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Running
on
Zero
Running
on
Zero
File size: 1,270 Bytes
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from typing import *
from transformers import AutoModelForImageSegmentation
import torch
from torchvision import transforms
from PIL import Image
class BiRefNet:
def __init__(self, model_name: str = "ZhengPeng7/BiRefNet"):
self.model = AutoModelForImageSegmentation.from_pretrained(
model_name, trust_remote_code=True
)
self.model.eval()
self.transform_image = transforms.Compose(
[
transforms.Resize((1024, 1024)),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
]
)
def to(self, device: str):
self.model.to(device)
def cuda(self):
self.model.cuda()
def cpu(self):
self.model.cpu()
def __call__(self, image: Image.Image) -> Image.Image:
image_size = image.size
input_images = self.transform_image(image).unsqueeze(0).to("cuda")
# Prediction
with torch.no_grad():
preds = self.model(input_images)[-1].sigmoid().cpu()
pred = preds[0].squeeze()
pred_pil = transforms.ToPILImage()(pred)
mask = pred_pil.resize(image_size)
image.putalpha(mask)
return image
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