g_max = im[..., 1].max()$/;" v +g_max_list WaterShedAlgo/find_upper_and_lower_patches.py /^g_max_list = []$/;" v +g_min WaterShedAlgo/find_upper_and_lower_patches.py /^ g_min = im[..., 1].min()$/;" v +g_min_list WaterShedAlgo/find_upper_and_lower_patches.py /^g_min_list = []$/;" v generate_anchors Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def generate_anchors(scales, ratios, shape, feature_stride, anchor_stride):$/;" f generate_pyramid_anchors Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def generate_pyramid_anchors(scales, ratios, feature_shapes, feature_strides,$/;" f generate_random_rois Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def generate_random_rois(image_shape, count, gt_class_ids, gt_boxes):$/;" f @@ -12797,6 +13157,7 @@ get_anchors Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^ def get_a get_ax Aniket_MASK_RCNN/MaskRCNN_3/mask_rcnn3.py /^def get_ax(rows=1, cols=1, size=8):$/;" f get_ax Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^def get_ax(rows=1, cols=1, size=8):$/;" f get_ax Aniket_MASK_RCNN/MaskRCNN_3/model_test_slide.py /^def get_ax(rows=1, cols=1, size=8):$/;" f +get_contour WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^def get_contour(img_bin):$/;" f get_data_generator Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^def get_data_generator(df, indices, for_training, batch_size=16):$/;" f get_data_generator Detector/GradCam_Prototype/evaluate_model.py /^def get_data_generator(df, indices, for_training, batch_size=16):$/;" f get_data_generator Detector/Version_2_Detector/train_SegModel_v2.py /^def get_data_generator(df, indices, for_training, batch_size=16):$/;" f @@ -12811,6 +13172,7 @@ get_img Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ get_img = np.a get_img_array Detector/utils/GRAD_CAM.py /^def get_img_array(img_path, size):$/;" f get_jet_img Detector/utils/GRAD_CAM.py /^def get_jet_img(img, heatmap):$/;" f get_source_class_id Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^ def get_source_class_id(self, class_id, source):$/;" m class:Dataset +get_top_two WaterShedAlgo/make_colour_cluster.py /^get_top_two = []$/;" v get_trainable_layers Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^ def get_trainable_layers(self):$/;" m class:MaskRCNN go Detector/MSBlobDetector/3d_GrayScalePlot.py /^import plotly.graph_objects as go$/;" I nameref:module:plotly.graph_objects go Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ import plotly.graph_objects as go$/;" I nameref:module:plotly.graph_objects @@ -12846,6 +13208,10 @@ gray Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ gray = gray Detector/MSBlobDetector/Sobel_Maker.py /^ gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)$/;" v gray Detector/MSBlobDetector/Sobel_Maker_2.py /^ gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)$/;" v gray Detector/MSBlobDetector/test.py /^ gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)$/;" v +gray WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ gray = cv2.cvtColor(shifted, cv2.COLOR_BGR2GRAY)$/;" v +gray WaterShedAlgo/test_ws.py /^gray = cv2.cvtColor(shifted, cv2.COLOR_BGR2GRAY)$/;" v +gray WaterShedAlgo/test_ws.py /^gray = cv2.cvtColor(shifted,cv2.COLOR_BGR2GRAY)$/;" v +gray WaterShedAlgo/water_Shed.py /^gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)$/;" v groupby .dvc/plots/confusion.json /^ "groupby": [$/;" a object:spec.transform.0 groupby .dvc/plots/confusion.json /^ "groupby": [$/;" a object:spec.transform.1 groupby .dvc/plots/confusion.json /^ "groupby": [$/;" a object:spec.transform.2 @@ -12861,6 +13227,7 @@ gt_class_id Aniket_MASK_RCNN/MaskRCNN_3/mask_rcnn3.py /^original_image, image_me gt_class_id Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^original_image, image_meta, gt_class_id, gt_bbox, gt_mask =\\$/;" v gt_mask Aniket_MASK_RCNN/MaskRCNN_3/mask_rcnn3.py /^original_image, image_meta, gt_class_id, gt_bbox, gt_mask =\\$/;" v gt_mask Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^original_image, image_meta, gt_class_id, gt_bbox, gt_mask =\\$/;" v +h WaterShedAlgo/find_avg.py /^w,h=Image.open(imlist[0]).size$/;" v heatmap Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ heatmap = make_gradcam_heatmap($/;" v heatmap Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ img, heatmap, heatmap_, superimposed_img = get_jet_img(img, heatmap)$/;" v heatmap Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ heatmap = make_gradcam_heatmap($/;" v @@ -12892,10 +13259,14 @@ history Classifier/classification_aniket.py /^history = model.fit(train_generato history Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^history = model.fit(train_gen,$/;" v history Detector/Version_2_Detector/train_SegModel_v2.py /^history = model.fit(train_gen,$/;" v hook Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^ def hook(images, augmenter, parents, default):$/;" f function:load_image_gt file: +hsv WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)$/;" v +hsv data/Blood SmearAnalysis/BASOPHILS/test.py /^hsv = cv.cvtColor(img, cv.COLOR_BGR2HSV)$/;" v iaa Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/nucleus/nucleus.py /^from imgaug import augmenters as iaa$/;" x nameref:unknown:augmenters iaa Aniket_MASK_RCNN/MaskRCNN_3/mask_rcnn3.py /^from imgaug import augmenters as iaa$/;" x nameref:unknown:augmenters iaa Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^from imgaug import augmenters as iaa$/;" x nameref:unknown:augmenters iaa Aniket_MASK_RCNN/MaskRCNN_3/model_test_slide.py /^from imgaug import augmenters as iaa$/;" x nameref:unknown:augmenters +id_token .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" z +id_token_jwt .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" z identity_block Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def identity_block(input_tensor, kernel_size, filters, stage, block,$/;" f ignore exp/demo.py /^ ignore, target = torch.max( output, 1 )$/;" v im Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ im = Image.open(img_file)$/;" v @@ -12922,6 +13293,10 @@ im Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ im = np.array(im) \/ im Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ im = Image.open(img_file)$/;" v im Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ im = im.resize((360, 360))$/;" v im Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ im = np.array(im) \/ 255.0$/;" v +im Detector/samples/ims.py /^im = cv2.imread('basophil_1.jpg')$/;" v +im Detector/samples/ims.py /^im = cv2.resize(im,(1000,1000))$/;" v +im WaterShedAlgo/find_upper_and_lower_patches.py /^ im = cv2.imread(images,cv2.IMREAD_COLOR)$/;" v +im WaterShedAlgo/find_upper_and_lower_patches.py /^ im = np.array(im)$/;" v im exp/demo.py /^im = cv2.imread(args.input)$/;" v im_target exp/demo.py /^ im_target = target.data.cpu().numpy()$/;" v im_target_rgb exp/demo.py /^ im_target_rgb = im_target_rgb.reshape( im.shape ).astype( np.uint8 )$/;" v @@ -12934,6 +13309,11 @@ image Detector/MSBlobDetector/Blob_Detector_Sobel.py /^ image = imgs$/;" v image Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ image = imgs$/;" v image Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ image = imgs$/;" v image Detector/MSBlobDetector/test.py /^ image = imgs$/;" v +image WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ image = cv2.imread(image_names)$/;" v +image WaterShedAlgo/k_means_clustering.py /^image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)$/;" v +image WaterShedAlgo/k_means_clustering.py /^image = cv2.imread('slide_9.png')$/;" v +image WaterShedAlgo/make_colour_cluster.py /^ image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)$/;" v +image WaterShedAlgo/make_colour_cluster.py /^ image = cv2.imread(total_files_list[0])$/;" v image_gray Detector/MSBlobDetector/Blob_Detector_Grayscale.py /^ image_gray = imgs$/;" v image_gray Detector/MSBlobDetector/Blob_Detector_Sobel.py /^ image_gray = imgs$/;" v image_gray Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ image_gray = imgs$/;" v @@ -12945,6 +13325,9 @@ image_id Aniket_MASK_RCNN/MaskRCNN_3/model_test_slide.py /^image_id = random.cho image_ids Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^ def image_ids(self):$/;" m class:Dataset image_meta Aniket_MASK_RCNN/MaskRCNN_3/mask_rcnn3.py /^original_image, image_meta, gt_class_id, gt_bbox, gt_mask =\\$/;" v image_meta Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^original_image, image_meta, gt_class_id, gt_bbox, gt_mask =\\$/;" v +image_name data/dataset.py /^ image_name = image.attributes['name'].value$/;" v +image_name_to_save WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ image_name_to_save = image_names.split('\/')[-1]$/;" v +image_names data/dataset.py /^ image_names = list(annotations.keys())$/;" v image_reference Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^ def image_reference(self, image_id):$/;" m class:Dataset image_reference Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/balloon/balloon.py /^ def image_reference(self, image_id):$/;" m class:BalloonDataset image_reference Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ def image_reference(self, image_id):$/;" m class:CocoDataset @@ -12954,6 +13337,8 @@ image_reference Aniket_MASK_RCNN/MaskRCNN_3/mask_rcnn3.py /^ def image_refere image_reference Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^ def image_reference(self, image_id):$/;" m class:BloodDataset image_reference Aniket_MASK_RCNN/MaskRCNN_3/model_test_slide.py /^ def image_reference(self, image_id):$/;" m class:BloodDataset image_seg_to_tfexample Segmentation/build_data.py /^def image_seg_to_tfexample(image_data, filename, height, width, seg_data):$/;" f +images data/dataset.py /^ images = doc.getElementsByTagName('image')$/;" v +imarr WaterShedAlgo/find_avg.py /^ imarr=numpy.array(Image.open(im),dtype=numpy.float)$/;" v img Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ img = get_img$/;" v img Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ img, heatmap, heatmap_, superimposed_img = get_jet_img(img, heatmap)$/;" v img Detector/MSBlobDetector/Blob_Detector_Grayscale.py /^ img = cv2.imread(im_name, cv2.IMREAD_UNCHANGED)$/;" v @@ -12962,6 +13347,15 @@ img Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ img = get_img$/;" v img Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ img, heatmap, heatmap_, superimposed_img = get_jet_img(img, heatmap)$/;" v img Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ img = get_img$/;" v img Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ img, heatmap, heatmap_, superimposed_img = get_jet_img(img, heatmap)$/;" v +img WaterShedAlgo/avg_thresh.py /^img = cv2.imread('slide_9.png', cv2.IMREAD_COLOR)$/;" v +img WaterShedAlgo/colour_thresholding.py /^img = cv2.imread('slide_1.png', cv2.IMREAD_COLOR)$/;" v +img WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ img = image.copy()$/;" v +img WaterShedAlgo/test_ws.py /^img = cv2.imread('slide_1.png', cv2.IMREAD_COLOR)$/;" v +img WaterShedAlgo/test_ws.py /^img = cv2.resize(img,(667, 500), cv2.INTER_AREA)$/;" v +img WaterShedAlgo/water_Shed.py /^img = cv.imread('slide_9.png')$/;" v +img WaterShedAlgo/water_Shed.py /^img = cv.resize(img,(400, 300), cv.INTER_AREA)$/;" v +img data/Blood SmearAnalysis/BASOPHILS/test.py /^img = cv.imread('IMG_2799.jpg')$/;" v +img data/Blood SmearAnalysis/BASOPHILS/test.py /^img = cv.resize(img,(400, 300), cv.INTER_AREA)$/;" v img_array Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ img_array = np.expand_dims(get_img, axis=0)$/;" v img_array Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ img_array = np.expand_dims(get_img, axis=0)$/;" v img_array Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ img_array = np.expand_dims(get_img, axis=0)$/;" v @@ -12997,6 +13391,7 @@ imgs Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ imgs = cv2.Gaussian imgs Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ imgs = sobel_imgs[2]$/;" v imgs Detector/MSBlobDetector/test.py /^ imgs = cv2.GaussianBlur(imgs,(5,5),0)$/;" v imgs Detector/MSBlobDetector/test.py /^ imgs = sobel_imgs[2]$/;" v +imlist WaterShedAlgo/find_avg.py /^imlist=[filename for filename in allfiles if filename[-4:] in [".png",".PNG"]]$/;" v impute .dvc/plots/confusion.json /^ "impute": "xy_count",$/;" s object:spec.transform.1 impute .dvc/plots/confusion.json /^ "impute": "xy_count",$/;" s object:spec.transform.2 impute .dvc/plots/confusion_normalized.json /^ "impute": "xy_count",$/;" s object:spec.transform.1 @@ -13020,9 +13415,11 @@ input_layer Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^input_layer = input_layer Detector/GradCam_Prototype/evaluate_model.py /^input_layer = tf.keras.Input(shape=(H, W, C))$/;" v input_layer Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^input_layer = tf.keras.Input(shape=(H, W, C))$/;" v install_reqs Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/setup.py /^ install_reqs = []$/;" v +invalid .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" b item_name Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^ item_name = item.split('\/')[1]$/;" v item_name Detector/GradCam_Prototype/evaluate_model.py /^ item_name = item.split('\/')[1]$/;" v item_name Detector/Version_2_Detector/train_SegModel_v2.py /^ item_name = item.split('\/')[1]$/;" v +itm WaterShedAlgo/get_colour_cluster.py /^itm = pickle.load(file)$/;" v joinaggregate .dvc/plots/confusion.json /^ "joinaggregate": [$/;" a object:spec.transform.3 joinaggregate .dvc/plots/confusion_normalized.json /^ "joinaggregate": [$/;" a object:spec.transform.3 kernel Detector/MSBlobDetector/Blob_Detector_Sobel.py /^ kernel = np.ones((5,5),np.uint8) #cv2.getGaussianKernel(5, 0)$/;" v @@ -13031,6 +13428,9 @@ kernel Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ kernel = np.ones( kernel Detector/MSBlobDetector/test.py /^ kernel = np.ones((5,5),np.uint8) #cv2.getGaussianKernel(5, 0)$/;" v kernel Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ kernel = np.ones((10,10),np.uint8) #cv2.getGaussianKernel(5, 0)$/;" v kernel Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ kernel = np.ones((10,10),np.uint8) #cv2.getGaussianKernel(5, 0)$/;" v +kernel WaterShedAlgo/test_ws.py /^kernel = np.ones((2,2),np.uint8)$/;" v +kernel WaterShedAlgo/water_Shed.py /^kernel = np.ones((3,3),np.uint8)$/;" v +kernel data/Blood SmearAnalysis/BASOPHILS/test.py /^kernel = np.ones((5,5),np.uint8)$/;" v key .dvc/plots/confusion.json /^ "key": "",$/;" s object:spec.transform.1 key .dvc/plots/confusion.json /^ "key": "",$/;" s object:spec.transform.2 key .dvc/plots/confusion_normalized.json /^ "key": "",$/;" s object:spec.transform.1 @@ -13043,6 +13443,7 @@ label .dvc/plots/scatter.json /^ "label": {$/;" o object: label_colours exp/demo.py /^label_colours = np.random.randint(255,size=(100,3))$/;" v labels Classifier/classification_aniket.py /^labels = (train_generator.class_indices)$/;" v labels Classifier/classification_aniket.py /^labels = dict((v,k) for k,v in labels.items())$/;" v +labels WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ labels = watershed(-D, markers, mask=mask)$/;" v labels exp/demo.py /^labels = labels.reshape(im.shape[0]*im.shape[1])$/;" v labels exp/demo.py /^labels = segmentation.slic(im, compactness=args.compactness, n_segments=args.num_superpixels)$/;" v labels_per_sp exp/demo.py /^ labels_per_sp = im_target[ l_inds[ i ] ]$/;" v @@ -13070,6 +13471,7 @@ layer .dvc/plots/scatter.json /^ "layer": [$/;" a object:laye layer .dvc/plots/scatter.json /^ "layer": [$/;" a object:layer.0 layer .dvc/plots/scatter.json /^ "layer": [$/;" a object:layer.1 layer .dvc/plots/scatter.json /^ "layer": [$/;" a +list_ WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^list_ = [ 3329, 6224, 7438, 10555, 11975, 13526, 14744]$/;" v load_balloon Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/balloon/balloon.py /^ def load_balloon(self, dataset_dir, subset):$/;" m class:BalloonDataset load_blood Aniket_MASK_RCNN/MaskRCNN_3/mask_rcnn3.py /^ def load_blood(self, dataset_dir, subset):$/;" m class:BloodDataset load_blood Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^ def load_blood(self, dataset_dir, subset):$/;" m class:BloodDataset @@ -13089,6 +13491,7 @@ load_mask Aniket_MASK_RCNN/MaskRCNN_3/model_test_slide.py /^ def load_mask(se load_nucleus Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/nucleus/nucleus.py /^ def load_nucleus(self, dataset_dir, subset):$/;" m class:NucleusDataset load_shapes Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/shapes/shapes.py /^ def load_shapes(self, count, height, width):$/;" m class:ShapesDataset load_weights Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^ def load_weights(self, filepath, by_name=False, exclude=None):$/;" m class:MaskRCNN +localMax WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ localMax = peak_local_max(D, indices=False, min_distance=20,$/;" v loess .dvc/plots/smooth.json /^ "loess": "",$/;" s object:transform.0 log Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def log(text, array=None):$/;" f log2_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def log2_graph(x):$/;" f @@ -13105,6 +13508,10 @@ loss Detector/Version_2_Detector/history_classification_model_v2_20e.json /^{"lo loss Detector/Version_3_GRAD_CAM/history_classification_model_Gradcam_v3_20e.json /^{"loss":{"0":1.5502912998,"1":1.1300779581,"2":0.9987698197,"3":0.8822384477,"4":0.7874717116,"5/;" o loss exp/demo.py /^ loss = loss_fn(output, target)$/;" v loss_fn exp/demo.py /^loss_fn = torch.nn.CrossEntropyLoss()$/;" v +lower_blue WaterShedAlgo/avg_thresh.py /^lower_blue = np.array([54, 38, 197])$/;" v +lower_blue WaterShedAlgo/colour_thresholding.py /^lower_blue = np.array([113, 4, 123])$/;" v +lower_blue WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ lower_blue = np.array([100,20,20])$/;" v +lower_blue data/Blood SmearAnalysis/BASOPHILS/test.py /^lower_blue = np.array([100,20,20])$/;" v lr Classifier/Classifier_model_v2/history_classification_model_v2_150e.json /^{"loss":{"0":2.8016490936,"1":2.4731841087,"2":2.2225644588,"3":2.0351891518,"4":1.8644064665,"5/;" o lr Classifier/Classifier_model_v4/history_classification_model_v4_150e.json /^{"loss":{"0":2.7692947388,"1":2.3991117477,"2":2.1364119053,"3":1.9868150949,"4":1.8946658373,"5/;" o lr Detector/Version_2_Detector/history_classification_model_v2_100e.json /^{"loss":{"0":1.3461431265,"1":0.6267504096,"2":0.4135994017,"3":0.2969979644,"4":0.2387731522,"5/;" o @@ -13128,8 +13535,25 @@ mark .dvc/plots/scatter.json /^ "mark": {$/;" o objec mark .dvc/plots/scatter.json /^ "mark": "point"$/;" s object:layer.0.layer.0 mark .dvc/plots/scatter.json /^ "mark": "point",$/;" s object:layer.0.layer.1 mark .dvc/plots/smooth.json /^ "mark": {$/;" o +markers WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ markers = ndimage.label(localMax, structure=np.ones((3, 3)))[0]$/;" v +markers WaterShedAlgo/test_ws.py /^markers = cv2.watershed(img,markers)$/;" v +markers WaterShedAlgo/test_ws.py /^markers = markers+1$/;" v +markers WaterShedAlgo/test_ws.py /^ret, markers = cv2.connectedComponents(sure_fg)$/;" v +markers WaterShedAlgo/water_Shed.py /^markers = cv.watershed(img,markers)$/;" v +markers WaterShedAlgo/water_Shed.py /^markers = markers+1$/;" v +markers WaterShedAlgo/water_Shed.py /^ret, markers = cv.connectedComponents(sure_fg)$/;" v +mask WaterShedAlgo/avg_thresh.py /^mask = cv2.inRange(img, lower_blue, upper_blue)$/;" v +mask WaterShedAlgo/colour_thresholding.py /^mask = cv2.inRange(img, lower_blue, upper_blue)$/;" v +mask WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ mask = cv2.dilate(mask, None, iterations=3)$/;" v +mask WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ mask = cv2.inRange(hsv, lower_blue, upper_blue)$/;" v +mask data/Blood SmearAnalysis/BASOPHILS/test.py /^mask = cv.inRange(hsv, lower_blue, upper_blue)$/;" v maskUtils Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^from pycocotools import mask as maskUtils$/;" x nameref:unknown:mask +mask_1 WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ mask_1 = np.zeros(gray.shape, dtype="uint8")$/;" v mask_to_rle Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/nucleus/nucleus.py /^def mask_to_rle(image_id, mask, scores):$/;" f +max_r WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ max_r = int(r)$/;" v +max_r WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ max_r = 0$/;" v +max_x WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ max_x = int(x)$/;" v +max_y WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ max_y = int(y)$/;" v maximum Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ maximum = np.amax(added_heatmap)$/;" v maximum Detector/MSBlobDetector/Sobel_Maker_2.py /^maximum = np.amax(blurred_thresh)$/;" v maximum Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ maximum = np.amax(added_heatmap)$/;" v @@ -13245,6 +13669,18 @@ np Detector/Version_2_Detector/train_SegModel_v2.py /^import numpy as np$/;" I n np Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^import numpy as np$/;" I nameref:module:numpy np Detector/utils/GRAD_CAM.py /^import numpy as np$/;" I nameref:module:numpy np Segmentation/remove_gt_colormap.py /^import numpy as np$/;" I nameref:module:numpy +np WaterShedAlgo/avg_thresh.py /^import numpy as np$/;" I nameref:module:numpy +np WaterShedAlgo/colour_thresholding.py /^import numpy as np$/;" I nameref:module:numpy +np WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^import cv2, numpy as np$/;" I nameref:module:numpy +np WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^import numpy as np$/;" I nameref:module:numpy +np WaterShedAlgo/find_avg.py /^import numpy as np$/;" I nameref:module:numpy +np WaterShedAlgo/find_upper_and_lower_patches.py /^import numpy as np$/;" I nameref:module:numpy +np WaterShedAlgo/k_means_clustering.py /^import cv2, numpy as np$/;" I nameref:module:numpy +np WaterShedAlgo/make_colour_cluster.py /^import numpy as np$/;" I nameref:module:numpy +np WaterShedAlgo/test_ws.py /^import numpy as np$/;" I nameref:module:numpy +np WaterShedAlgo/water_Shed.py /^import numpy as np$/;" I nameref:module:numpy +np data/Blood SmearAnalysis/BASOPHILS/test.py /^import numpy as np$/;" I nameref:module:numpy +np data/dataset.py /^import numpy as np$/;" I nameref:module:numpy np exp/demo.py /^import numpy as np$/;" I nameref:module:numpy np_utils Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^from keras import utils as np_utils$/;" x nameref:unknown:utils np_utils Detector/GradCam_Prototype/evaluate_model.py /^from keras import utils as np_utils$/;" x nameref:unknown:utils @@ -13266,6 +13702,9 @@ op .dvc/plots/confusion_normalized.json /^ "op": "count", op .dvc/plots/confusion_normalized.json /^ "op": "sum",$/;" s object:spec.transform.3.joinaggregate.0 opacity .dvc/plots/linear.json /^ "opacity": {$/;" o object:layer.0.layer.1.encoding opacity .dvc/plots/scatter.json /^ "opacity": {$/;" o object:layer.0.layer.1.encoding +opening WaterShedAlgo/test_ws.py /^opening = cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel, iterations = 1)$/;" v +opening WaterShedAlgo/water_Shed.py /^opening = cv.morphologyEx(thresh,cv.MORPH_OPEN,kernel, iterations = 2)$/;" v +opening data/Blood SmearAnalysis/BASOPHILS/test.py /^opening = cv.morphologyEx(mask,cv.MORPH_OPEN,kernel, iterations = 2)$/;" v opt Classifier/Classifier_model_v4/classification_aniket.py /^opt = Adam(learning_rate=1e-5)$/;" v opt Classifier/classification_aniket.py /^opt = Adam(learning_rate=1e-5)$/;" v optim exp/demo.py /^import torch.optim as optim$/;" I nameref:module:torch.optim @@ -13274,6 +13713,7 @@ optimizer exp/demo.py /^optimizer = optim.SGD(model.parameters(), lr=args.lr, mo original_image Aniket_MASK_RCNN/MaskRCNN_3/mask_rcnn3.py /^original_image, image_meta, gt_class_id, gt_bbox, gt_mask =\\$/;" v original_image Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^original_image, image_meta, gt_class_id, gt_bbox, gt_mask =\\$/;" v original_image Aniket_MASK_RCNN/MaskRCNN_3/model_test_slide.py /^original_image = cv2.imread("..\/..\/Detector\/samples_1\/slide_12.png")$/;" v +out WaterShedAlgo/find_avg.py /^out=Image.fromarray(arr,mode="RGB")$/;" v output exp/demo.py /^ output = model( data )[ 0 ]$/;" v output exp/demo.py /^ output = output.permute( 1, 2, 0 ).contiguous().view( -1, args.nChannel )$/;" v overlaps_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def overlaps_graph(boxes1, boxes2):$/;" f @@ -13293,6 +13733,7 @@ parse_image_meta_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^de parser Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/balloon/balloon.py /^ parser = argparse.ArgumentParser($/;" v parser Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ parser = argparse.ArgumentParser($/;" v parser Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/nucleus/nucleus.py /^ parser = argparse.ArgumentParser($/;" v +parser data/dataset.py /^parser = argparse.ArgumentParser()$/;" v parser exp/demo.py /^parser = argparse.ArgumentParser(description='PyTorch Unsupervised Segmentation')$/;" v patch Aniket_MASK_RCNN/color_palatte.py /^patch = []$/;" v path24476 docs/Hematopoiesis_simple.svg /^ d="m 1324.5107,570.40282 c 0.2028,12.98435 -4.4636,23.39897 -13.9988,31.24379 -9.7383,8.1/;" i @@ -14882,6 +15323,14 @@ plt Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^import matplotlib.pypl plt Detector/Version_2_Detector/train_SegModel_v2.py /^import matplotlib.pyplot as plt$/;" I nameref:module:matplotlib.pyplot plt Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^import matplotlib.pyplot as plt$/;" I nameref:module:matplotlib.pyplot plt Detector/utils/GRAD_CAM.py /^import matplotlib.pyplot as plt$/;" I nameref:module:matplotlib.pyplot +plt WaterShedAlgo/avg_thresh.py /^from matplotlib import pyplot as plt$/;" x nameref:unknown:pyplot +plt WaterShedAlgo/colour_thresholding.py /^from matplotlib import pyplot as plt$/;" x nameref:unknown:pyplot +plt WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^import matplotlib.pyplot as plt$/;" I nameref:module:matplotlib.pyplot +plt WaterShedAlgo/find_avg.py /^import matplotlib.pyplot as plt$/;" I nameref:module:matplotlib.pyplot +plt WaterShedAlgo/make_colour_cluster.py /^import matplotlib.pyplot as plt$/;" I nameref:module:matplotlib.pyplot +plt WaterShedAlgo/test_ws.py /^from matplotlib import pyplot as plt$/;" x nameref:unknown:pyplot +plt WaterShedAlgo/water_Shed.py /^from matplotlib import pyplot as plt$/;" x nameref:unknown:pyplot +plt data/Blood SmearAnalysis/BASOPHILS/test.py /^from matplotlib import pyplot as plt$/;" x nameref:unknown:pyplot precision Classifier/Classifier_model_v2/history_classification_model_v2_150e.json /^{"loss":{"0":2.8016490936,"1":2.4731841087,"2":2.2225644588,"3":2.0351891518,"4":1.8644064665,"5/;" o precision Classifier/Classifier_model_v4/history_classification_model_v4_150e.json /^{"loss":{"0":2.7692947388,"1":2.3991117477,"2":2.1364119053,"3":1.9868150949,"4":1.8946658373,"5/;" o pred Classifier/classification_aniket.py /^pred = model.predict_generator(test_generator,$/;" v @@ -14903,6 +15352,12 @@ r Detector/MSBlobDetector/Blob_Detector_Sobel.py /^ y, x, r = blob$/; r Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ y, x, r = blob$/;" v r Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ y, x, r = blob$/;" v r Detector/MSBlobDetector/test.py /^ y, x, r = blob$/;" v +r WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ r = iter[2]$/;" v +r_max WaterShedAlgo/find_upper_and_lower_patches.py /^ r_max = im[..., 0].max()$/;" v +r_max_list WaterShedAlgo/find_upper_and_lower_patches.py /^r_max_list = []$/;" v +r_min WaterShedAlgo/find_upper_and_lower_patches.py /^ r_min = im[..., 0].min()$/;" v +r_min_list WaterShedAlgo/find_upper_and_lower_patches.py /^r_min_list = []$/;" v +rad_circles_coords WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ rad_circles_coords = []$/;" v radialGradient16107 docs/Hematopoiesis_simple.svg /^ r="819.20001" \/>$/;" d radialGradient16107 docs/Hematopoiesis_simple.svg /^ r="819.20001" \/>$/;" i radialGradient16109 docs/Hematopoiesis_simple.svg /^ r="819.20001" \/>$/;" d @@ -16762,8 +17217,15 @@ read_image_dims Segmentation/build_data.py /^ def read_image_dims(self, image_d recall Classifier/Classifier_model_v2/history_classification_model_v2_150e.json /^{"loss":{"0":2.8016490936,"1":2.4731841087,"2":2.2225644588,"3":2.0351891518,"4":1.8644064665,"5/;" o recall Classifier/Classifier_model_v4/history_classification_model_v4_150e.json /^{"loss":{"0":2.7692947388,"1":2.3991117477,"2":2.1364119053,"3":1.9868150949,"4":1.8946658373,"5/;" o refine_detections_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def refine_detections_graph(rois, probs, deltas, window, config):$/;" f +refresh_token .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s res Detector/GradCam_Prototype/evaluate_model.py /^res = dict(zip(model.metrics_names, model.evaluate(test_gen, steps=len(test_idx)\/\/128)))$/;" v res Detector/Version_2_Detector/train_SegModel_v2.py /^res = dict(zip(model.metrics_names, model.evaluate(test_gen, steps=len(test_idx)\/\/128)))$/;" v +res WaterShedAlgo/avg_thresh.py /^res = cv2.bitwise_and(img,img, mask= mask)$/;" v +res WaterShedAlgo/colour_thresholding.py /^res = cv2.bitwise_and(img,img, mask= mask)$/;" v +res WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ res = cv2.bitwise_and(img,img, mask= mask)$/;" v +res data/Blood SmearAnalysis/BASOPHILS/test.py /^res = cv.bitwise_and(hsv,hsv, mask= mask)$/;" v +reshape WaterShedAlgo/k_means_clustering.py /^reshape = image.reshape((image.shape[0] * image.shape[1], 3))$/;" v +reshape WaterShedAlgo/make_colour_cluster.py /^ reshape = image.reshape((image.shape[0] * image.shape[1], 3))$/;" v resize Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def resize(image, output_shape, order=1, mode='constant', cval=0, clip=True,$/;" f resize_image Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def resize_image(image, min_dim=None, max_dim=None, min_scale=None, mode="square"):$/;" f resize_mask Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def resize_mask(mask, scale, padding, crop=None):$/;" f @@ -16776,6 +17238,11 @@ ret Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ ret, thres = c ret Detector/MSBlobDetector/Sobel_Maker_2.py /^ ret, thres = cv2.threshold(imgs,0,mean,cv2.THRESH_OTSU)$/;" v ret Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ ret, thres = cv2.threshold(heatmap_,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)$/;" v ret Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ ret, thres = cv2.threshold(heatmap_,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)$/;" v +ret WaterShedAlgo/test_ws.py /^ret, markers = cv2.connectedComponents(sure_fg)$/;" v +ret WaterShedAlgo/test_ws.py /^ret, thresh = cv2.threshold(gray,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)$/;" v +ret WaterShedAlgo/water_Shed.py /^ret, markers = cv.connectedComponents(sure_fg)$/;" v +ret WaterShedAlgo/water_Shed.py /^ret, sure_fg = cv.threshold(dist_transform,0.7*dist_transform.max(),255,0)$/;" v +ret WaterShedAlgo/water_Shed.py /^ret, thresh = cv.threshold(gray,0,255,cv.THRESH_BINARY_INV+cv.THRESH_OTSU)$/;" v rev_index Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^rev_index = {}$/;" v rev_index Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^rev_index = {0: 'platelet', 1: 'eosinophil', 2: 'lymphocyte', 3: 'monocyte', 4: 'basophil', 5: '/;" v rev_index Detector/GradCam_Prototype/evaluate_model.py /^rev_index = {}$/;" v @@ -16783,7 +17250,9 @@ rev_index Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^rev_index = {0: 'p rev_index Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^rev_index = {0: 'platelet', 1: 'eosinophil', 2: 'lymphocyte', 3: 'monocyte', 4: 'basophil', 5: '/;" v rev_index Detector/Version_2_Detector/train_SegModel_v2.py /^rev_index = {}$/;" v rev_index Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^rev_index = {0: 'platelet', 1: 'eosinophil', 2: 'lymphocyte', 3: 'monocyte', 4: 'basophil', 5: '/;" v +revoke_uri .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s rgb_to_hex Aniket_MASK_RCNN/color_palatte.py /^def rgb_to_hex(rgb):$/;" f +rgb_to_hsv WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^def rgb_to_hsv(r, g, b):$/;" f rle_decode Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/nucleus/nucleus.py /^def rle_decode(rle, shape):$/;" f rle_encode Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/nucleus/nucleus.py /^def rle_encode(mask):$/;" f rpn_bbox_loss Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_loss":{"0":5.9190143108,"1":1.9187240362,"2":3.0439857244,"3":2.8388522148,"4":2.370081734/;" o @@ -16792,6 +17261,7 @@ rpn_class_loss Aniket_MASK_RCNN/MaskRCNN_3/history_network_heads.json /^{"val_lo rpn_class_loss_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def rpn_class_loss_graph(rpn_match, rpn_class_logits):$/;" f rpn_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def rpn_graph(feature_map, anchors_per_location, anchor_stride):$/;" f run_graph Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^ def run_graph(self, images, outputs, image_metas=None):$/;" m class:MaskRCNN +save_path WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ save_path = 'PBC_dataset_normal_DIB_cropped\/{}\/{}'.format(folder_name,image_name_to_save)$/;" v saving Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^ from keras.engine import topology as saving$/;" x member:MaskRCNN.load_weights file: nameref:unknown:topology scale .dvc/plots/confusion.json /^ "scale": {$/;" o object:spec.layer.0.encoding.color scale .dvc/plots/confusion_normalized.json /^ "scale": {$/;" o object:spec.layer.0.encoding.color @@ -16811,6 +17281,8 @@ scale Detector/MSBlobDetector/Sobel_Maker_2.py /^ scale = i_loop$/;" scale Detector/MSBlobDetector/Sobel_Maker_2.py /^scale = 1$/;" v scale Detector/MSBlobDetector/test.py /^ scale = i_loop$/;" v scale Detector/MSBlobDetector/test.py /^ scale = 1$/;" v +scope .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s object:token_response +scopes .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" a searchKeysByVal Aniket_MASK_RCNN/MaskRCNN_3/mask_rcnn3.py /^def searchKeysByVal(dict, byVal):$/;" f searchKeysByVal Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^def searchKeysByVal(dict, byVal):$/;" f searchKeysByVal Aniket_MASK_RCNN/MaskRCNN_3/model_test_slide.py /^def searchKeysByVal(dict, byVal):$/;" f @@ -16838,6 +17310,8 @@ set_val Detector/MSBlobDetector/Blob_Detector_Sobel.py /^ set_val = int(len(u set_val Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ set_val = int(len(unique_set)\/1.2)$/;" v set_val Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ set_val = int(len(unique_set)\/1.2)$/;" v set_val Detector/MSBlobDetector/test.py /^ set_val = int(len(unique_set)\/1.2)$/;" v +shifted WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ shifted = cv2.pyrMeanShiftFiltering(image, 50, 50)$/;" v +shifted WaterShedAlgo/test_ws.py /^shifted = cv2.pyrMeanShiftFiltering(img, 30, 30)$/;" v short_index Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^short_index = {}$/;" v short_index Detector/GradCam_Prototype/evaluate_model.py /^short_index = {}$/;" v short_index Detector/Version_2_Detector/train_SegModel_v2.py /^short_index = {}$/;" v @@ -19990,10 +20464,20 @@ stop88 docs/Hematopoiesis_simple.svg /^ id="stop88" \/>$/;" i stop91 docs/Hematopoiesis_simple.svg /^ id="stop91" \/>$/;" i stop93 docs/Hematopoiesis_simple.svg /^ id="stop93" \/>$/;" i stop95 docs/Hematopoiesis_simple.svg /^ id="stop95" \/>$/;" i +sub_folders WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^sub_folders = glob.glob('PBC_dataset_normal_DIB\/*')$/;" v +sub_folders WaterShedAlgo/make_colour_cluster.py /^sub_folders = glob.glob('PBC_dataset_normal_DIB\/*')$/;" v summary Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/parallel_model.py /^ def summary(self, *args, **kwargs):$/;" m class:ParallelModel superimposed_img Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ img, heatmap, heatmap_, superimposed_img = get_jet_img(img, heatmap)$/;" v superimposed_img Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ img, heatmap, heatmap_, superimposed_img = get_jet_img(img, heatmap)$/;" v superimposed_img Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ img, heatmap, heatmap_, superimposed_img = get_jet_img(img, heatmap)$/;" v +sure_bg WaterShedAlgo/test_ws.py /^sure_bg = cv2.dilate(opening,kernel,iterations=1)$/;" v +sure_bg WaterShedAlgo/test_ws.py /^sure_bg = threshold_bg.copy()$/;" v +sure_bg WaterShedAlgo/water_Shed.py /^sure_bg = cv.dilate(opening,kernel,iterations=3)$/;" v +sure_bg data/Blood SmearAnalysis/BASOPHILS/test.py /^sure_bg = cv.dilate(opening,kernel,iterations=1)$/;" v +sure_fg WaterShedAlgo/test_ws.py /^sure_fg = np.uint8(sure_fg)$/;" v +sure_fg WaterShedAlgo/test_ws.py /^sure_fg = sure_bg.copy()$/;" v +sure_fg WaterShedAlgo/water_Shed.py /^ret, sure_fg = cv.threshold(dist_transform,0.7*dist_transform.max(),255,0)$/;" v +sure_fg WaterShedAlgo/water_Shed.py /^sure_fg = np.uint8(sure_fg)$/;" v svg docs/Hematopoiesis_simple.svg /^ inkscape:output_extension="org.inkscape.output.svg.inkscape">$/;" n uri:http://www.w3.org/2000/svg svg2 docs/Hematopoiesis_simple.svg /^ inkscape:output_extension="org.inkscape.output.svg.inkscape">$/;" i target exp/demo.py /^ target = target.cuda()$/;" v @@ -20009,12 +20493,14 @@ test .dvc/plots/confusion_normalized.json /^ "test": test Classifier/Classifier_model_v4/classification_aniket.py /^train, validate, test = \\$/;" v test Classifier/classification_aniket.py /^train, validate, test = \\$/;" v test_datagen Classifier/classification_aniket.py /^test_datagen=ImageDataGenerator(rescale=1.\/255.,$/;" v +test_files data/dataset.py /^ test_files = image_names[train_no + valid_no:]$/;" v test_gen Detector/GradCam_Prototype/evaluate_model.py /^test_gen = get_data_generator(df, test_idx, for_training=False, batch_size=128)$/;" v test_gen Detector/Version_2_Detector/train_SegModel_v2.py /^test_gen = get_data_generator(df, test_idx, for_training=False, batch_size=128)$/;" v test_generator Classifier/classification_aniket.py /^test_generator=test_datagen.flow_from_dataframe($/;" v test_idx Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^test_idx = p[train_up_to:]$/;" v test_idx Detector/GradCam_Prototype/evaluate_model.py /^test_idx = p[train_up_to:]$/;" v test_idx Detector/Version_2_Detector/train_SegModel_v2.py /^test_idx = p[train_up_to:]$/;" v +test_no data/dataset.py /^ test_no = len(image_names) - (train_no + valid_no)$/;" v text .dvc/plots/confusion.json /^ "text": {$/;" o object:spec.layer.1.encoding text .dvc/plots/confusion_normalized.json /^ "text": {$/;" o object:spec.layer.1.encoding text .dvc/plots/linear.json /^ "text": {$/;" o object:layer.1.layer.1.encoding @@ -20060,6 +20546,10 @@ thres Detector/GradCam_Prototype/GRAD_CAM_Segmentation.py /^ ret, thres = thres Detector/MSBlobDetector/Sobel_Maker_2.py /^ ret, thres = cv2.threshold(imgs,0,mean,cv2.THRESH_OTSU)$/;" v thres Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ ret, thres = cv2.threshold(heatmap_,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)$/;" v thres Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ ret, thres = cv2.threshold(heatmap_,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)$/;" v +thresh WaterShedAlgo/test_ws.py /^ret, thresh = cv2.threshold(gray,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)$/;" v +thresh WaterShedAlgo/test_ws.py /^thresh = cv2.threshold(blurred, blurred.mean(), 255,$/;" v +thresh WaterShedAlgo/water_Shed.py /^ret, thresh = cv.threshold(gray,0,255,cv.THRESH_BINARY_INV+cv.THRESH_OTSU)$/;" v +threshold_bg WaterShedAlgo/test_ws.py /^threshold_bg = thresh.copy()$/;" v title .dvc/plots/confusion.json /^ "title": "",$/;" s object:spec.layer.0.encoding.color title .dvc/plots/confusion.json /^ "title": ""$/;" s object:spec.encoding.x title .dvc/plots/confusion.json /^ "title": ""$/;" s object:spec.encoding.y @@ -20085,6 +20575,15 @@ titles Detector/MSBlobDetector/Blob_Detector_Sobel.py /^ titles = ['Laplacian titles Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ titles = ['Laplacian of Gaussian', 'Difference of Gaussian',$/;" v titles Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ titles = ['Laplacian of Gaussian', 'Difference of Gaussian',$/;" v titles Detector/MSBlobDetector/test.py /^ titles = ['Laplacian of Gaussian', 'Difference of Gaussian',$/;" v +token_expiry .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s +token_info_uri .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s +token_response .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" o +token_type .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s object:token_response +token_uri .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" s +total_files_list WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^total_files_list = []$/;" v +total_files_list WaterShedAlgo/make_colour_cluster.py /^total_files_list = []$/;" v +total_img_cnts WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^total_img_cnts = 0$/;" v +total_img_cnts WaterShedAlgo/make_colour_cluster.py /^total_img_cnts = 0$/;" v total_img_names Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^total_img_names = []$/;" v total_img_names Detector/GradCam_Prototype/evaluate_model.py /^total_img_names = []$/;" v total_img_names Detector/Version_2_Detector/train_SegModel_v2.py /^total_img_names = []$/;" v @@ -20098,6 +20597,7 @@ train Aniket_MASK_RCNN/MaskRCNN_3/model_test.py /^def train(model, dataset_dir): train Aniket_MASK_RCNN/MaskRCNN_3/model_test_slide.py /^def train(model, dataset_dir):$/;" f train Classifier/Classifier_model_v4/classification_aniket.py /^train, validate, test = \\$/;" v train Classifier/classification_aniket.py /^train, validate, test = \\$/;" v +train_files data/dataset.py /^ train_files = image_names[:train_no]$/;" v train_gen Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^train_gen = get_data_generator(df, train_idx, for_training=True, batch_size=batch_size)$/;" v train_gen Detector/Version_2_Detector/train_SegModel_v2.py /^train_gen = get_data_generator(df, train_idx, for_training=True, batch_size=batch_size)$/;" v train_generator Classifier/Classifier_model_v4/classification_aniket.py /^train_generator=datagen.flow_from_dataframe($/;" v @@ -20108,6 +20608,7 @@ train_idx Detector/GradCam_Prototype/evaluate_model.py /^train_idx = p[:train_up train_idx Detector/GradCam_Prototype/evaluate_model.py /^train_idx, valid_idx = train_idx[:train_up_to], train_idx[train_up_to:]$/;" v train_idx Detector/Version_2_Detector/train_SegModel_v2.py /^train_idx = p[:train_up_to]$/;" v train_idx Detector/Version_2_Detector/train_SegModel_v2.py /^train_idx, valid_idx = train_idx[:train_up_to], train_idx[train_up_to:]$/;" v +train_no data/dataset.py /^ train_no = int(round((args.train \/ 100) * len(image_names)))$/;" v train_up_to Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^train_up_to = int(len(df) * 0.95)$/;" v train_up_to Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^train_up_to = int(train_up_to * 0.95)$/;" v train_up_to Detector/GradCam_Prototype/evaluate_model.py /^train_up_to = int(len(df) * 0.95)$/;" v @@ -20191,10 +20692,17 @@ unique_set Detector/MSBlobDetector/Blob_Detector_Sobel.py /^ unique_set = lis unique_set Detector/MSBlobDetector/Blob_Detector_Sobel_v1.py /^ unique_set = list(set(flat))$/;" v unique_set Detector/MSBlobDetector/Blob_Detector_Sobel_v2.py /^ unique_set = list(set(flat))$/;" v unique_set Detector/MSBlobDetector/test.py /^ unique_set = list(set(flat))$/;" v +unknown WaterShedAlgo/test_ws.py /^unknown = cv2.subtract(sure_fg,sure_bg)$/;" v +unknown WaterShedAlgo/water_Shed.py /^unknown = cv.subtract(sure_bg,sure_fg)$/;" v unmold_detections Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^ def unmold_detections(self, detections, mrcnn_mask, original_image_shape,$/;" m class:MaskRCNN unmold_image Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/model.py /^def unmold_image(normalized_images, config):$/;" f unmold_mask Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/utils.py /^def unmold_mask(mask, bbox, image_shape):$/;" f +upper_blue WaterShedAlgo/avg_thresh.py /^upper_blue = np.array([250, 230, 252])$/;" v +upper_blue WaterShedAlgo/colour_thresholding.py /^upper_blue = np.array([162, 49, 158])$/;" v +upper_blue WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ upper_blue = np.array([300,245,245])$/;" v +upper_blue data/Blood SmearAnalysis/BASOPHILS/test.py /^upper_blue = np.array([300,255,255])$/;" v use_cuda exp/demo.py /^use_cuda = torch.cuda.is_available()$/;" v +user_agent .dvc/tmp/gdrive-user-credentials.json /^{"access_token": "ya29.a0AfH6SMDYwX9zeFm4rtg_F5SoRwZ0bvZNq8Gq2H3AeLxJd9JYfw8FTtYN_Ke6zcWdXyBlKy5/;" z val_accuracy Classifier/Classifier_model_v2/history_classification_model_v2_150e.json /^{"loss":{"0":2.8016490936,"1":2.4731841087,"2":2.2225644588,"3":2.0351891518,"4":1.8644064665,"5/;" o val_accuracy Classifier/Classifier_model_v4/history_classification_model_v4_150e.json /^{"loss":{"0":2.7692947388,"1":2.3991117477,"2":2.1364119053,"3":1.9868150949,"4":1.8946658373,"5/;" o val_accuracy Detector/GradCam_Prototype/history_200e.json /^{"loss":{"0":2.0645632744,"1":2.0310845375,"2":2.0178854465,"3":1.9957487583,"4":1.9383163452,"5/;" o @@ -20230,6 +20738,7 @@ val_true_positives Classifier/Classifier_model_v4/history_classification_model_v val_type Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/coco/coco.py /^ val_type = "val" if args.year in '2017' else "minival"$/;" v valid_batch_size Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^valid_batch_size = 40$/;" v valid_batch_size Detector/Version_2_Detector/train_SegModel_v2.py /^valid_batch_size = 120$/;" v +valid_files data/dataset.py /^ valid_files = image_names[train_no:train_no + valid_no]$/;" v valid_gen Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^valid_gen = get_data_generator(df, valid_idx, for_training=True, batch_size=valid_batch_size)$/;" v valid_gen Detector/Version_2_Detector/train_SegModel_v2.py /^valid_gen = get_data_generator(df, valid_idx, for_training=True, batch_size=valid_batch_size)$/;" v valid_generator Classifier/Classifier_model_v4/classification_aniket.py /^valid_generator = datagen.flow_from_dataframe($/;" v @@ -20237,6 +20746,7 @@ valid_generator Classifier/classification_aniket.py /^valid_generator = datagen. valid_idx Detector/GradCam_Prototype/CNN_Classifier_GRAD_CAM.py /^train_idx, valid_idx = train_idx[:train_up_to], train_idx[train_up_to:]$/;" v valid_idx Detector/GradCam_Prototype/evaluate_model.py /^train_idx, valid_idx = train_idx[:train_up_to], train_idx[train_up_to:]$/;" v valid_idx Detector/Version_2_Detector/train_SegModel_v2.py /^train_idx, valid_idx = train_idx[:train_up_to], train_idx[train_up_to:]$/;" v +valid_no data/dataset.py /^ valid_no = int(round((args.val \/ 100) * len(image_names)))$/;" v validate Classifier/Classifier_model_v4/classification_aniket.py /^train, validate, test = \\$/;" v validate Classifier/classification_aniket.py /^train, validate, test = \\$/;" v value .dvc/plots/confusion.json /^ "value": "white"$/;" s object:spec.layer.1.encoding.color.condition @@ -20258,6 +20768,12 @@ values .dvc/plots/linear.json /^ "values": ""$/;" s obje values .dvc/plots/scatter.json /^ "values": ""$/;" s object:data values .dvc/plots/smooth.json /^ "values": ""$/;" s object:data ver Detector/MSBlobDetector/Blob.py /^ver = (cv2.__version__).split('.')$/;" v +visualize WaterShedAlgo/k_means_clustering.py /^visualize = cv2.cvtColor(visualize, cv2.COLOR_RGB2BGR)$/;" v +visualize WaterShedAlgo/k_means_clustering.py /^visualize = visualize_colors(cluster, cluster.cluster_centers_)$/;" v +visualize WaterShedAlgo/make_colour_cluster.py /^ visualize = visualize_colors(cluster, cluster.cluster_centers_)$/;" v +visualize_colors WaterShedAlgo/k_means_clustering.py /^def visualize_colors(cluster, centroids):$/;" f +visualize_colors WaterShedAlgo/make_colour_cluster.py /^def visualize_colors(cluster, centroids):$/;" f +w WaterShedAlgo/find_avg.py /^w,h=Image.open(imlist[0]).size$/;" v weights_path Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/balloon/balloon.py /^ weights_path = COCO_WEIGHTS_PATH$/;" v weights_path Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/balloon/balloon.py /^ weights_path = model.find_last()$/;" v weights_path Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/samples/balloon/balloon.py /^ weights_path = model.get_imagenet_weights()$/;" v @@ -20340,6 +20856,7 @@ x Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^x = tf.keras.layers.MaxPool x Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^x = tf.keras.layers.MaxPooling2D((2, 2), name="max_pool4")(x_6)$/;" v x Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^x = tf.keras.layers.MaxPooling2D((2, 2), name="max_pool5")(x_9)$/;" v x Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^x = tf.keras.layers.MaxPooling2D((2, 2), name="max_pool6")(x)$/;" v +x WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ x = iter[0]$/;" v x_1 Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^x_1 = tf.keras.layers.Conv2D(16, 3, activation='relu', strides=(1, 1), name="conv_32", padding='/;" v x_2 Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^x_2 = tf.keras.layers.Conv2D(1, 3, activation='relu', strides=(1, 1), name="conv_64", padding='s/;" v x_3 Detector/Version_3_GRAD_CAM/GRAD_CAM_Seg_unav.py /^x_3 = tf.keras.layers.Conv2D(16, 3, activation='relu', strides=(1, 1), name="conv_64_2", padding/;" v @@ -20354,6 +20871,7 @@ x_test Detector/Version_2_Detector/train_SegModel_v2.py /^x_test, y_test = next( x_train Aniket_MASK_RCNN/MaskRCNN_3/Mask_RCNN/mrcnn/parallel_model.py /^ x_train = np.expand_dims(x_train, -1).astype('float32') \/ 255$/;" v xlink Segmentation/Docs_and_slides/Prototype_1_GradcamSeg.svg /^$/;" n uri:http://www.w3.org/1999/xlink +xml_str data/dataset.py /^ xml_str = annotation_xml.toprettyxml(indent="\\t")$/;" v y .dvc/plots/confusion.json /^ "y": {$/;" o object:spec.encoding y .dvc/plots/confusion_normalized.json /^ "y": {$/;" o object:spec.encoding y .dvc/plots/default.json /^ "y": {$/;" o object:encoding @@ -20371,6 +20889,7 @@ y Detector/MSBlobDetector/Sobel_Maker_2.py /^x, y = coord[0][0], coord[1][0]$/; y Detector/MSBlobDetector/test.py /^ y, x, r = blob$/;" v y Detector/Version_2_Detector/Detect_GRAD_CAM_v2.py /^ x, y = coord[0][0], coord[1][0]$/;" v y Detector/Version_2_Detector/Detect_GRAD_CAM_v2_2.py /^ x, y = coord[0][0], coord[1][0]$/;" v +y WaterShedAlgo/create_PBC_dataset_normal_DIB_cropped.py /^ y = iter[1]$/;" v y_pred Detector/Version_2_Detector/train_SegModel_v2.py /^y_pred = model.predict_on_batch(x_test)$/;" v y_pred Detector/Version_2_Detector/train_SegModel_v2.py /^y_pred = tf.math.argmax(y_pred, axis=-1)$/;" v y_test Detector/Version_2_Detector/train_SegModel_v2.py /^x_test, y_test = next(test_gen)$/;" v