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app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+import pathlib
+
+temp = pathlib.PosixPath
+pathlib.PosixPath = pathlib.WindowsPath
+
+learn = load_learner('eksport1.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 = 'Potato Disease Classifier'
+description = 'A potato disease classifier trained on random images from internet with fastai. Created as a demo for Gradio and HuggingFace Spaces.'
+examples = ['early_blight.JPG', 'healthy.JPG', 'late_blight.JPG']
+
+gr.Interface(fn = predict,
+    inputs = 'image',
+    outputs = 'label',
+    title = title,
+    description = description,
+    examples = examples).launch()

eksport1.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:69af0dd3fe72b9a1406e02b9c42c4b19a075fd574cf8d1b67f710e5156589f15
+size 47019827