Video Blanking Detection

black-edge-check.py

import sys
import os
import cv2 
import numpy as np 
import time

from tqdm import tqdm
from plyer import notification

# Detection threshold margin in pixels
spatial_thresh = 5 # How many black pixels will trigger detection
lum_thresh = 5 # How dark the black pixels need to be to trigger detection
skip_frames = 2 # Skip a frame unless it's a multiple of...
manually_approve = True # Confirmation prompt on detection?
window_height = 1080 # Vertical height to resize window to if img too small or too large

args = sys.argv
if (len(args) > 2):
    print(f"One file at a time please!")
   
# Create a VideoCapture object and read from input file 
cap = cv2.VideoCapture(sys.argv[1])
filename = os.path.basename(sys.argv[1])
w_res = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
h_res = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT ))
fps = int(cap.get(cv2.CAP_PROP_FPS))
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
scale_factor = window_height/h_res

print(f"Video resolution: {w_res}x{h_res}")
print(f"Video framerate: {fps}")
print(f"Video length: {total_frames} frames")
print(f"Window scale factor: {scale_factor}")
print("\n")

x_thresh = spatial_thresh
y_thresh = spatial_thresh
w_thresh = w_res - spatial_thresh
h_thresh = h_res - spatial_thresh

# Check if camera opened successfully 
if (cap.isOpened()== False):  
  print(f"Error opening {filename}") 


# Loop variables
count = 0
waiting_reset = False 
found = []

# Progress bar
for i in tqdm (range (total_frames), desc="Analysing Video..."): 

  # Read until video is completed    
    count += 1

    # Capture frame-by-frame 
    ret, frame = cap.read() 
    if ret == True:

      if skip_frames:
        if (count % skip_frames) == 0:
          continue
    
      # Resize frame
      frame = cv2.resize(frame, (0, 0), fx=scale_factor, fy=scale_factor, interpolation = cv2.INTER_AREA)

      gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
      _,thresh = cv2.threshold(gray, 0, lum_thresh, cv2.THRESH_BINARY)

      contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
      cnt = contours[0]
      x,y,w,h = cv2.boundingRect(cnt)
      # tqdm.write(f"X-{x}, Y-{y}, W-{w}, H-{h}")
      # tqdm.write(f"Margins: X-{x_thresh}, Y-{y_thresh}, W-{w_thresh}, H-{h_thresh}")

      cv2.imshow('Frame', frame)

      if x > x_thresh or y > y_thresh or w < w_thresh or h < h_thresh:
        if waiting_reset == False:
          if manually_approve == True:
            tqdm.write("\a")
            cv2.rectangle(frame, (x, y), (w, h), (255, 0, 0), 2)
            cv2.imshow('Frame', frame)
            cv2.waitKey(10)
            check = input(f"\nAt frame {count}: Any blanking visible here?")
          else:
            check = "y"
          if "y" in check.lower():
            tqdm.write("Marked frame")
            waiting_reset = True
            found.append(count)
        # else:
        #   tqdm.write("Waiting for next unqiue detection...")
      else:
        waiting_reset = False
    
      # Press Q on keyboard to  exit
      if cv2.waitKey(25) & 0xFF == ord('q'): 
        break
    
    # Break the loop 
    else:  
      break

cap.release()
print("\n")

print(f"Blanking found in frames: {found}")

# Toast notify
notification.notify(
    title='Video Blanking Checker',
    message=f'Done analysing "{filename}"',
    app_icon=None,
    timeout=5,
)