Update app.py

app.py

@@ -12,7 +12,6 @@ model = pipeline("image-classification", model="0x70DA/down-syndrome-classifier"
 detector = dlib.get_frontal_face_detector()
 
 # Define the prediction function
-@st.experimental_memo
 def predict(image):
     img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)  # Convert PIL Image to NumPy array
     faces = detector(img)
@@ -41,25 +40,3 @@ if uploaded_image is not None:
     st.write("Classification Results:")
     for label, score in result.items():
         st.write(f"{label}: {score:.4f}")
-
-# Endpoint to handle POST requests
-@st.experimental_memo
-def classify_from_post_request(image_data):
-    image = Image.open(image_data)
-    result = predict(image)
-    return result
-
-# Main entry point for handling POST requests
-if st._is_running_with_streamlit:
-    import streamlit as st
-    import io
-
-    st.title("Streamlit App with POST Request Support")
-
-    uploaded_image = st.file_uploader("Upload an image for classification", type=["jpg", "jpeg", "png"])
-
-    if uploaded_image is not None:
-        result = classify_from_post_request(uploaded_image)
-        st.write("Classification Results:")
-        for label, score in result.items():
-            st.write(f"{label}: {score:.4f}")