Create app.py

app.py

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+import streamlit as st
+from huggingface_hub import InferenceClient
+import requests
+
+# Define a function to check if the given URL is valid and reachable
+def is_valid_url(url):
+    try:
+        response = requests.get(url)
+        # Check if the response status code is 200 (OK)
+        return response.status_code == 200
+    except requests.exceptions.RequestException:
+        # Return False if the URL is not reachable or any other exception occurs
+        return False
+
+# Streamlit app
+def main():
+    st.title("Image Classifier")
+    st.write("Enter the URL of an image to classify it using Hugging Face's Inference API.")
+
+    # Input for image URL
+    image_url = st.text_input("Image URL")
+
+    # Display the image if the URL is valid
+    if image_url:
+        if is_valid_url(image_url):
+            st.image(image_url, caption='Uploaded Image', use_column_width=True)
+        else:
+            st.error("The URL is not valid or the image is not accessible. Please check the URL.")
+
+    # Button to classify the image
+    if st.button("Classify Image"):
+        if not image_url:
+            st.error("Please enter a URL.")
+        elif not is_valid_url(image_url):
+            st.error("Please enter a valid URL of an accessible image.")
+        else:
+            # If the URL is valid, initialize the InferenceClient with the model ID
+            # Replace "your-model-id" with the actual model ID you want to use
+            client = InferenceClient()
+            try:
+                # Perform the classification using the client
+                response = client.image_classification(image_url)
+                # Extract the label from the first prediction
+                label = response[0]['label']  # Adjust according to the actual output structure
+                st.success(f"The image was classified as: {label}")
+            except Exception as e:
+                st.error(f"Failed to classify the image: {str(e)}")
+
+# Run the Streamlit app
+if __name__ == "__main__":
+    main()