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Create app.py
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app.py
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import gradio as gr
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from fastai.vision.all import load_learner
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from fastai import *
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import torch
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import os
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from PIL import Image
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model_path = 'model3-86%.pkl'
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model = load_learner(model_path)
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def result(path):
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pred,_,probability = model.predict(path)
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pred = str(pred)
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pred = pred.upper()
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return {pred: float(probability.max())}
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path = 'test/'
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image_path = []
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for i in os.listdir(path):
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image_path.append(path+i)
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image = gr.inputs.Image(shape =(200,200),image_mode='L',invert_colors=False)
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label = gr.outputs.Label()
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iface = gr.Interface(fn=result, inputs=image, outputs=label, examples = image_path)
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iface.launch(inline=False)
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