initial commit

app.py

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+import gradio as gr
+from fastbook import *
+from fastai.vision.widgets import *
+import timm
+categories = ['accident' , 'non-accident']
+learn = load_learner('model.pkl')
+def classify(img):
+  category,index,probs = learn.predict(img)
+  return (dict(zip(categories , map(float,probs))))
+img = gr.inputs.Image(shape=(224))
+label = gr.outputs.Label()
+example = ['accident.jpg' , 'non-accident.jpg']
+iface = gr.Interface(fn=classify, inputs="image", outputs="label" , examples= example)
+iface.launch()

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2d3804ac77daa0fb339dd721d58cd8e7fbe7d4e710cecbfe8697cac8d01c79b9
+size 114640698

requirements.txt

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+gradio
+-Uqq fastbook
+timm