Added everything

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+learn = load_learner('model_v5_87_percent_final.pkl')
+
+categories = ('pencil', 'pen', 'eraser', 'calculator', 'binder clip', 'marker', 'glue', 'tape', 'crayon', 'paper')
+
+def classify_image(img):
+  pred, idx, probs = learn.predict(img)
+  return dict(zip(categories, map(float, probs)))
+
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['pencil.jpg', 'pen.jpg', 'eraser.jpg', 'calculator.jpg', 'binder_clip.jpg', 'marker.jpg', 'glue.jpg', 'tape.jpg', 'crayon.jpg', 'paper.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch()

model_v5_87_percent_final.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8fac109d5f2d7dce4022b8e0bf63c5cf1502453fb15a5559337991f32f8f714d
+size 102936709

requirements.txt

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+fastai
+gradio