shirtfit model

app.py

@@ -1,8 +1,27 @@
-import gradio as gr
-
-def greet(name):
-    return "Hello " + name + "!!"
-
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
-					
+import gradio as gr
+from fastai.vision.all import *
+
+learn = load_learner('model.pkl')
+
+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))}
+
+title = "Shirt Fit Classifier"
+description = "A Loose vs. Fitted shirt classifier"
+article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
+examples = ['demo1.jpg', 'demo2.jpg', 'demo3.jpg', 'demo4.jpg']
+interpretation='default'
+enable_queue=True
+
+gr.Interface(fn=predict,
+             inputs=gr.inputs.Image(shape=(300, 300)),
+             outputs=gr.outputs.Label(num_top_classes=3),
+             title=title,
+             description=description,
+             article=article,
+             examples=examples,
+             interpretation=interpretation,
+             enable_queue=enable_queue).launch()