Moved prediction code to specific functions

yolov3.py

@@ -540,40 +540,18 @@ LABELS = ["person",             # 0
           "hair drier",
           "toothbrush"]
 
-def main():
+def make_prediction(model):
     """
-    Defined starting point of source code.
+    Execute predictions with YOLO v3.
     """
-
-    # Step 3:
-    # (1) Define the model
-    # (2) Load the weight
-    # (3) Save the model
-
-    # Define the YOLO v3 model
-    yolov3 = make_yolov3_model()
-    print(yolov3.summary())
-
-    # Load the weights
-    # Source: https://pjreddie.com/media/files/yolov3.weights
-    weight_reader = WeightReader('yolov3.weights')
-
-    # Set the weights
-    weight_reader.load_weights(yolov3)
-
-    # Save the model to file
-    yolov3.save('yolov3.h5')
-
-    # Step 8:
-    # Make Prediction
-    for photo_filename in glob.glob("images/test/dog/*"):
+    for photo_filename in glob.glob("images/test/motorbike/images2.jpg"):
         # Define the expected input shape for the model
         input_w, input_h = 416, 416
 
         image, image_w, image_h = load_image_pixels(photo_filename, (input_w, input_h))
 
         # Make prediction
-        netouts = yolov3.predict(image)
+        netouts = model.predict(image)
 
         # Summarize the shape of the list of arrays
         print([a.shape for a in netouts])
@@ -600,5 +578,33 @@ def main():
         # Draw what we found
         draw_boxes(photo_filename, v_boxes, v_labels, v_scores)
 
+def main():
+    """
+    Defined starting point of source code.
+    """
+
+    # Step 3:
+    # (1) Define the model
+    # (2) Load the weight
+    # (3) Save the model
+
+    # Define the YOLO v3 model
+    yolov3 = make_yolov3_model()
+    print(yolov3.summary())
+
+    # Load the weights
+    # Source: https://pjreddie.com/media/files/yolov3.weights
+    weight_reader = WeightReader('yolov3.weights')
+
+    # Set the weights
+    weight_reader.load_weights(yolov3)
+
+    # Save the model to file
+    yolov3.save('yolov3.h5')
+
+    # Step 8:
+    # Make Prediction
+    make_prediction(yolov3)
+
 if __name__ == "__main__":
     main()