main_push

app.py

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+import gradio as gr
+import skimage
+from fastai.vision.all import *
+
+learn = load_learner('resnet50_m0.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 = "Satellite Image Deforestation Classifier"
+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."
+article="<p style='text-align: center'><a href='https://github.com/LucianCotolan/sas-image-deforestification' target='_blank'>Project Github Repository</a></p>"
+examples = ['fragment_1.jpg']
+
+interpretation='default'
+enable_queue=True
+
+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()

resnet50_m0.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:844993df2c0c26fcf4a38b9b1b70f8f75685e432763ec2503b32fdcd4cb6ffe2
+size 103470446