| import gradio as gr | |
| import cv2 | |
| from llm import llm | |
| import numpy as np | |
| def process_image(image): | |
| # Convert Gradio Image to OpenCV format | |
| img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR) | |
| # Perform your image processing | |
| result = llm(img) | |
| return result | |
| iface = gr.Interface(fn=process_image, inputs="image", outputs=gr.Markdown(), live=True, title="Nutrition Content Based LLM", description="The llm based project needs a clear image of only the Nutrition Facts Box at the back of a product, \n The llm shows the content and give health advice based on the Nutritions Facts.") | |
| iface.launch(share=True) |