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import streamlit as st
import numpy as np
from PIL import Image
import mediapipe as mp
# Try importing OpenCV and handle ImportError
try:
import cv2
except ImportError:
st.error("OpenCV is not installed. Please check the requirements.")
# 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()
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