| from model import model | |
| import gradio as gr | |
| import numpy as np | |
| def classify_image(image): | |
| probabilities = model.predict(image.name) # Call prediction function | |
| labels = ["Category1", "Category2", "Category3", "Category4"] # Assing labels | |
| top_labels = [labels[i] for i in np.argsort(probabilities)[::-1][:4]] | |
| top_probs = [round(float(probabilities[i]), 4) for i in np.argsort(probabilities)[::-1][:4]] | |
| demo = gr.Interface( | |
| fn=classify_image, | |
| inputs=gr.inputs.Image(), | |
| outputs=gr.outputs.Label(num_top_classes=4), | |
| title="Image Classifier", | |
| description="Upload an image and get the top 4 predicted labels with probabilities.",) | |
| demo.launch() |