Create hand.py

hand.py

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+import cv2
+import numpy as np
+import streamlit as st
+from cvzone.HandTrackingModule import HandDetector
+
+# Streamlit app title
+st.title("Hand Tracking Drawing App")
+
+# Initialize the webcam
+cap = cv2.VideoCapture(0)
+
+# Initialize the hand detector
+detector = HandDetector(detectionCon=0.8, maxHands=2)
+
+# Streamlit placeholder for the video feed
+video_placeholder = st.empty()
+
+# Initialize drawing canvas
+height, width = 500, 800
+background_color = (0, 0, 0)
+img = np.full((height, width, 3), background_color, dtype=np.uint8)
+img_show = img.copy()
+
+# Function to draw shapes
+def draw(shape, x1, x2, y1, y2, color, thickness):
+    if shape == "line":
+        cv2.line(img, (x1, y1), (x2, y2), color, thickness)
+    elif shape == "circle":
+        cv2.circle(img, ((x2 + x1) // 2, (y2 + y1) // 2), int((np.sqrt((x2 - x1)**2 + (y2 - y1)**2)) / 2), color, thickness)
+    elif shape == "rectangle":
+        cv2.rectangle(img, (x1, y1), (x2, y2), color, thickness)
+
+# Main loop
+while True:
+    # Read a frame from the webcam
+    success, frame = cap.read()
+    if not success:
+        st.error("Failed to capture video from the webcam.")
+        break
+
+    # Detect hands in the frame
+    hands, frame = detector.findHands(frame)
+
+    # Display the frame in the Streamlit app
+    video_placeholder.image(frame, channels="BGR", use_column_width=True)
+
+    # Check for hand gestures and draw on the canvas
+    if hands:
+        # Example: Draw a line if two fingers are detected
+        if len(hands) == 2:
+            x1, y1 = hands[0]['center']
+            x2, y2 = hands[1]['center']
+            draw("line", x1, x2, y1, y2, (0, 255, 0), 5)
+
+    # Display the drawing canvas
+    st.image(img, channels="BGR", use_column_width=True)
+
+# Release the webcam
+cap.release()