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| import gradio as gr | |
| from skimage.filters import threshold_otsu | |
| from PIL import Image | |
| import numpy as np | |
| def segmentor(image): | |
| img_np=np.array(image.convert("L")) | |
| threshold=threshold_otsu(img_np) | |
| binary=img_np>threshold | |
| return Image.fromarray(binary) | |
| image_input=gr.Image(type="pil",label="Upload your image") | |
| image_output=gr.Image(label="Image processed") | |
| iface=gr.Interface(fn=segmentor,inputs=image_input, | |
| outputs=image_output,title="FindSkinLesion", | |
| description="An app to make a segmentation on image in input to predict if there is a skin lesion or not") | |
| iface.launch(share=True) |