Create app.py

app.py

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+import streamlit as st
+import cv2
+import mediapipe as mp
+import numpy as np
+from PIL import Image
+
+# Initialize MediaPipe
+mp_hands = mp.solutions.hands
+hands = mp_hands.Hands(static_image_mode=False, max_num_hands=1, min_detection_confidence=0.5)
+mp_drawing = mp.solutions.drawing_utils
+
+# Function to recognize gestures
+def get_gesture(landmarks):
+    thumb_tip = landmarks[4]
+    index_tip = landmarks[8]
+    
+    if thumb_tip.y < index_tip.y:
+        return 'Thumbs Up'
+    elif thumb_tip.y > landmarks[0].y:
+        return 'Thumbs Down'
+    else:
+        return 'Other Gesture'
+
+# Process hand gestures
+def process_hand(image):
+    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    results = hands.process(image_rgb)
+    
+    if results.multi_hand_landmarks:
+        for hand_landmarks in results.multi_hand_landmarks:
+            mp_drawing.draw_landmarks(image, hand_landmarks, mp_hands.HAND_CONNECTIONS)
+            
+            landmarks = hand_landmarks.landmark
+            gesture = get_gesture(landmarks)
+            
+            # Draw the recognized gesture on the image
+            cv2.putText(image, gesture, (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
+    
+    return image
+
+# Streamlit Interface
+st.title("AI Sign Language Interpreter")
+st.write("Make a thumbs up or thumbs down gesture in front of your camera.")
+
+# Upload or capture an image
+uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+if uploaded_file is not None:
+    image = np.array(Image.open(uploaded_file))
+    processed_image = process_hand(image)
+    
+    # Convert the image back to RGB for display
+    st.image(cv2.cvtColor(processed_image, cv2.COLOR_BGR2RGB), caption="Processed Output", use_column_width=True)
+else:
+    st.write("Please upload an image.")
+
+# Activate the webcam feed for live processing
+if st.button("Start Webcam"):
+    run = st.checkbox('Running')
+    cam = cv2.VideoCapture(0)
+    stframe = st.empty()
+
+    while run:
+        ret, frame = cam.read()
+        if not ret:
+            st.write("Failed to capture image")
+            break
+        
+        processed_frame = process_hand(frame)
+        stframe.image(cv2.cvtColor(processed_frame, cv2.COLOR_BGR2RGB), channels="RGB", use_column_width=True)
+        
+    cam.release()