IOPaint/iopaint/tests/test_model.py
2024-01-05 15:19:23 +08:00

161 lines
4.8 KiB
Python

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
)