| from fastai.vision.all import * | |
| import gradio as gr | |
| 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))} | |
| with gr.Blocks(theme=gr.themes.Monochrome()) as demo: | |
| img = gr.Image(height=500, sources=["upload"]) | |
| examples = gr.Examples([ | |
| ["./imgs/dali2.jpeg"], | |
| ["./imgs/dali3.jpeg"], | |
| ["./imgs/dali4.jpeg"], | |
| ["./imgs/dali5.jpeg"], | |
| ["./imgs/dali6.jpeg"], | |
| ], inputs=img) | |
| with gr.Row(): | |
| clear_btn = gr.ClearButton(value="Clear") | |
| submit_btn = gr.Button("Predict") | |
| output = gr.Label(num_top_classes=2, label="Labels") | |
| submit_btn.click(predict, img, output) | |
| clear_btn.add(img) | |
| demo.launch() |