refactoring keras retinanet

Author: bw4sz

deepforest/data/classes.csv

@@ -1 +1,2 @@
-Tree,0
+Dead,0
+Alive,1

deepforest/deepforest.py

@@ -26,15 +26,12 @@
 from deepforest.retinanet_train import main as retinanet_train
 from deepforest.retinanet_train import parse_args
 
-try:
-    from keras_retinanet import models
-    from keras_retinanet.models import convert_model
-    from keras_retinanet.bin.train import create_models
-    from keras_retinanet.preprocessing.csv_generator import CSVGenerator, _read_classes
-    from keras_retinanet.utils.eval import evaluate
-    from keras_retinanet.utils.visualization import draw_box
-except:
-    pass
+from deepforest.keras_retinanet import models
+from deepforest.keras_retinanet.models import convert_model
+from deepforest.keras_retinanet.bin.train import create_models
+from deepforest.keras_retinanet.preprocessing.csv_generator import CSVGenerator, _read_classes
+from deepforest.keras_retinanet.utils.eval import evaluate
+from deepforest.keras_retinanet.utils.visualization import draw_box
 
 
 class deepforest:

keras_retinanet/__init__.py deepforest/keras_retinanet/__init__.py

@@ -9,12 +9,9 @@
 import pandas as pd
 import tensorflow as tf
 
-try:
-    # Retinanet-viz
-    from keras_retinanet.utils import image as keras_retinanet_image
-    from keras_retinanet.utils.visualization import draw_detections
-except:
-    pass
+# Retinanet-viz
+from deepforest.keras_retinanet.utils import image as keras_retinanet_image
+from deepforest.keras_retinanet.utils.visualization import draw_detections
 
 def predict_image(model,
                   image_path=None,

keras_retinanet/backend/__init__.py deepforest/keras_retinanet/backend/__init__.py

@@ -9,30 +9,26 @@
 import sys
 import warnings
 
-try:
-    import keras
-    import keras.preprocessing.image
-    import tensorflow as tf
-except:
-    pass
-try:
-    # Retinanet
-    from keras_retinanet import layers
-    from keras_retinanet import losses
-    from keras_retinanet import models
-    from keras_retinanet.callbacks import RedirectModel
-    from keras_retinanet.callbacks.eval import Evaluate
-    from keras_retinanet.models.retinanet import retinanet_bbox
-    from keras_retinanet.preprocessing.csv_generator import CSVGenerator
-    from keras_retinanet.utils.anchors import make_shapes_callback
-    from keras_retinanet.utils.config import read_config_file, parse_anchor_parameters
-    from keras_retinanet.utils.keras_version import check_keras_version
-    from keras_retinanet.utils.model import freeze as freeze_model
-    from keras_retinanet.utils.transform import random_transform_generator
-    from keras_retinanet.utils.image import random_visual_effect_generator
-    from keras_retinanet.utils.gpu import setup_gpu
-except:
-    pass
+import keras
+import keras.preprocessing.image
+import tensorflow as tf
+
+# Retinanet
+from deepforest.keras_retinanet import layers
+from deepforest.keras_retinanet import losses
+from deepforest.keras_retinanet import models
+from deepforest.keras_retinanet.callbacks import RedirectModel
+from deepforest.keras_retinanet.callbacks.eval import Evaluate
+from deepforest.keras_retinanet.models.retinanet import retinanet_bbox
+from deepforest.keras_retinanet.preprocessing.csv_generator import CSVGenerator
+from deepforest.keras_retinanet.utils.anchors import make_shapes_callback
+from deepforest.keras_retinanet.utils.config import read_config_file, parse_anchor_parameters
+from deepforest.keras_retinanet.utils.keras_version import check_keras_version
+from deepforest.keras_retinanet.utils.model import freeze as freeze_model
+from deepforest.keras_retinanet.utils.transform import random_transform_generator
+from deepforest.keras_retinanet.utils.image import random_visual_effect_generator
+from deepforest.keras_retinanet.utils.gpu import setup_gpu
+
 from deepforest import tfrecords
 
 

keras_retinanet/backend/cntk_backend.py deepforest/keras_retinanet/backend/cntk_backend.py

@@ -17,11 +17,8 @@
 import psutil
 import tensorflow as tf
 
-try:
-    from keras_retinanet import models
-    from keras_retinanet.preprocessing.csv_generator import CSVGenerator
-except:
-    pass
+from deepforest.keras_retinanet import models
+from deepforest.keras_retinanet.preprocessing.csv_generator import CSVGenerator
 
 
 def create_tf_example(image, regression_target, class_target, fname, original_image):
@@ -248,7 +245,7 @@ def _parse_fn(example):
     loaded_image = tf.cast(loaded_image, tf.float32)
 
     # Turn loaded image from rgb into bgr and subtract imagenet means,
-    # see keras_retinanet.utils.image.preprocess_image
+    # see deepforest.keras_retinanet.utils.image.preprocess_image
     red, green, blue = tf.unstack(loaded_image, axis=-1)
 
     # Subtract imagenet means

keras_retinanet/backend/common.py deepforest/keras_retinanet/backend/common.py

@@ -17,11 +17,9 @@
     warnings.filterwarnings("ignore", category=FutureWarning)
     warnings.filterwarnings("ignore", category=DeprecationWarning)
 
-try:
-    from keras_retinanet import models
-    from keras.utils import multi_gpu_model
-except:
-    pass
+from deepforest.keras_retinanet import models
+from keras.utils import multi_gpu_model
+
 from deepforest import _ROOT
 
 

keras_retinanet/backend/dynamic.py deepforest/keras_retinanet/backend/dynamic.py

@@ -86,8 +86,8 @@ def run(self, *args, **kwargs):
 
 extensions = [
     Extension(
-        'keras_retinanet.utils.compute_overlap',
-        ['keras_retinanet/utils/compute_overlap.pyx']
+        'deepforest.keras_retinanet.utils.compute_overlap',
+        ['deepforest/keras_retinanet/utils/compute_overlap.pyx']
     ),
 ]
 

keras_retinanet/backend/tensorflow_backend.py deepforest/keras_retinanet/backend/tensorflow_backend.py

@@ -1,6 +1,6 @@
 # test loading of keras retinanet
 import os
-from keras_retinanet.utils.anchors import compute_overlap
+from deepforest.keras_retinanet.utils.anchors import compute_overlap
 import numpy as np
 
 def test_keras_retinanet():

keras_retinanet/backend/theano_backend.py deepforest/keras_retinanet/backend/theano_backend.py

@@ -9,8 +9,8 @@
 from deepforest import preprocess
 from deepforest import tfrecords
 from deepforest import utilities
-from keras_retinanet import models
-from keras_retinanet.preprocessing import csv_generator
+from deepforest.keras_retinanet import models
+from deepforest.keras_retinanet.preprocessing import csv_generator
 
 
 # Helper function to check filenames