chore: Change name of DecodeDetections2 layer

The previous name was non-descriptive and inconsistent with the rest of the code.
nicocurat · Apr 23, 2018 · 03fa7c4 · 03fa7c4
1 parent 5156b65
commit 03fa7c4
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Showing 11 changed files with 44 additions and 45 deletions.
diff --git a/keras_layers/keras_layer_DecodeDetections2.py b/keras_layers/keras_layer_DecodeDetections2.py
@@ -27,7 +27,7 @@
 from keras.engine.topology import InputSpec
 from keras.engine.topology import Layer
 
-class DecodeDetections2(Layer):
+class DecodeDetectionsFast(Layer):
     '''
     A Keras layer to decode the raw SSD prediction output.
 
@@ -103,11 +103,11 @@ def __init__(self,
         self.tf_img_width = tf.constant(self.img_width, dtype=tf.float32, name='img_width')
         self.tf_nms_max_output_size = tf.constant(self.nms_max_output_size, name='nms_max_output_size')
 
-        super(DecodeDetections2, self).__init__(**kwargs)
+        super(DecodeDetectionsFast, self).__init__(**kwargs)
 
     def build(self, input_shape):
         self.input_spec = [InputSpec(shape=input_shape)]
-        super(DecodeDetections2, self).build(input_shape)
+        super(DecodeDetectionsFast, self).build(input_shape)
 
     def call(self, y_pred, mask=None):
         '''
@@ -157,8 +157,7 @@ def non_normalized_coords():
         y_pred = tf.concat(values=[class_ids, confidences, xmin, ymin, xmax, ymax], axis=-1)
 
         #####################################################################################
-        # 2. Perform confidence thresholding, per-class non-maximum suppression, and
-        #    top-k filtering.
+        # 2. Perform confidence thresholding, non-maximum suppression, and top-k filtering.
         #####################################################################################
 
         batch_size = tf.shape(y_pred)[0] # Output dtype: tf.int32
@@ -264,5 +263,5 @@ def get_config(self):
             'img_height': self.img_height,
             'img_width': self.img_width,
         }
-        base_config = super(DecodeDetections2, self).get_config()
+        base_config = super(DecodeDetectionsFast, self).get_config()
         return dict(list(base_config.items()) + list(config.items()))
diff --git a/models/keras_ssd300.py b/models/keras_ssd300.py
@@ -27,7 +27,7 @@
 from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes
 from keras_layers.keras_layer_L2Normalization import L2Normalization
 from keras_layers.keras_layer_DecodeDetections import DecodeDetections
-from keras_layers.keras_layer_DecodeDetections2 import DecodeDetections2
+from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast
 
 def ssd_300(image_size,
             n_classes,
@@ -433,15 +433,15 @@ def input_channel_swap(tensor):
                                                name='decoded_predictions')(predictions)
         model = Model(inputs=x, outputs=decoded_predictions)
     elif mode == 'inference_fast':
-        decoded_predictions = DecodeDetections2(confidence_thresh=confidence_thresh,
-                                                iou_threshold=iou_threshold,
-                                                top_k=top_k,
-                                                nms_max_output_size=nms_max_output_size,
-                                                coords=coords,
-                                                normalize_coords=normalize_coords,
-                                                img_height=img_height,
-                                                img_width=img_width,
-                                                name='decoded_predictions')(predictions)
+        decoded_predictions = DecodeDetectionsFast(confidence_thresh=confidence_thresh,
+                                                   iou_threshold=iou_threshold,
+                                                   top_k=top_k,
+                                                   nms_max_output_size=nms_max_output_size,
+                                                   coords=coords,
+                                                   normalize_coords=normalize_coords,
+                                                   img_height=img_height,
+                                                   img_width=img_width,
+                                                   name='decoded_predictions')(predictions)
         model = Model(inputs=x, outputs=decoded_predictions)
     else:
         raise ValueError("`mode` must be one of 'training', 'inference' or 'inference_fast', but received '{}'.".format(mode))

diff --git a/models/keras_ssd512.py b/models/keras_ssd512.py
@@ -27,7 +27,7 @@
 from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes
 from keras_layers.keras_layer_L2Normalization import L2Normalization
 from keras_layers.keras_layer_DecodeDetections import DecodeDetections
-from keras_layers.keras_layer_DecodeDetections2 import DecodeDetections2
+from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast
 
 def ssd_512(image_size,
             n_classes,
@@ -452,15 +452,15 @@ def input_channel_swap(tensor):
                                                name='decoded_predictions')(predictions)
         model = Model(inputs=x, outputs=decoded_predictions)
     elif mode == 'inference_fast':
-        decoded_predictions = DecodeDetections2(confidence_thresh=confidence_thresh,
-                                                iou_threshold=iou_threshold,
-                                                top_k=top_k,
-                                                nms_max_output_size=nms_max_output_size,
-                                                coords=coords,
-                                                normalize_coords=normalize_coords,
-                                                img_height=img_height,
-                                                img_width=img_width,
-                                                name='decoded_predictions')(predictions)
+        decoded_predictions = DecodeDetectionsFast(confidence_thresh=confidence_thresh,
+                                                   iou_threshold=iou_threshold,
+                                                   top_k=top_k,
+                                                   nms_max_output_size=nms_max_output_size,
+                                                   coords=coords,
+                                                   normalize_coords=normalize_coords,
+                                                   img_height=img_height,
+                                                   img_width=img_width,
+                                                   name='decoded_predictions')(predictions)
         model = Model(inputs=x, outputs=decoded_predictions)
     else:
         raise ValueError("`mode` must be one of 'training', 'inference' or 'inference_fast', but received '{}'.".format(mode))

diff --git a/models/keras_ssd7.py b/models/keras_ssd7.py
@@ -26,7 +26,7 @@
 
 from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes
 from keras_layers.keras_layer_DecodeDetections import DecodeDetections
-from keras_layers.keras_layer_DecodeDetections2 import DecodeDetections2
+from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast
 
 def build_model(image_size,
                 n_classes,
@@ -407,15 +407,15 @@ def input_channel_swap(tensor):
                                                name='decoded_predictions')(predictions)
         model = Model(inputs=x, outputs=decoded_predictions)
     elif mode == 'inference_fast':
-        decoded_predictions = DecodeDetections2(confidence_thresh=confidence_thresh,
-                                                iou_threshold=iou_threshold,
-                                                top_k=top_k,
-                                                nms_max_output_size=nms_max_output_size,
-                                                coords=coords,
-                                                normalize_coords=normalize_coords,
-                                                img_height=img_height,
-                                                img_width=img_width,
-                                                name='decoded_predictions')(predictions)
+        decoded_predictions = DecodeDetectionsFast(confidence_thresh=confidence_thresh,
+                                                   iou_threshold=iou_threshold,
+                                                   top_k=top_k,
+                                                   nms_max_output_size=nms_max_output_size,
+                                                   coords=coords,
+                                                   normalize_coords=normalize_coords,
+                                                   img_height=img_height,
+                                                   img_width=img_width,
+                                                   name='decoded_predictions')(predictions)
         model = Model(inputs=x, outputs=decoded_predictions)
     else:
         raise ValueError("`mode` must be one of 'training', 'inference' or 'inference_fast', but received '{}'.".format(mode))

diff --git a/ssd300_evaluation_COCO.ipynb b/ssd300_evaluation_COCO.ipynb
@@ -43,7 +43,7 @@
     "from keras_loss_function.keras_ssd_loss import SSDLoss\n",
     "from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes\n",
     "from keras_layers.keras_layer_DecodeDetections import DecodeDetections\n",
-    "from keras_layers.keras_layer_DecodeDetections2 import DecodeDetections2\n",
+    "from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast\n",
     "from keras_layers.keras_layer_L2Normalization import L2Normalization\n",
     "from data_generator.object_detection_2d_data_generator import DataGenerator\n",
     "from eval_utils.coco_utils import get_coco_category_maps, predict_all_to_json\n",

diff --git a/ssd300_evaluation_Pascal_VOC.ipynb b/ssd300_evaluation_Pascal_VOC.ipynb
@@ -30,7 +30,7 @@
     "from keras_loss_function.keras_ssd_loss import SSDLoss\n",
     "from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes\n",
     "from keras_layers.keras_layer_DecodeDetections import DecodeDetections\n",
-    "from keras_layers.keras_layer_DecodeDetections2 import DecodeDetections2\n",
+    "from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast\n",
     "from keras_layers.keras_layer_L2Normalization import L2Normalization\n",
     "from data_generator.object_detection_2d_data_generator import DataGenerator\n",
     "from eval_utils.pascal_voc_utils import predict_all_to_txt\n",

diff --git a/ssd300_inference.ipynb b/ssd300_inference.ipynb
@@ -29,7 +29,7 @@
     "from keras_loss_function.keras_ssd_loss import SSDLoss\n",
     "from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes\n",
     "from keras_layers.keras_layer_DecodeDetections import DecodeDetections\n",
-    "from keras_layers.keras_layer_DecodeDetections2 import DecodeDetections2\n",
+    "from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast\n",
     "from keras_layers.keras_layer_L2Normalization import L2Normalization\n",
     "\n",
     "from ssd_encoder_decoder.ssd_output_decoder import decode_detections, decode_detections_fast\n",

diff --git a/ssd300_training.ipynb b/ssd300_training.ipynb
@@ -32,7 +32,7 @@
     "from keras_loss_function.keras_ssd_loss import SSDLoss\n",
     "from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes\n",
     "from keras_layers.keras_layer_DecodeDetections import DecodeDetections\n",
-    "from keras_layers.keras_layer_DecodeDetections2 import DecodeDetections2\n",
+    "from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast\n",
     "from keras_layers.keras_layer_L2Normalization import L2Normalization\n",
     "\n",
     "from ssd_encoder_decoder.ssd_input_encoder import SSDInputEncoder\n",
@@ -185,7 +185,7 @@
     "\n",
     "The SSD model contains custom objects: Neither the loss function nor the anchor box or L2-normalization layer types are contained in the Keras core library, so we need to provide them to the model loader.\n",
     "\n",
-    "This next code cell assumes that you want to load a model that was created in 'training' mode. If you want to load a model that was created in 'inference' or 'inference_fast' mode, you'll have to add the `DecodeDetections` or `DecodeDetections2` layer type to the `custom_objects` dictionary below."
+    "This next code cell assumes that you want to load a model that was created in 'training' mode. If you want to load a model that was created in 'inference' or 'inference_fast' mode, you'll have to add the `DecodeDetections` or `DecodeDetectionsFast` layer type to the `custom_objects` dictionary below."
    ]
   },
   {

diff --git a/ssd512_inference.ipynb b/ssd512_inference.ipynb
@@ -29,7 +29,7 @@
     "from keras_loss_function.keras_ssd_loss import SSDLoss\n",
     "from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes\n",
     "from keras_layers.keras_layer_DecodeDetections import DecodeDetections\n",
-    "from keras_layers.keras_layer_DecodeDetections2 import DecodeDetections2\n",
+    "from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast\n",
     "from keras_layers.keras_layer_L2Normalization import L2Normalization\n",
     "\n",
     "from ssd_encoder_decoder.ssd_output_decoder import decode_detections, decode_detections_fast\n",

diff --git a/ssd7_training.ipynb b/ssd7_training.ipynb
@@ -32,7 +32,7 @@
     "from keras_loss_function.keras_ssd_loss import SSDLoss\n",
     "from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes\n",
     "from keras_layers.keras_layer_DecodeDetections import DecodeDetections\n",
-    "from keras_layers.keras_layer_DecodeDetections2 import DecodeDetections2\n",
+    "from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast\n",
     "\n",
     "from ssd_encoder_decoder.ssd_input_encoder import SSDInputEncoder\n",
     "from ssd_encoder_decoder.ssd_output_decoder import decode_detections, decode_detections_fast\n",
@@ -167,7 +167,7 @@
     "\n",
     "The SSD model contains custom objects: Neither the loss function, nor the anchor box or detection decoding layer types are contained in the Keras core library, so we need to provide them to the model loader.\n",
     "\n",
-    "This next code cell assumes that you want to load a model that was created in 'training' mode. If you want to load a model that was created in 'inference' or 'inference_fast' mode, you'll have to add the `DecodeDetections` or `DecodeDetections2` layer type to the `custom_objects` dictionary below."
+    "This next code cell assumes that you want to load a model that was created in 'training' mode. If you want to load a model that was created in 'inference' or 'inference_fast' mode, you'll have to add the `DecodeDetections` or `DecodeDetectionsFast` layer type to the `custom_objects` dictionary below."
    ]
   },
   {

diff --git a/weight_sampling_tutorial.ipynb b/weight_sampling_tutorial.ipynb
@@ -426,7 +426,7 @@
     "from keras_loss_function.keras_ssd_loss import SSDLoss\n",
     "from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes\n",
     "from keras_layers.keras_layer_DecodeDetections import DecodeDetections\n",
-    "from keras_layers.keras_layer_DecodeDetections2 import DecodeDetections2\n",
+    "from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast\n",
     "from keras_layers.keras_layer_L2Normalization import L2Normalization\n",
     "\n",
     "from data_generator.object_detection_2d_data_generator import DataGenerator\n",