| from fastai.vision.all import * | |
| import skimage | |
| import gradio as gr | |
| learn = load_learner('01_tomato.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))} | |
| title = "Tomato Disease Diagnosis" | |
| gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(256,256)),title = title, outputs=gr.outputs.Label(num_top_classes=1)).launch() | |