Spaces:
Runtime error
Runtime error
File size: 3,985 Bytes
252e766 |
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 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 |
from pathlib import Path
import cv2
import pytest
import torch
from PIL import Image
from lama_cleaner.model_manager import ModelManager
from lama_cleaner.schema import HDStrategy
from lama_cleaner.tests.test_model import get_config, get_data
current_dir = Path(__file__).parent.absolute().resolve()
save_dir = current_dir / 'result'
save_dir.mkdir(exist_ok=True, parents=True)
device = 'cuda' if torch.cuda.is_available() else 'cpu'
device = torch.device(device)
def assert_equal(
model, config, gt_name,
fx: float = 1, fy: float = 1,
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
example_p=current_dir / "bunny.jpeg",
):
img, mask = get_data(fx=fx, fy=fy, img_p=img_p, mask_p=mask_p)
example_image = cv2.imread(str(example_p))
example_image = cv2.cvtColor(example_image, cv2.COLOR_BGRA2RGB)
example_image = cv2.resize(example_image, None, fx=fx, fy=fy, interpolation=cv2.INTER_AREA)
print(f"Input image shape: {img.shape}, example_image: {example_image.shape}")
config.paint_by_example_example_image = Image.fromarray(example_image)
res = model(img, mask, config)
cv2.imwrite(str(save_dir / gt_name), res)
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_paint_by_example(strategy):
model = ModelManager(name="paint_by_example", device=device, disable_nsfw=True)
cfg = get_config(strategy, paint_by_example_steps=30)
assert_equal(
model,
cfg,
f"paint_by_example_{strategy.capitalize()}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fy=0.9,
fx=1.3,
)
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_paint_by_example_disable_nsfw(strategy):
model = ModelManager(name="paint_by_example", device=device, disable_nsfw=False)
cfg = get_config(strategy, paint_by_example_steps=30)
assert_equal(
model,
cfg,
f"paint_by_example_{strategy.capitalize()}_disable_nsfw.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_paint_by_example_sd_scale(strategy):
model = ModelManager(name="paint_by_example", device=device, disable_nsfw=True)
cfg = get_config(strategy, paint_by_example_steps=30, sd_scale=0.85)
assert_equal(
model,
cfg,
f"paint_by_example_{strategy.capitalize()}_sdscale.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fy=0.9,
fx=1.3
)
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_paint_by_example_cpu_offload(strategy):
model = ModelManager(name="paint_by_example", device=device, cpu_offload=True, disable_nsfw=False)
cfg = get_config(strategy, paint_by_example_steps=30, sd_scale=0.85)
assert_equal(
model,
cfg,
f"paint_by_example_{strategy.capitalize()}_cpu_offload.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_paint_by_example_cpu_offload_cpu_device(strategy):
model = ModelManager(name="paint_by_example", device=torch.device('cpu'), cpu_offload=True, disable_nsfw=True)
cfg = get_config(strategy, paint_by_example_steps=1, sd_scale=0.85)
assert_equal(
model,
cfg,
f"paint_by_example_{strategy.capitalize()}_cpu_offload_cpu_device.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fy=0.9,
fx=1.3
)
|