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ASLmodelF.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b5650de58254be07efbc29801b40f2dae16a7898d33d5261a62eaaeed6c9e78e
+size 14532992

app.py

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+import tensorflow as tf
+import numpy as np
+import streamlit as st
+import cv2
+import av
+import mediapipe as mp
+from streamlit_webrtc import webrtc_streamer, RTCConfiguration
+
+
+# Initializing the Model
+mpHands = mp.solutions.hands
+hands = mpHands.Hands()
+
+# Initializing the drawing utils for drawing the landmarks on image
+mpDraw = mp.solutions.drawing_utils
+mpDrawingStyle = mp.solutions.drawing_styles
+
+# Load the Trained model of Sign Language
+model = tf.keras.models.load_model('ASLmodelF.h5')
+
+RTC_CONFIGURATION = RTCConfiguration({"iceServers": [{"urls": ["stun:stun.l.google.com:19302"]}]})
+ASLimg = cv2.imread('ASLimg.JPG')
+
+
+label = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M',
+         'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z']
+
+# cap = cv2.VideoCapture(0)
+class signDetection:
+    def recv(self, frame):
+        img = frame.to_ndarray(format="bgr24")
+        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        lmsList = []
+        result = hands.process(imgRGB)
+        if result.multi_hand_landmarks:
+            handLms = result.multi_hand_landmarks[0]
+            for lm in handLms.landmark:
+                h, w, c = img.shape
+                lmsList.append(lm.x)
+                lmsList.append(lm.y)
+            mpDraw.draw_landmarks(img, handLms, mpHands.HAND_CONNECTIONS, mpDrawingStyle.get_default_hand_landmarks_style(),
+                                  mpDrawingStyle.get_default_hand_connections_style())
+            lmsList = [lmsList]
+            lmsList = np.array(lmsList)
+            r = model.predict(lmsList)
+            r = np.argmax(r)
+            cv2.putText(img, f'Result = {label[r]}', (50, 40), cv2.FONT_HERSHEY_DUPLEX, 1, (0, 0, 255), 2)
+        return av.VideoFrame.from_ndarray(img, format='bgr24')
+
+def main():
+    st.title('Real Time Sign Language Detection')
+
+    st.header('Webcam Live Feed')
+    st.write("Click on start to use webcam and detect finger spellings")
+    webrtc_streamer(key='key', rtc_configuration=RTC_CONFIGURATION, video_processor_factory=signDetection)
+
+    with st.sidebar:
+        st.header('Finger Spellings')
+        st.image(image=ASLimg)
+        st.markdown('**Created by:** Manish Kumar')
+        st.markdown('Github Link: [ASL-Recognition](https://github.com/ManishKumar219/ASL-Recognition)')
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+pandas
+numpy
+matplotlib
+scikit-learn
+opencv-python
+streamlit
+streamlit_webrtc
+mediapipe
+tensorflow
+keras
+av