Update app.py

app.py

@@ -0,0 +1,66 @@
+import cv2
+import gradio as gr
+
+video_path = ""
+
+def upload_video(uploaded_video):
+    global video_path
+    video_path = uploaded_video
+    return f"Video uploaded: {uploaded_video}"
+
+def process_video():
+    if not video_path:
+        return "No video uploaded. Please upload a video first."
+
+    cap = cv2.VideoCapture(video_path)
+    if not cap.isOpened():
+        return "Error: Unable to open video"
+
+    processed_frame = None
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
+        gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        faces = face_cascade.detectMultiScale(gray_frame, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
+
+        for (x, y, w, h) in faces:
+            cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
+
+        processed_frame = frame  # Save the last frame with detection
+
+    cap.release()
+    if processed_frame is not None:
+        return processed_frame
+    else:
+        return "No faces detected or video is empty."
+
+def end_processing():
+    global video_path
+    video_path = ""
+    return "Processing ended. You can upload a new video now."
+
+iface = gr.Blocks()
+
+with iface:
+    gr.Markdown("## Video Face Detection Tool")
+    
+    with gr.Row():
+        video_input = gr.Video(label="Upload Video")
+        upload_button = gr.Button("Upload")
+        upload_output = gr.Textbox(label="Upload Status")
+
+    upload_button.click(upload_video, inputs=video_input, outputs=upload_output)
+    
+    with gr.Row():
+        process_button = gr.Button("Process Video")
+        end_button = gr.Button("End and New Video")
+        process_output = gr.Image(label="Processed Video")
+        end_output = gr.Textbox(label="Process Status")
+
+    process_button.click(process_video, outputs=process_output)
+    end_button.click(end_processing, outputs=end_output)
+
+iface.launch(share=True)  # `share=True` allows Hugging Face integration