wip mat float16
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@@ -9,13 +9,18 @@ from lama_cleaner.model_manager import ModelManager
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from lama_cleaner.schema import Config, HDStrategy, LDMSampler, SDSampler
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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 = 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 = "cuda" if torch.cuda.is_available() else "cpu"
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device = torch.device(device)
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def get_data(fx: float = 1, fy: float = 1.0, img_p=current_dir / "image.png", mask_p=current_dir / "mask.png"):
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def get_data(
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fx: float = 1,
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fy: float = 1.0,
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img_p=current_dir / "image.png",
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mask_p=current_dir / "mask.png",
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):
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img = cv2.imread(str(img_p))
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img = cv2.cvtColor(img, cv2.COLOR_BGRA2RGB)
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mask = cv2.imread(str(mask_p), cv2.IMREAD_GRAYSCALE)
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@@ -37,10 +42,15 @@ def get_config(strategy, **kwargs):
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return Config(**data)
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def assert_equal(model, config, gt_name,
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fx: float = 1, fy: float = 1,
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img_p=current_dir / "image.png",
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mask_p=current_dir / "mask.png"):
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def assert_equal(
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model,
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config,
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gt_name,
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fx: float = 1,
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fy: float = 1,
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img_p=current_dir / "image.png",
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mask_p=current_dir / "mask.png",
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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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print(f"Input image shape: {img.shape}")
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res = model(img, mask, config)
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@@ -59,139 +69,13 @@ def assert_equal(model, config, gt_name,
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# assert np.array_equal(res, gt)
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@pytest.mark.parametrize(
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"strategy", [HDStrategy.ORIGINAL, HDStrategy.RESIZE, HDStrategy.CROP]
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)
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def test_lama(strategy):
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model = ModelManager(name="lama", device=device)
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assert_equal(
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model,
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get_config(strategy),
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f"lama_{strategy[0].upper() + strategy[1:]}_result.png",
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)
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fx = 1.3
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assert_equal(
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model,
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get_config(strategy),
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f"lama_{strategy[0].upper() + strategy[1:]}_fx_{fx}_result.png",
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fx=1.3,
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)
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@pytest.mark.parametrize(
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"strategy", [HDStrategy.ORIGINAL, HDStrategy.RESIZE, HDStrategy.CROP]
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)
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@pytest.mark.parametrize("ldm_sampler", [LDMSampler.ddim, LDMSampler.plms])
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def test_ldm(strategy, ldm_sampler):
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model = ModelManager(name="ldm", device=device)
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cfg = get_config(strategy, ldm_sampler=ldm_sampler)
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assert_equal(
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model, cfg, f"ldm_{strategy[0].upper() + strategy[1:]}_{ldm_sampler}_result.png"
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)
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fx = 1.3
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assert_equal(
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model,
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cfg,
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f"ldm_{strategy[0].upper() + strategy[1:]}_{ldm_sampler}_fx_{fx}_result.png",
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fx=fx,
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)
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@pytest.mark.parametrize(
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"strategy", [HDStrategy.ORIGINAL, HDStrategy.RESIZE, HDStrategy.CROP]
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)
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@pytest.mark.parametrize("zits_wireframe", [False, True])
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def test_zits(strategy, zits_wireframe):
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model = ModelManager(name="zits", device=device)
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cfg = get_config(strategy, zits_wireframe=zits_wireframe)
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# os.environ['ZITS_DEBUG_LINE_PATH'] = str(current_dir / 'zits_debug_line.jpg')
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# os.environ['ZITS_DEBUG_EDGE_PATH'] = str(current_dir / 'zits_debug_edge.jpg')
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assert_equal(
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model,
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cfg,
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f"zits_{strategy[0].upper() + strategy[1:]}_wireframe_{zits_wireframe}_result.png",
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)
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fx = 1.3
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assert_equal(
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model,
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cfg,
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f"zits_{strategy.capitalize()}_wireframe_{zits_wireframe}_fx_{fx}_result.png",
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fx=fx,
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)
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@pytest.mark.parametrize(
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"strategy", [HDStrategy.ORIGINAL]
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)
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@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
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def test_mat(strategy):
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model = ModelManager(name="mat", device=device)
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cfg = get_config(strategy)
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assert_equal(
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model,
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cfg,
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f"mat_{strategy.capitalize()}_result.png",
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)
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for _ in range(10):
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assert_equal(
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model, cfg, f"mat_{strategy.capitalize()}_result.png",
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)
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@pytest.mark.parametrize(
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"strategy", [HDStrategy.ORIGINAL]
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)
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def test_fcf(strategy):
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model = ModelManager(name="fcf", device=device)
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cfg = get_config(strategy)
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assert_equal(
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model,
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cfg,
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f"fcf_{strategy.capitalize()}_result.png",
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fx=2,
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fy=2
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)
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assert_equal(
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model,
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cfg,
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f"fcf_{strategy.capitalize()}_result.png",
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fx=3.8,
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fy=2
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)
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@pytest.mark.parametrize(
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"strategy", [HDStrategy.ORIGINAL, HDStrategy.RESIZE, HDStrategy.CROP]
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)
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@pytest.mark.parametrize("cv2_flag", ['INPAINT_NS', 'INPAINT_TELEA'])
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@pytest.mark.parametrize("cv2_radius", [3, 15])
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def test_cv2(strategy, cv2_flag, cv2_radius):
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model = ModelManager(
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name="cv2",
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device=torch.device(device),
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)
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cfg = get_config(strategy, cv2_flag=cv2_flag, cv2_radius=cv2_radius)
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assert_equal(
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model,
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cfg,
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f"sd_{strategy.capitalize()}_{cv2_flag}_{cv2_radius}.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, HDStrategy.RESIZE, HDStrategy.CROP])
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def test_manga(strategy):
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model = ModelManager(
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name="manga",
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device=torch.device(device),
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)
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cfg = get_config(strategy)
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assert_equal(
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model,
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cfg,
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f"sd_{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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)
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