deploy to huggingface spaces

app.py

@@ -0,0 +1,21 @@
+from fastai.vision.all import *
+import gradio as gr
+
+pat = r'^(.*)_\d+.jpg'
+
+labels = learn.dls.vocab
+
+def classify_image(img):
+    img = PILImage.create(img)
+    pred, idx, probs = learn.predict(img)
+    return {labels[i] : float(probs[i]) for i in range(len(labels))}
+    #return dict(zip(labels, map(float,probs)))
+
+image = gr.inputs.Image(shape=(512,512))
+label = gr.outputs.Label(num_top_classes=3)
+examples = ['Basset-Hound-standing-in-the-garden.jpg']
+title = "Cat&Dog Breed Classifier"
+description = "A cat and dog breed classifier trained on the Oxford Pets dataset."
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples, title=title, description = description, enable_queue=True)
+intf.launch(inline=False, share=True)

model_new.plk

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d9518c002caa2103748471b9345189aec0287b6e11f94857d7c6d457235256a5
+size 47145695

requirements.txt

@@ -0,0 +1 @@
+fastai