| import gradio as gr | |
| from transformers import pipeline | |
| # Load your image captioning model from Hugging Face | |
| model_name = "Mayada/AIC-transformer" # Update this with your model path | |
| captioner = pipeline("image-to-text", model=model_name) | |
| # Define a function to generate a caption from an image | |
| def generate_caption(image): | |
| result = captioner(image) | |
| return result[0]['generated_text'] | |
| # Create a Gradio interface | |
| interface = gr.Interface( | |
| fn=generate_caption, # Function to process image and return caption | |
| inputs=gr.inputs.Image(type="pil"), # Accept image input | |
| outputs="text", # Output the caption as text | |
| title="AIC-transformer-2023", # Title for your interface | |
| description="Description", # Description for users | |
| ) | |
| # Launch the Gradio interface | |
| interface.launch() | |