Update app.py

app.py

@@ -1,26 +1,24 @@
+import cv2
 import streamlit as st
-import pandas as pd
-import pickle
-# Load Model
-model = pickle.load(open('logreg_model.pkl', 'rb'))
-st.title('Iris Variety Prediction')
-# Form
-with st.form(key='form_parameters'):
-   sepal_length = st.slider('Sepal Length', 4.0, 8.0, 4.0)
-   sepal_width = st.slider('Sepal Width', 2.0, 4.5, 2.0)
-   petal_length = st.slider('Petal Length', 1.0, 7.0, 1.0)
-   petal_width = st.slider('Petal Width', 0.1, 2.5, 0.1)
-   st.markdown('---')
-   submitted = st.form_submit_button('Predict')
-# Data Inference
-data_inf = {
-   'sepal.length': sepal_length,
-   'sepal.width': sepal_width,
-   'petal.length': petal_length,
-   'petal.width': petal_width
-}
-data_inf = pd.DataFrame([data_inf])
-if submitted:
-   # Predict using Logistic Regression
-   y_pred_inf = model.predict(data_inf)
-   st.write('## Iris Variety = '+ str(y_pred_inf))
+
+cap = cv2.VideoCapture(0)
+
+st.title("Sign Language App")
+
+frame_placeholder = st.empty()
+
+stop_button_pressed = st.button("Stop")
+
+while cap.isOpened() and not stop_button_pressed:
+    ret, frame = cap.read()
+
+    if not ret:
+        st.write('video ended')
+        break
+    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+    frame_placeholder.image(frame, channels='RGB')
+    if cv2.waitKey(1) & 0xFF == ord('q') or stop_button_pressed:
+        break
+
+cap.release()
+cv2.destroyAllWindows()