Upload app.py

app.py

@@ -0,0 +1,31 @@
+import gradio as gr
+from fastai.vision.all import *
+
+learn = load_learner("export.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 = "Car or Bike Classifier"
+description = "A Car or Bike or not classifier trained with downloaded data from internet. Created as a demo for Gradio and HuggingFace Spaces."
+
+examples = ["cars.jpg", "bike.jpg"]
+interpretation = "default"
+enable_queue = True
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(512, 512)),
+    outputs=gr.outputs.Label(num_top_classes=2),
+    title=title,
+    description=description,
+    examples=examples,
+    interpretation=interpretation,
+    enable_queue=enable_queue,
+).launch(share=True)