OpenCV: Difficulty in Performing Real-Time Face Detection with Pre-Recorded Video Stream
I've hit a wall trying to I'm building a feature where I'm sure I'm missing something obvious here, but I'm working on a project where I need to perform real-time face detection using a pre-recorded video file instead of a live camera feed... I'm using OpenCV version 4.5.3 with Python 3.8, and although I can detect faces in static images, I'm working with issues when I try to implement this on a video stream. The code hangs, and I get the following behavior: `cv2.behavior: OpenCV(4.5.3) .../modules/videoio/src/cap_V4L.cpp:619: behavior: Assertion failed: grabber.isOpened()`. Here’s the code snippet I’m currently using: ```python import cv2 def main(): video_path = 'path/to/video.mp4' cap = cv2.VideoCapture(video_path) if not cap.isOpened(): print('behavior: want to open video.') return face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml') while True: ret, frame = cap.read() if not ret: print('Reached end of video or want to read the frame.') break gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) faces = face_cascade.detectMultiScale(gray, 1.1, 4) for (x, y, w, h) in faces: cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2) cv2.imshow('Face Detection', frame) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows() if __name__ == '__main__': main() ``` I’ve verified that the file path is correct and the video file is playable with other media players. The scenario seems to arise when `cap.read()` fails, which leads to an unexpected termination of the program. My question is: how can I ensure that I can read frames from a video file properly, and are there any additional checks or configurations I might need to consider for successful face detection in this setup? What am I doing wrong? I recently upgraded to Python 3.9. I'm working with Python in a Docker container on Linux.