Create app.py

app.py

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+import cv2
+import mediapipe as mp
+import numpy as np
+import gradio as gr
+
+# --- MediaPipe setup ---
+mp_hands = mp.solutions.hands
+hands = mp_hands.Hands(
+    static_image_mode=False,
+    max_num_hands=1,
+    min_detection_confidence=0.7,
+    min_tracking_confidence=0.5,
+)
+mp_draw = mp.solutions.drawing_utils
+
+# --- Global canvas ---
+canvas = None
+
+def paint(frame: np.ndarray) -> np.ndarray:
+    """
+    Receives a BGR frame from the browser camera,
+    returns the frame overlaid with the drawing canvas.
+    """
+    global canvas
+
+    # Convert to RGB for MediaPipe, and capture dimensions
+    rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+    h, w, _ = rgb.shape
+
+    # Initialize canvas once
+    if canvas is None:
+        canvas = np.zeros((h, w, 3), dtype=np.uint8)
+
+    # Detect hand landmarks
+    results = hands.process(rgb)
+    if results.multi_hand_landmarks:
+        hand_lms = results.multi_hand_landmarks[0]
+        # Get normalized index-finger tip coords
+        lm = hand_lms.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
+        x, y = int(lm.x * w), int(lm.y * h)
+        # Draw on the canvas: small circle or line from previous point
+        cv2.circle(canvas, (x, y), 8, (0, 0, 255), -1)
+
+    # Blend canvas with live frame
+    blended = cv2.addWeighted(frame, 0.5, canvas, 0.5, 0)
+    return blended
+
+# --- Gradio interface ---
+demo = gr.Interface(
+    fn=paint,
+    inputs=gr.Camera(type="numpy", streaming=True),
+    outputs=gr.Image(type="numpy"),
+    live=True,
+    title="🖌️ Virtual Painter",
+    description="Move your index finger in front of the camera to draw!"
+)
+
+if __name__ == "__main__":
+    demo.launch()