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import cv2
from Prediction import predict_fight # Assuming you have this
# Process video: read, predict, and output labeled video
def process_video(video_path):
cap = cv2.VideoCapture(video_path)
sequence_length = 40 # Number of frames for one prediction
all_frames = []
predictions = []
# Step 1: Read all frames from the video
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
all_frames.append(frame)
cap.release()
# Step 2: Process frames in chunks of 40 to make predictions
for i in range(0, len(all_frames), sequence_length):
frames_buffer = all_frames[i:i + sequence_length] # Get a batch of 40 frames
# If the number of frames is less than 40 at the end, pad it with the last frame
if len(frames_buffer) < sequence_length:
frames_buffer += [frames_buffer[-1]] * (sequence_length - len(frames_buffer))
# Perform the prediction on the current batch of frames
fight_detected = predict_fight(frames_buffer)
# Store the prediction for this batch
predictions.append(fight_detected)
# Step 3: Create output video with labels
output_video_path = "output_labeled.mp4"
height, width, _ = all_frames[0].shape
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
out = cv2.VideoWriter(output_video_path, fourcc, 30, (width, height)) # Adjust frame rate if needed
frame_idx = 0
for pred in predictions:
label = "Violence Detected!" if pred else "No Violence"
color = (0, 0, 255) if pred else (0, 255, 0)
# For the next 40 frames, show the same label
for _ in range(sequence_length):
if frame_idx >= len(all_frames):
break
frame = all_frames[frame_idx]
cv2.putText(frame, label, (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, color, 2)
out.write(frame)
frame_idx += 1
out.release()
return output_video_path
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