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app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('modelt.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 = "Human Body Parts Classifier"
+description = "Human Body parts Classifier created with custom scraped dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+article="https://visual-synthesizer.ai,    https://github.com/Visual-Synthesizer"
+examples = ['images/face.jpg', 'images/feet.jpg', 'images/pose.jpg', 'images/hand.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,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch(share=True)

modelt.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3cb7010a3669ef123c42b6143ac95afbde1f688824a001273f09a25028e37825
+size 46975393

requirments.txt

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+fastai
+scikit-image
+gradio