40 lines
1.0 KiB
Python
40 lines
1.0 KiB
Python
import numpy as np
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def create_briarmbg2_session():
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from transformers import AutoModelForImageSegmentation
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birefnet = AutoModelForImageSegmentation.from_pretrained(
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"briaai/RMBG-2.0", trust_remote_code=True
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)
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return birefnet
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def briarmbg2_process(bgr_np_image, session, only_mask=False):
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from torchvision import transforms
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from PIL import Image
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transform_image = transforms.Compose(
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[
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transforms.Resize((1024, 1024)),
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transforms.ToTensor(),
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transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
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]
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)
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image = Image.fromarray(bgr_np_image)
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image_size = image.size
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input_images = transform_image(image).unsqueeze(0)
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# Prediction
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preds = session(input_images)[-1].sigmoid().cpu()
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pred = preds[0].squeeze()
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pred_pil = transforms.ToPILImage()(pred)
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mask = pred_pil.resize(image_size)
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if only_mask:
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return np.array(mask)
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image.putalpha(mask)
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return np.array(image)
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