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import gradio as gr
from transformers import pipeline
from PIL import Image, ImageOps
import time
# Initialize Segmentation Pipeline
segformer_b2_clothes_pipe = pipeline("image-segmentation", model="mattmdjaga/segformer_b2_clothes")
def segformer_b2_clothes(img):
result = segformer_b2_clothes_pipe(img)
mask = result[0]['mask'].convert('L')
mask = ImageOps.invert(mask)
img.putalpha(mask)
return img
def remove_background(img):
start = time.time()
segformer_b2_clothes_result = segformer_b2_clothes(img)
end = time.time()
segformer_b2_clothes_text = "[mattmdjaga/segformer_b2_clothes](https://huggingface.co/mattmdjaga/segformer_b2_clothes) in " + str(end-start) + " seconds"
return segformer_b2_clothes_text, segformer_b2_clothes_result
iface = gr.Interface(fn=remove_background,
inputs=gr.Image(type='pil'),
outputs=[gr.Markdown(),
gr.Image(label='segformer_b2_clothes', type='pil')])
iface.launch() |