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from pathlib import Path |
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import cv2 |
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import pytest |
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import torch |
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from PIL import Image |
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from lama_cleaner.model_manager import ModelManager |
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from lama_cleaner.schema import HDStrategy |
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from lama_cleaner.tests.test_model import get_config, get_data |
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current_dir = Path(__file__).parent.absolute().resolve() |
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save_dir = current_dir / 'result' |
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save_dir.mkdir(exist_ok=True, parents=True) |
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device = 'cuda' if torch.cuda.is_available() else 'cpu' |
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device = torch.device(device) |
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def assert_equal( |
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model, config, gt_name, |
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fx: float = 1, fy: float = 1, |
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img_p=current_dir / "overture-creations-5sI6fQgYIuo.png", |
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png", |
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example_p=current_dir / "bunny.jpeg", |
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): |
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img, mask = get_data(fx=fx, fy=fy, img_p=img_p, mask_p=mask_p) |
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example_image = cv2.imread(str(example_p)) |
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example_image = cv2.cvtColor(example_image, cv2.COLOR_BGRA2RGB) |
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example_image = cv2.resize(example_image, None, fx=fx, fy=fy, interpolation=cv2.INTER_AREA) |
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print(f"Input image shape: {img.shape}, example_image: {example_image.shape}") |
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config.paint_by_example_example_image = Image.fromarray(example_image) |
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res = model(img, mask, config) |
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cv2.imwrite(str(save_dir / gt_name), res) |
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@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL]) |
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def test_paint_by_example(strategy): |
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model = ModelManager(name="paint_by_example", device=device, disable_nsfw=True) |
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cfg = get_config(strategy, paint_by_example_steps=30) |
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assert_equal( |
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model, |
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cfg, |
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f"paint_by_example_{strategy.capitalize()}.png", |
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img_p=current_dir / "overture-creations-5sI6fQgYIuo.png", |
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png", |
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fy=0.9, |
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fx=1.3, |
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) |
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@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL]) |
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def test_paint_by_example_disable_nsfw(strategy): |
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model = ModelManager(name="paint_by_example", device=device, disable_nsfw=False) |
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cfg = get_config(strategy, paint_by_example_steps=30) |
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assert_equal( |
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model, |
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cfg, |
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f"paint_by_example_{strategy.capitalize()}_disable_nsfw.png", |
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img_p=current_dir / "overture-creations-5sI6fQgYIuo.png", |
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png", |
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) |
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@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL]) |
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def test_paint_by_example_sd_scale(strategy): |
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model = ModelManager(name="paint_by_example", device=device, disable_nsfw=True) |
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cfg = get_config(strategy, paint_by_example_steps=30, sd_scale=0.85) |
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assert_equal( |
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model, |
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cfg, |
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f"paint_by_example_{strategy.capitalize()}_sdscale.png", |
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img_p=current_dir / "overture-creations-5sI6fQgYIuo.png", |
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png", |
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fy=0.9, |
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fx=1.3 |
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) |
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@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL]) |
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def test_paint_by_example_cpu_offload(strategy): |
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model = ModelManager(name="paint_by_example", device=device, cpu_offload=True, disable_nsfw=False) |
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cfg = get_config(strategy, paint_by_example_steps=30, sd_scale=0.85) |
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assert_equal( |
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model, |
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cfg, |
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f"paint_by_example_{strategy.capitalize()}_cpu_offload.png", |
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img_p=current_dir / "overture-creations-5sI6fQgYIuo.png", |
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png", |
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) |
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@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL]) |
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def test_paint_by_example_cpu_offload_cpu_device(strategy): |
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model = ModelManager(name="paint_by_example", device=torch.device('cpu'), cpu_offload=True, disable_nsfw=True) |
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cfg = get_config(strategy, paint_by_example_steps=1, sd_scale=0.85) |
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assert_equal( |
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model, |
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cfg, |
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f"paint_by_example_{strategy.capitalize()}_cpu_offload_cpu_device.png", |
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img_p=current_dir / "overture-creations-5sI6fQgYIuo.png", |
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png", |
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fy=0.9, |
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fx=1.3 |
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) |
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