initial commit

.gitignore

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+flagged/
+*.pkl
+*.png
+*.jpg
+*.mp4
+*.mkv
+gradio_cached_examples/

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+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))}
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil", image_mode="RGB", height=512, width=512, sources=["upload"]),
+    outputs=gr.Label(num_top_classes=3),
+    title="Image Classifier",
+    description="Upload an image; the app resizes to 512×512 inside predict()."
+).launch(share=True)

requirements.txt

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+fastai