validation, error handling, logging and removing outdated tensorflow object detection api

.gitignore

@@ -1,2 +1,8 @@
 *.pyc
 .ipynb_checkpoints
+images
+test_images
+*.avi
+train.record
+val.record
+object_detection

create_tf_record.py

@@ -148,6 +148,7 @@ def create_tf_record(output_filename,
   writer.close()
 
 def main(_):
+  logging.getLogger().setLevel(logging.INFO)
   label_map_dict = label_map_util.get_label_map_dict('annotations/label_map.pbtxt')
 
   logging.info('Reading from Pet dataset.')

extract_towncentre.py

@@ -1,41 +1,77 @@
 import os
 import cv2
 import numpy as np
+import logging as log
 
 #Dataset from http://www.robots.ox.ac.uk/ActiveVision/Research/Projects/2009bbenfold_headpose/project.html#datasets
 
-def video2im(src, train_path='images', test_path='test_images', factor=2):
+def video2im(src='TownCentreXVID.avi', train_path='images', test_path='test_images', factor=2):
     """
     Extracts all frames from a video and saves them as jpgs
     """
 
-    os.mkdir(train_path)
-    os.mkdir(test_path)
+    try:
+        os.mkdir(train_path)
+        os.mkdir(test_path)
+    except FileExistsError as fee:
+        log.error(f"Error creating output directories - {fee.strerror}: {fee.filename}")
+        logging.getLogger().setLevel(logging.INFO)
+        log.info("delete or rename offending directory")
+        return
 
     frame = 0
     cap = cv2.VideoCapture(src)
     length = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
-    
+
     print('Total Frame Count:', length )
-    
+
     while True:
         check, img = cap.read()
         if check:
             if frame < 3600:
                 path = train_path
             else:
                 path = test_path
-            
+
             img = cv2.resize(img, (1920 // factor, 1080 // factor))
             cv2.imwrite(os.path.join(path, str(frame) + ".jpg"), img)
 
             frame += 1
             print('Processed: ',frame, end = '\r')
-        
+
         else:
             break
-    
+
     cap.release()
 
+def validate_video_path(path):
+    """
+    returns a tuple. first element of the tuple indicates whether the validation succeeded
+    second element is an optional logging message
+    """
+    if os.path.exists(path):
+        return (True, f"Processing {path}...")
+    else:
+        return (False, f"{path} does not exist")
+
+# validator=validate_video_path, processor=video2i
+def process_video_cmd_args(argv, validator=validate_video_path, processor=video2im):
+    """
+    calls video2im() with validated path or none (default path to be used) when there are no args passed
+    """
+    try:
+        path = argv[1]
+        status, msg = validator(path)
+        if status:
+            processor(src=path)
+            log.info(msg)
+        else:
+            log.error(msg)
+    except IndexError:
+        log.warning('Video file path was not passed to script arguements, trying default location, name')
+        processor()
+
+
 if __name__ == '__main__':
-    video2im('TownCentreXVID.avi')
+    import sys
+    process_video_cmd_args(sys.argv, validate_video_path, video2im)