| import pathlib | |
| temp = pathlib.PosixPath | |
| pathlib.WindowsPath = pathlib.PosixPath | |
| learn_inf = load_learner('export.pkl') | |
| import gradio as gr | |
| labels = ['fluorescent', 'not_fluorescent'] | |
| def predict(img): | |
| img = PILImage.create(img) | |
| pred,pred_idx,probs = learn_inf.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| fluo_id_web = gr.Interface(fn = "predict", | |
| inputs = "image", | |
| outputs= "label", | |
| interpretation = "default", | |
| title="Fluorescence identification").launch(share=True) | |
| fluo_id_web.launch() |