39
iopaint/plugins/briarmbg2.py
Normal file
39
iopaint/plugins/briarmbg2.py
Normal file
@@ -0,0 +1,39 @@
|
||||
import numpy as np
|
||||
|
||||
|
||||
def create_briarmbg2_session():
|
||||
from transformers import AutoModelForImageSegmentation
|
||||
|
||||
birefnet = AutoModelForImageSegmentation.from_pretrained(
|
||||
"briaai/RMBG-2.0", trust_remote_code=True
|
||||
)
|
||||
return birefnet
|
||||
|
||||
|
||||
def briarmbg2_process(bgr_np_image, session, only_mask=False):
|
||||
from torchvision import transforms
|
||||
from PIL import Image
|
||||
|
||||
transform_image = transforms.Compose(
|
||||
[
|
||||
transforms.Resize((1024, 1024)),
|
||||
transforms.ToTensor(),
|
||||
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
|
||||
]
|
||||
)
|
||||
|
||||
image = Image.fromarray(bgr_np_image)
|
||||
image_size = image.size
|
||||
input_images = transform_image(image).unsqueeze(0)
|
||||
|
||||
# Prediction
|
||||
preds = session(input_images)[-1].sigmoid().cpu()
|
||||
pred = preds[0].squeeze()
|
||||
pred_pil = transforms.ToPILImage()(pred)
|
||||
mask = pred_pil.resize(image_size)
|
||||
|
||||
if only_mask:
|
||||
return np.array(mask)
|
||||
|
||||
image.putalpha(mask)
|
||||
return np.array(image)
|
||||
Reference in New Issue
Block a user