initial commit

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('resnet.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 = "Skin Disease Classifier"
+description = "A prototype app for classifying common skin diseases, developed with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+
+examples = ['acne.jpg']
+interpretation='default'
+enable_queue=True
+
+gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),
+title=title,description=description, examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()

requirements.txt

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+fastai
+scikit-image

resnet.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d58fa488627a1907ddd62b96abd83eddf66eb4de6689a74b8c520c6d03603300
+size 102914453