Create app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+from fastai.vision.all import PILImage
+
+learn = load_learner('export.pkl')
+
+labels = learn.dls.vocab
+
+def predict(img):
+ img = PILImage.create(img)
+ img = img.resize((512, 512))
+ pred,pred_idx,probs = learn.predict(img)
+ return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+examples = ['image.jpg']
+
+#gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
+gr.Interface(fn=predict,inputs=gr.components.Image(),outputs=gr.components.Label(num_top_classes=3),examples=examples,).launch()