Add luxury bag classifier interface minus model

app.py

@@ -0,0 +1,35 @@
+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner("luxury_bag_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 = "Luxury Bag Classifier"
+description = (
+    "A luxury bag classifier trained on photos of a few brands. Created with resnet18 architecture."
+)
+article = "<p style='text-align: center'><a href='https://www.kaggle.com/code/sellde/fastai-chapter-2' target='_blank'>Model Source</a></p>"
+examples = ["gucci.jpg", "chanel.jpg", "vuitton.jpg"]
+interpretation = "default"
+enable_queue = True
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(512, 512)),
+    outputs=gr.outputs.Label(),
+    title=title,
+    description=description,
+    article=article,
+    examples=examples,
+    interpretation=interpretation,
+    enable_queue=enable_queue,
+).launch()

requirements.txt

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+fastai
+scikit-image