38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
|
import cv2
|
||
|
|
import time
|
||
|
|
from event_detector import detect_event
|
||
|
|
from description_generator import generate_description
|
||
|
|
from datetime import datetime
|
||
|
|
|
||
|
|
def process_video_realtime(video_path, model_type='gpt', model_name='gpt-4o'):
|
||
|
|
cap = cv2.VideoCapture(video_path)
|
||
|
|
fps = cap.get(cv2.CAP_PROP_FPS)
|
||
|
|
frame_count = 0
|
||
|
|
start_time = time.time()
|
||
|
|
|
||
|
|
while cap.isOpened():
|
||
|
|
ret, frame = cap.read()
|
||
|
|
if not ret:
|
||
|
|
break
|
||
|
|
|
||
|
|
frame_count += 1
|
||
|
|
current_time = start_time + (frame_count / fps)
|
||
|
|
|
||
|
|
# Detect events
|
||
|
|
events = detect_event(frame, current_time)
|
||
|
|
|
||
|
|
# Generate description every 5 seconds
|
||
|
|
if frame_count % int(fps * 5) == 0:
|
||
|
|
description = generate_description(events, model_type, model_name)
|
||
|
|
if description:
|
||
|
|
print(f"At {datetime.fromtimestamp(current_time).strftime('%H:%M:%S')}:")
|
||
|
|
print(description)
|
||
|
|
print()
|
||
|
|
|
||
|
|
# Real-time display (optional)
|
||
|
|
cv2.imshow('Video', frame)
|
||
|
|
if cv2.waitKey(1) & 0xFF == ord('q'):
|
||
|
|
break
|
||
|
|
|
||
|
|
cap.release()
|
||
|
|
cv2.destroyAllWindows()
|