updated app.py

app.py

@@ -0,0 +1,28 @@
+# app.py
+
+import streamlit as st
+from transformers import pipeline
+from PIL import Image
+import requests
+
+# Load the Hugging Face pipeline for image classification
+classifier = pipeline("image-classification", model="imfarzanansari/skintelligent-acne")
+
+# Title of the Streamlit app
+st.title("Skin Condition Classification - Acne Detection")
+
+# Upload an image file
+uploaded_file = st.file_uploader("Choose an image...", type="jpg")
+
+if uploaded_file is not None:
+    # Display the uploaded image
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    # Perform image classification using the Hugging Face pipeline
+    st.write("Classifying...")
+    predictions = classifier(image)
+
+    # Display the results
+    for pred in predictions:
+        st.write(f"Label: {pred['label']}, Score: {pred['score']:.4f}")