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Browse files- app.py +21 -0
- fragment_1.jpg +0 -0
- requirements.txt +0 -0
- resnet50_m0.pkl +3 -0
app.py
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import gradio as gr
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import skimage
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from fastai.vision.all import *
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learn = load_learner('resnet50_m0.pkl')
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labels = learn.dls.vocab
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def predict(img):
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img = PILImage.create(img)
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pred,pred_idx,probs = learn.predict(img)
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return {labels[i]: float(probs[i]) for i in range(len(labels))}
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title = "Satellite Image Deforestation Classifier"
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description = "A deep learning model based on ResNet50 that can classify satellite images into two categories - deforestation (a deforestation event occured in the image) or not_deforestation."
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article="<p style='text-align: center'><a href='https://github.com/LucianCotolan/sas-image-deforestification' target='_blank'>Project Github Repository</a></p>"
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examples = ['fragment_1.jpg']
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interpretation='default'
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enable_queue=True
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gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(224, 224)),outputs=gr.outputs.Label(),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
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fragment_1.jpg
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requirements.txt
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resnet50_m0.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:844993df2c0c26fcf4a38b9b1b70f8f75685e432763ec2503b32fdcd4cb6ffe2
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size 103470446
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