Test

utils.py

@@ -5,27 +5,27 @@ import multiprocessing
 from PIL import Image
 import numpy as np
 import itertools
-import logging
+# import logging
 import math
 import cv2
 import os
 
 
-logging.basicConfig(filename=f'{os.getcwd()}/frame_processing.log', level=logging.INFO)
-logging.info('Starting frame processing')
+# logging.basicConfig(filename=f'{os.getcwd()}/frame_processing.log', level=logging.INFO)
+# logging.info('Starting frame processing')
 fps = 0
 def read_file(name):
     global fps
     cap = cv2.VideoCapture(name)
     fps = cap.get(cv2.CAP_PROP_FPS)
     if not cap.isOpened():
-        logging.error("Cannot open Video")
+        # logging.error("Cannot open Video")
         exit()
     frames = []
     while True:
         ret,frame = cap.read()
         if not ret:
-            logging.info("Can't receive frame (stream end?). Exiting ...")
+            # logging.info("Can't receive frame (stream end?). Exiting ...")
             break
         frames.append(frame)
 
@@ -95,7 +95,7 @@ q = 3
 t = 2
 def process_video(frames_with_index):
     num_processes = multiprocessing.cpu_count()
-    logging.info(f"Using {num_processes} processes")
+    # logging.info(f"Using {num_processes} processes")
     pool = multiprocessing.Pool(num_processes)  
     # process the frames in parallel
     processed_frames = pool.map(process_frame, frames_with_index)
@@ -133,13 +133,13 @@ def each_frame(frame_and_index,processed_frames):
                 f3 = processed_frames[index+3][i,j]
                 k = (frame[i,j], f1, f2, f3)
                 freq_dict3[k]=freq_dict3.get(k,0)+1
-    logging.info(f"hist made for frame {index}")
+    # logging.info(f"hist made for frame {index}")
     return (freq_dict,freq_dict2,freq_dict3)
 
 def extract_video(processed_frame_with_index):
     processed_frames = [frame for frame, index in processed_frame_with_index]
     num_processes = multiprocessing.cpu_count()
-    logging.info(f"Using2 {num_processes} processes")
+    # logging.info(f"Using2 {num_processes} processes")
     pool = multiprocessing.Pool(num_processes)  
     # process the frames in parallel
     freq_dict_list = pool.starmap(each_frame, zip(processed_frame_with_index,itertools.repeat(processed_frames)))