Create app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+from huggingface_hub import from_pretrained_fastai
+
+import pathlib
+plt = platform.system()
+if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
+
+learn = from_pretrained_fastai(repo_id = "KathrynMercer/BoneClassifier")
+
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i].title(): float(probs[i]) for i in range(len(labels))}
+
+gr.Interface(fn=predict, 
+             inputs='image', 
+             outputs='label',
+             title = 'Human vs Nonhuman Long Bone Classifier',
+             description = ''A computer vision classifier to determine if an image of a bone is more likely human or non-human origin. Use at your own risk.',
+             examples = [[r'test images\test human femur - Swedish History Museum.jpg'],
+             interpretation='default').launch(share=True)