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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() | |
| # from huggingface_hub import InferenceClient | |
| # from dotenv import load_dotenv | |
| # load_dotenv() | |
| # client = InferenceClient() | |
| # response = client.image_classification("https://upload.wikimedia.org/wikipedia/commons/thumb/3/33/Callie_the_golden_retriever_puppy.jpg/800px-Callie_the_golden_retriever_puppy.jpg") | |
| # print(response[0].label) | |