init

app.py

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+from fastai.vision.all import *
+import gradio as gr
+import os
+
+os.makedirs("uploads", exist_ok=True)
+
+def classify_image(img):
+    learn = load_learner("model.pkl")
+    _, _, probs = learn.predict(img)
+    # Return a dictionary of label->confidence pairs
+    return dict(zip(learn.dls.vocab, map(float, probs)))
+
+# Get a list of example images if they exist
+examples = []
+for filename in ["exa1.jpg", "exa2.jpg"]:
+    if os.path.exists(filename):
+        examples.append(filename)
+
+# Create and launch the Gradio interface
+interface = gr.Interface(
+    fn=classify_image,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(),
+    examples=examples,
+    title="German Bread Classification"
+).launch(inline=True)
+
+if __name__ == "__main__":
+    interface.launch(inline=False)

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c005529b3bd79bd441f0ef025a93d88390edbd399b950c74b715ddc9e7d3509b
+size 47009534

requirements.txt

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+fastai
+gradio