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import cv2
import os
import uuid
import numpy as np
from utils import extract_frames, save_video
TEMP_DIR = "temp_videos"
os.makedirs(TEMP_DIR, exist_ok=True)
def process_live_video():
# Simulated live stream (replace with real buffer system if needed)
live_source = "sample_videos/lbw_sample.mp4"
cap = cv2.VideoCapture(live_source)
fps = cap.get(cv2.CAP_PROP_FPS)
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
duration = total_frames / fps
# Trim last 10 seconds
trim_start = max(0, duration - 10)
start_frame = int(trim_start * fps)
cap.set(cv2.CAP_PROP_POS_FRAMES, start_frame)
frames = []
while True:
ret, frame = cap.read()
if not ret:
break
frames.append(frame)
cap.release()
video_id = str(uuid.uuid4())
trimmed_path = os.path.join(TEMP_DIR, f"{video_id}_trimmed.mp4")
save_video(frames, trimmed_path, fps)
# Extract & Analyze
decision = "Analyzing..." # Placeholder, will use lbw_detector later
return trimmed_path, decision
def process_uploaded_video(video_file):
cap = cv2.VideoCapture(video_file)
fps = cap.get(cv2.CAP_PROP_FPS)
frames = []
while True:
ret, frame = cap.read()
if not ret:
break
frames.append(frame)
cap.release()
video_id = str(uuid.uuid4())
saved_path = os.path.join(TEMP_DIR, f"{video_id}_upload.mp4")
save_video(frames, saved_path, fps)
# Extract & Analyze
decision = "Analyzing..." # Placeholder for lbw_detector output
return saved_path, decision
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