File size: 4,957 Bytes
cbbdd92 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 |
import pytest
import torch
from iopaint.model_manager import ModelManager
from iopaint.schema import HDStrategy, LDMSampler
from iopaint.tests.utils import assert_equal, get_config, current_dir, check_device
@pytest.mark.parametrize("device", ["cuda", "mps", "cpu"])
@pytest.mark.parametrize(
"strategy", [HDStrategy.ORIGINAL, HDStrategy.RESIZE, HDStrategy.CROP]
)
def test_lama(device, strategy):
check_device(device)
model = ModelManager(name="lama", device=device)
assert_equal(
model,
get_config(strategy=strategy),
f"lama_{strategy[0].upper() + strategy[1:]}_result.png",
)
fx = 1.3
assert_equal(
model,
get_config(strategy=strategy),
f"lama_{strategy[0].upper() + strategy[1:]}_fx_{fx}_result.png",
fx=1.3,
)
@pytest.mark.parametrize("device", ["cuda", "cpu"])
@pytest.mark.parametrize(
"strategy", [HDStrategy.ORIGINAL, HDStrategy.RESIZE, HDStrategy.CROP]
)
@pytest.mark.parametrize("ldm_sampler", [LDMSampler.ddim, LDMSampler.plms])
def test_ldm(device, strategy, ldm_sampler):
check_device(device)
model = ModelManager(name="ldm", device=device)
cfg = get_config(strategy=strategy, ldm_sampler=ldm_sampler)
assert_equal(
model, cfg, f"ldm_{strategy[0].upper() + strategy[1:]}_{ldm_sampler}_result.png"
)
fx = 1.3
assert_equal(
model,
cfg,
f"ldm_{strategy[0].upper() + strategy[1:]}_{ldm_sampler}_fx_{fx}_result.png",
fx=fx,
)
@pytest.mark.parametrize("device", ["cuda", "cpu"])
@pytest.mark.parametrize(
"strategy", [HDStrategy.ORIGINAL, HDStrategy.RESIZE, HDStrategy.CROP]
)
@pytest.mark.parametrize("zits_wireframe", [False, True])
def test_zits(device, strategy, zits_wireframe):
check_device(device)
model = ModelManager(name="zits", device=device)
cfg = get_config(strategy=strategy, zits_wireframe=zits_wireframe)
assert_equal(
model,
cfg,
f"zits_{strategy[0].upper() + strategy[1:]}_wireframe_{zits_wireframe}_result.png",
)
fx = 1.3
assert_equal(
model,
cfg,
f"zits_{strategy.capitalize()}_wireframe_{zits_wireframe}_fx_{fx}_result.png",
fx=fx,
)
@pytest.mark.parametrize("device", ["cuda", "cpu"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("no_half", [True, False])
def test_mat(device, strategy, no_half):
check_device(device)
model = ModelManager(name="mat", device=device, no_half=no_half)
cfg = get_config(strategy=strategy)
assert_equal(
model,
cfg,
f"mat_{strategy.capitalize()}_result.png",
)
@pytest.mark.parametrize("device", ["cuda", "cpu"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_fcf(device, strategy):
check_device(device)
model = ModelManager(name="fcf", device=device)
cfg = get_config(strategy=strategy)
assert_equal(model, cfg, f"fcf_{strategy.capitalize()}_result.png", fx=2, fy=2)
assert_equal(model, cfg, f"fcf_{strategy.capitalize()}_result.png", fx=3.8, fy=2)
@pytest.mark.parametrize(
"strategy", [HDStrategy.ORIGINAL, HDStrategy.RESIZE, HDStrategy.CROP]
)
@pytest.mark.parametrize("cv2_flag", ["INPAINT_NS", "INPAINT_TELEA"])
@pytest.mark.parametrize("cv2_radius", [3, 15])
def test_cv2(strategy, cv2_flag, cv2_radius):
model = ModelManager(
name="cv2",
device=torch.device("cpu"),
)
cfg = get_config(strategy=strategy, cv2_flag=cv2_flag, cv2_radius=cv2_radius)
assert_equal(
model,
cfg,
f"cv2_{strategy.capitalize()}_{cv2_flag}_{cv2_radius}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("device", ["cuda", "cpu"])
@pytest.mark.parametrize(
"strategy", [HDStrategy.ORIGINAL, HDStrategy.RESIZE, HDStrategy.CROP]
)
def test_manga(device, strategy):
check_device(device)
model = ModelManager(
name="manga",
device=torch.device(device),
)
cfg = get_config(strategy=strategy)
assert_equal(
model,
cfg,
f"manga_{strategy.capitalize()}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("device", ["cuda", "mps", "cpu"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_mi_gan(device, strategy):
check_device(device)
model = ModelManager(
name="migan",
device=torch.device(device),
)
cfg = get_config(strategy=strategy)
assert_equal(
model,
cfg,
f"migan_device_{device}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fx=1.5,
fy=1.7
)
|