-
Notifications
You must be signed in to change notification settings - Fork 3
/
inference.py
70 lines (60 loc) · 1.81 KB
/
inference.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
import argparse
import numpy as np
import torch
from mmengine.registry import init_default_scope
from mmengine.runner import set_random_seed
from PIL import Image
from torchvision.utils import save_image
from mmagic.apis import init_model
parser = argparse.ArgumentParser(description='Run inference with SGDiff model')
parser.add_argument(
'--ckpt',
type=str,
default='sgdiff.pth',
help='Path to the model checkpoint file')
parser.add_argument(
'--prompt',
type=str,
default='sleeveless jumpsuit',
help='Attribute level description of cloth')
parser.add_argument(
'--img_path',
type=str,
default='examples/starry_night.jpg',
help='Path to the input image file')
parser.add_argument(
'--output_path',
type=str,
default='results.png',
help='Path to the output image file')
args = parser.parse_args()
init_default_scope('mmagic')
set_random_seed(100)
def load_img(img_path: str):
img = Image.open(img_path).resize((256, 256))
img = np.array(img) / 255.
img = (img - 0.5) / 0.5
img = torch.tensor(img).permute(2, 0, 1).unsqueeze(0).cuda()
return img.to(torch.float32)
if __name__ == '__main__':
config = 'configs/sgdiff/sgdiff-ddim-sg_fashion-64x64.py'
model = init_model(config, args.ckpt).cuda().eval()
prompt = args.prompt
img = load_img(args.img_path)
modality_order_cfg = {'txt': 1.5, 'style': 2}
with torch.no_grad():
conditions = {
'style': img,
'prompt': prompt,
}
data = model.infer_mm(
modality_order_cfg=modality_order_cfg,
show_progress=True,
**conditions)
samples = data['samples']
save_image(
samples,
args.output_path,
nrow=4,
normalize=True,
value_range=(-1, 1))