Trial 1

ShoeClassifier.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c7a7377c297adc7a6f6c291f549687bcfe55118b54f76b0a90cfbf33e9b67195
+size 102885663

app.py

@@ -1,9 +1,25 @@
 import gradio as gr
+from fastai.vision.all import *
 
 
-def greet(name):
-    return "Hello " + name + "!!"
+def shoe(x):
+    return x[0].isupper()
 
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+learn = load_learner('ShoeClassifier.pkl')
+categories = ("everyday running shoes", "running racing shoes",
+              "stability running shoes", "tempo running shoes")
+
+
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+
+image = gr.inputs.Image(shape=(256, 256))
+label = gr.outputs.Label()
+examples = ["racers.jpeg", "stability.jpeg", "dailytrainer.jpeg", "tempo.jpeg"]
+
+intf = gr.Interface(fn=classify_image, inputs=image,
+                    outputs=label, examples=examples)
+intf.launch(inline=False)