refactor structure

* create package mrcnn
* move notebooks to samples

README.md

@@ -26,27 +26,27 @@ The goal is to improve OpenStreetMap by adding high quality baseball, soccer, te
     [![Mask RCNN on 4K Video](assets/4k_video.gif)](https://www.youtube.com/watch?v=OOT3UIXZztE)
 
 # Getting Started
-* [demo.ipynb](/demo.ipynb) Is the easiest way to start. It shows an example of using a model pre-trained on MS COCO to segment objects in your own images.
+* [demo.ipynb](samples/demo.ipynb) Is the easiest way to start. It shows an example of using a model pre-trained on MS COCO to segment objects in your own images.
 It includes code to run object detection and instance segmentation on arbitrary images.
 
-* [train_shapes.ipynb](train_shapes.ipynb) shows how to train Mask R-CNN on your own dataset. This notebook introduces a toy dataset (Shapes) to demonstrate training on a new dataset.
+* [train_shapes.ipynb](samples/train_shapes.ipynb) shows how to train Mask R-CNN on your own dataset. This notebook introduces a toy dataset (Shapes) to demonstrate training on a new dataset.
 
-* ([model.py](model.py), [utils.py](utils.py), [config.py](config.py)): These files contain the main Mask RCNN implementation. 
+* ([model.py](mrcnn/model.py), [utils.py](mrcnn/utils.py), [config.py](mrcnn/config.py)): These files contain the main Mask RCNN implementation. 
 
 
-* [inspect_data.ipynb](/inspect_data.ipynb). This notebook visualizes the different pre-processing steps
+* [inspect_data.ipynb](samples/inspect_data.ipynb). This notebook visualizes the different pre-processing steps
 to prepare the training data.
 
-* [inspect_model.ipynb](/inspect_model.ipynb) This notebook goes in depth into the steps performed to detect and segment objects. It provides visualizations of every step of the pipeline.
+* [inspect_model.ipynb](samples/inspect_model.ipynb) This notebook goes in depth into the steps performed to detect and segment objects. It provides visualizations of every step of the pipeline.
 
-* [inspect_weights.ipynb](/inspect_weights.ipynb)
+* [inspect_weights.ipynb](samples/inspect_weights.ipynb)
 This notebooks inspects the weights of a trained model and looks for anomalies and odd patterns.
 
 
 # Step by Step Detection
 To help with debugging and understanding the model, there are 3 notebooks 
-([inspect_data.ipynb](inspect_data.ipynb), [inspect_model.ipynb](inspect_model.ipynb),
-[inspect_weights.ipynb](inspect_weights.ipynb)) that provide a lot of visualizations and allow running the model step by step to inspect the output at each point. Here are a few examples:
+([inspect_data.ipynb](samples/inspect_data.ipynb), [inspect_model.ipynb](samples/inspect_model.ipynb),
+[inspect_weights.ipynb](samples/inspect_weights.ipynb)) that provide a lot of visualizations and allow running the model step by step to inspect the output at each point. Here are a few examples:
 
 
 

coco.py

@@ -46,9 +46,8 @@
 import urllib.request
 import shutil
 
-from config import Config
-import utils
-import model as modellib
+from mrcnn.config import Config
+from mrcnn import model as modellib, utils
 
 # Root directory of the project
 ROOT_DIR = os.getcwd()

mrcnn/__init__.py

@@ -0,0 +1,18 @@
+import os
+import logging
+
+import matplotlib
+import numpy as np
+
+# in case you are running on machine without display, e.g. server
+if os.environ.get('DISPLAY', '') == '' \
+        and matplotlib.rcParams['backend'] != 'agg':
+    logging.warning('No display found. Using non-interactive Agg backend')
+    # https://matplotlib.org/faq/usage_faq.html
+    matplotlib.use('Agg')
+
+# parse the numpy versions
+np_version = [int(i) for i in np.version.full_version.split('.')]
+# comparing strings does not work for version lower 1.10
+if np_version >= [1, 14]:
+    np.set_printoptions(legacy='1.13')

model.py → mrcnn/model.py

@@ -8,13 +8,8 @@
 """
 
 import os
-import sys
-import glob
 import random
-import math
 import datetime
-import itertools
-import json
 import re
 import logging
 from collections import OrderedDict
@@ -25,11 +20,10 @@
 import keras
 import keras.backend as K
 import keras.layers as KL
-import keras.initializers as KI
 import keras.engine as KE
 import keras.models as KM
 
-import utils
+from mrcnn import utils
 
 # Requires TensorFlow 1.3+ and Keras 2.0.8+.
 from distutils.version import LooseVersion
@@ -1986,7 +1980,7 @@ def build(self, mode, config):
                        mrcnn_class_logits, mrcnn_class, mrcnn_bbox, mrcnn_mask,
                        rpn_rois, output_rois,
                        rpn_class_loss, rpn_bbox_loss, class_loss, bbox_loss, mask_loss]
-            model = KM.Model(inputs, outputs, name='mask_rcnn')
+            model = KM.Model(inputs, outputs, name='mrcnn')
         else:
             # Network Heads
             # Proposal classifier and BBox regressor heads
@@ -2012,11 +2006,11 @@ def build(self, mode, config):
             model = KM.Model([input_image, input_image_meta],
                              [detections, mrcnn_class, mrcnn_bbox,
                                  mrcnn_mask, rpn_rois, rpn_class, rpn_bbox],
-                             name='mask_rcnn')
+                             name='mrcnn')
 
         # Add multi-GPU support.
         if config.GPU_COUNT > 1:
-            from parallel_model import ParallelModel
+            from mrcnn.parallel_model import ParallelModel
             model = ParallelModel(model, config.GPU_COUNT)
 
         return model
@@ -2039,7 +2033,7 @@ def find_last(self):
         dir_name = os.path.join(self.model_dir, dir_names[-1])
         # Find the last checkpoint
         checkpoints = next(os.walk(dir_name))[2]
-        checkpoints = filter(lambda f: f.startswith("mask_rcnn"), checkpoints)
+        checkpoints = filter(lambda f: f.startswith("mrcnn"), checkpoints)
         checkpoints = sorted(checkpoints)
         if not checkpoints:
             return dir_name, None

shapes.py → mrcnn/shapes.py

@@ -14,8 +14,8 @@
 import numpy as np
 import cv2
 
-from config import Config
-import utils
+from mrcnn.config import Config
+from mrcnn import utils
 
 
 class ShapesConfig(Config):

visualize.py → mrcnn/visualize.py

@@ -18,7 +18,7 @@
 from matplotlib.patches import Polygon
 import IPython.display
 
-import utils
+from mrcnn import utils
 
 
 ############################################################

samples/balloon/balloon.py

@@ -42,9 +42,8 @@
 
 # Import Mask RCNN
 sys.path.append(ROOT_DIR)
-from config import Config
-import utils
-import model as modellib
+from mrcnn.config import Config
+from mrcnn import model as modellib, utils
 
 # Path to trained weights file
 COCO_WEIGHTS_PATH = os.path.join(ROOT_DIR, "mask_rcnn_coco.h5")

samples/balloon/inspect_balloon_data.ipynb

@@ -49,13 +49,13 @@
     "\n",
     "# Import Mask RCNN\n",
     "sys.path.append(ROOT_DIR)\n",
-    "import utils\n",
-    "import visualize\n",
-    "from visualize import display_images\n",
-    "import model as modellib\n",
-    "from model import log\n",
+    "import mrcnn.utils\n",
+    "import mrcnn.visualize\n",
+    "from mrcnn.visualize import display_images\n",
+    "import mrcnn.model as modellib\n",
+    "from mrcnn.model import log\n",
     "\n",
-    "import balloon\n",
+    "from samples.balloon import balloon\n",
     "\n",
     "%matplotlib inline "
    ]

samples/balloon/inspect_balloon_model.ipynb

@@ -45,13 +45,13 @@
     "\n",
     "# Import Mask RCNN\n",
     "sys.path.append(ROOT_DIR)\n",
-    "import utils\n",
-    "import visualize\n",
-    "from visualize import display_images\n",
-    "import model as modellib\n",
-    "from model import log\n",
+    "import mrcnn.utils\n",
+    "import mrcnn.visualize\n",
+    "from mrcnn.visualize import display_images\n",
+    "import mrcnn.model as modellib\n",
+    "from mrcnn.model import log\n",
     "\n",
-    "import balloon\n",
+    "from samples.balloon import balloon\n",
     "\n",
     "%matplotlib inline \n",
     "\n",

demo.ipynb → samples/demo.ipynb

@@ -33,9 +33,9 @@
     "import matplotlib.pyplot as plt\n",
     "\n",
     "import coco\n",
-    "import utils\n",
-    "import model as modellib\n",
-    "import visualize\n",
+    "import mrcnn.utils\n",
+    "import mrcnn.model as modellib\n",
+    "import mrcnn.visualize\n",
     "\n",
     "%matplotlib inline \n",
     "\n",

inspect_data.ipynb → samples/inspect_data.ipynb

@@ -39,11 +39,11 @@
     "import matplotlib.lines as lines\n",
     "from matplotlib.patches import Polygon\n",
     "\n",
-    "import utils\n",
-    "import visualize\n",
-    "from visualize import display_images\n",
-    "import model as modellib\n",
-    "from model import log\n",
+    "import mrcnn.utils\n",
+    "import mrcnn.visualize\n",
+    "from mrcnn.visualize import display_images\n",
+    "import mrcnn.model as modellib\n",
+    "from mrcnn.model import log\n",
     "\n",
     "%matplotlib inline \n",
     "\n",

inspect_model.ipynb → samples/inspect_model.ipynb

@@ -35,11 +35,11 @@
     "import matplotlib.pyplot as plt\n",
     "import matplotlib.patches as patches\n",
     "\n",
-    "import utils\n",
-    "import visualize\n",
-    "from visualize import display_images\n",
-    "import model as modellib\n",
-    "from model import log\n",
+    "import mrcnn.utils\n",
+    "import mrcnn.visualize\n",
+    "from mrcnn.visualize import display_images\n",
+    "import mrcnn.model as modellib\n",
+    "from mrcnn.model import log\n",
     "\n",
     "%matplotlib inline \n",
     "\n",

inspect_weights.ipynb → samples/inspect_weights.ipynb

@@ -31,10 +31,10 @@
     "import matplotlib.pyplot as plt\n",
     "import keras\n",
     "\n",
-    "import utils\n",
-    "import model as modellib\n",
-    "import visualize\n",
-    "from model import log\n",
+    "import mrcnn.utils\n",
+    "import mrcnn.model as modellib\n",
+    "import mrcnn.visualize\n",
+    "from mrcnn.model import log\n",
     "\n",
     "%matplotlib inline \n",
     "\n",
@@ -179,7 +179,7 @@
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "execute_result"
     }
    ],
    "source": [

train_shapes.ipynb → samples/train_shapes.ipynb

@@ -37,11 +37,11 @@
     "import matplotlib\n",
     "import matplotlib.pyplot as plt\n",
     "\n",
-    "from config import Config\n",
-    "import utils\n",
-    "import model as modellib\n",
-    "import visualize\n",
-    "from model import log\n",
+    "from mrcnn.config import Config\n",
+    "import mrcnn.utils\n",
+    "import mrcnn.model as modellib\n",
+    "import mrcnn.visualize\n",
+    "from mrcnn.model import log\n",
     "\n",
     "%matplotlib inline \n",
     "\n",