I'm trying to calculate the real time of video recording. I have a lot of videos, some of which were lost during transmission. All of them are in mp4 format. to get the duration, I recognize the time using pytesseract.image_to_string, but I get incorrect results. My approach involves capturing the frames, preprocessing the images, and using Tesseract to extract the text. However, the digit recognition is often incorrect or inconsistent. The image on which the code recognizes the numbers is incorrect: The above image gives a similar answer the time is calculated from 'data2/20240619_191208_first_frame.jpg' 19:12:66 The full code looks like this: def digit_detect(image): text = pytesseract.image_to_string(image, config='--psm 6 --oem 3 -c tessedit_char_whitelist=0123456789:') return text def resize_roi(image, x1 = 131, y1 = 11, x2 = 228, y2 = 32): roi = image[y1:y2, x1:x2] return roi def preprocess_image(image): gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) _, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) return binary # def extract_time_from_image(image): # regions = [ # (131, 11, 142, 31, '012'), # Tens of hours (0-2) # (142, 11, 155, 31, '0123456789'), # Units of hours (0-9) # (163, 11, 179, 31, '012345'), # Tens of minutes (0-5) # (179, 11, 193, 31, '0123456789'), # Units of minutes (0-9) # (202, 11, 215, 31, '012345'), # Tens of seconds (0-5) # (215, 11, 226, 31, '0123456789') # Units of seconds (0-9) # ] # digits = [] # for (x1, y1, x2, y2, whitelist) in regions: # preprocess = preprocess_image(image) # resized_roi = resize_roi(preprocess, x1, y1, x2, y2) # custom_config = f'--psm 6 --oem 3 -c tessedit_char_whitelist={whitelist}' # digit = pytesseract.image_to_string(resized_roi, config=custom_config) # digits.append(digit) # return digits folder_path = 'data/output_rec/rkbt/1' load_path = "data2" if not os.path.isdir(folder_path): print(f"Error1") exit() video_files = [f for f in os.listdir(folder_path) if f.endswith('.mp4')] for video_file in video_files: video_path = os.path.join(folder_path, video_file) cap = cv2.VideoCapture(video_path) if not cap.isOpened(): print(f"Error2") continue total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) ret, first_frame = cap.read() if not ret: print(f"Error3") cap.release() continue cap.set(cv2.CAP_PROP_POS_FRAMES, total_frames - 1) ret, last_frame = cap.read() if not ret: print(f"Error3") cap.release() continue cap.release() first_frame = resize_roi(first_frame) last_frame = resize_roi(last_frame) first_frame = preprocess_image(first_frame) last_frame = preprocess_image(last_frame) # print(extract_time_from_image(first_frame)) # print(extract_time_from_image(last_frame)) first_frame_path = os.path.join(load_path, f"{os.path.splitext(video_file)[0]}_first_frame.jpg") last_frame_path = os.path.join(load_path, f"{os.path.splitext(video_file)[0]}_last_frame.jpg") print(f"the time is calculated from '{first_frame_path}'" , digit_detect(first_frame)) print(f"the time is calculated from '{last_frame_path}'" , digit_detect(last_frame)) cv2.imwrite(first_frame_path, first_frame) cv2.imwrite(last_frame_path, last_frame) print(f"Saved images with the first and last frames for '{video_file}'") I tried to recognize each digit separately, limiting the many possible options. I also used various variations of image binarization and various parameters of pytesseract.image_to_string Continue reading...
