Video & Webcam
Real-time face analysis for video streams.
Work in Progress
This page contains example code patterns. Test thoroughly before using in production.
Webcam Detection
import cv2
from uniface import RetinaFace
from uniface.visualization import draw_detections
detector = RetinaFace()
cap = cv2.VideoCapture(0)
print("Press 'q' to quit")
while True:
ret, frame = cap.read()
if not ret:
break
faces = detector.detect(frame)
draw_detections(
image=frame,
bboxes=[f.bbox for f in faces],
scores=[f.confidence for f in faces],
landmarks=[f.landmarks for f in faces]
)
cv2.imshow("Face Detection", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
Video File Processing
import cv2
from uniface import RetinaFace
def process_video(input_path, output_path):
"""Process a video file."""
detector = RetinaFace()
cap = cv2.VideoCapture(input_path)
# Get video properties
fps = cap.get(cv2.CAP_PROP_FPS)
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
# Setup output
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
while cap.read()[0]:
ret, frame = cap.read()
if not ret:
break
faces = detector.detect(frame)
# ... process and draw ...
out.write(frame)
cap.release()
out.release()
# Usage
process_video("input.mp4", "output.mp4")
Performance Tips
Skip Frames
PROCESS_EVERY_N = 3 # Process every 3rd frame
frame_count = 0
last_faces = []
while True:
ret, frame = cap.read()
if frame_count % PROCESS_EVERY_N == 0:
last_faces = detector.detect(frame)
frame_count += 1
# Draw last_faces...
FPS Counter
import time
prev_time = time.time()
while True:
curr_time = time.time()
fps = 1 / (curr_time - prev_time)
prev_time = curr_time
cv2.putText(frame, f"FPS: {fps:.1f}", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
See Also
- Anonymize Stream - Privacy protection in video
- Batch Processing - Process multiple files
- Detection Module - Detection options
- Gaze Module - Gaze tracking