Cat or Dog app with Gradio

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -1,8 +1,28 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: Cat or Dog.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
+
+# %% Cat or Dog.ipynb 2
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+def is_cat(x): return x[0].isupper()
+
+# %% Cat or Dog.ipynb 4
+learn = load_learner('model.pkl')
+
+# %% Cat or Dog.ipynb 6
+categories = ('Dog', 'Cat')
+
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+# %% Cat or Dog.ipynb 8
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['dog.jpg', 'dog2.jpg', 'cat.jpg', 'cat2.jpg']
 
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False, server_name="0.0.0.0", server_port=3000)

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6210fe38f7b43a584e093dd8c4a4fd8a06bad7a44feb423a4c0abab88f5b9f2a
+size 47061355