test

app.py

@@ -1,7 +1,21 @@
+__all__ = ['is_cat', 'learn', 'classify_image', 'categoreies', 'image', 'label', 'examples', 'intf']
+
+from fastai.vision import *
 import gradio as gr
 
-def greet(name):
-  return "Hello " + name + "!"
+def is_cat(x): return x[0].obj == 'cat'
+
+learn = load_learner('model.pkl')
+
+categories = ('Dog', 'Cat')
+
+def classify_image(img):
+    pred_class, pred_idx, outputs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+    # return {'label': str(pred_class), 'confidence': float(outputs[pred_idx])}
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label(num_top_classes=2)
+examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
+intf = gr.Interface(classify_image, image, label, capture_session=True, examples=examples)
+intf.launch()

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1fc32c3ba5114f2ec20768522beea7f7459d15b4bdaf7c3c710fc3f524176de2
+size 47063121

requirements.txt

@@ -0,0 +1,2 @@
+gradio
+fastai