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import cv2 | |
import gradio as gr | |
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') | |
def detect_faces(frame): | |
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) | |
faces = face_cascade.detectMultiScale(gray, 1.3, 5) | |
print(f"Detected {len(faces)} faces") | |
return len(faces) | |
import gradio as gr | |
camera = cv2.VideoCapture(0) | |
def detect_faces_in_video(): | |
success, frame = camera.read() | |
if success: | |
num_faces = detect_faces(frame) | |
return int(num_faces) | |
else: | |
return None | |
iface = gr.Interface(fn=detect_faces_in_video, inputs="webcam", outputs="number", title="Webcam Face Detection") | |
iface.launch() |