| from pathlib import Path | |
| from time import sleep | |
| from time import time | |
| from fastai.vision.all import * | |
| from fastai.vision.widgets import * | |
| from fastbook import * | |
| from fastcore.parallel import * | |
| from fastdownload import download_url | |
| from google.colab import drive | |
| import gradio as gr | |
| from huggingface_hub import from_pretrained_fastai, notebook_login, push_to_hub_fastai | |
| import timm | |
| from torchvision.models import resnet18 | |
| import os | |
| learn = load_learner('model.pkl') | |
| labels = learn.dls.vocab | |
| def predict(img): | |
| img = PILImage.create(img) | |
| pred,pred_idx,probs = learn.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| demo=gr.Interface(fn=predict, inputs=gr.Image(), outputs=gr.Label(num_top_classes=2)).launch(share=True) | |
| if __name__ == "__main__": | |
| demo.launch() | |