Upload app.py

app.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+
+from fastbook import *
+from fastai.vision.widgets import *
+import os
+
+
+# In[6]:
+
+
+learn = load_learner('export.pkl')
+
+
+# In[7]:
+
+
+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))}
+
+
+# In[18]:
+
+
+
+# In[19]:
+
+
+import gradio as gr
+
+title = "Pet Breed Classifier"
+description = "A pet breed classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+
+gr.Interface(fn=predict,
+             inputs=gr.inputs.Image(shape=(512, 512)),
+             title = "?תפוח או עגבניה",
+             description = "A fruite classifier trained on images from the internet with fastai. Created as a demo for Gradio and HuggingFace Spaces.",
+             interpretation='default',
+             outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)
+
+
+# In[ ]:
+
+
+
+