pet classify app

app.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:02eb3a56c6194f7249d17c6ce92fc59c068a0c35e0fc3d552402eae8c7a0f346
+size 114778679

app.py

@@ -0,0 +1,25 @@
+__all__ = ['learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
+
+# Cell
+from fastai.vision.all import *
+import gradio as gr
+import timm
+
+# Cell
+learn = load_learner('model.pkl')
+
+# Cell
+categories = learn.dls.vocab
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+# Cell
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['basset.jpg']
+
+# Cell
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch()