let's deploy to huggingface spaces

01_tomato.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4652c05a640b4697c6b4ded50f5e2e11e951bde43b3d25f0c1b5da2c007fe25f
+size 201640677

app.py

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+from fastai.vision.all import *
+import skimage
+import gradio as gr
+learn = load_learner('01_tomato.pkl')
+labels = learn_inf.dls.vocab
+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))}
+
+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(share=True)

requirements.txt

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+fastai
+scikit-image