| import gradio as gr | |
| import numpy as np | |
| import cv2 | |
| from model import classify_image | |
| def main(img): | |
| img = cv2.resize(img, (224,224)) | |
| img = img/255.0 | |
| img = np.expand_dims(img, axis=0) | |
| label, accuracy = classify_image(img) | |
| print(label) | |
| out = {label: accuracy} | |
| return out | |
| demo = gr.Interface(fn=main, | |
| inputs=gr.Image(), | |
| outputs=gr.Label(num_top_classes=1), allow_flagging='never') | |
| if __name__ == "__main__": | |
| demo.launch(share=True) |