_ / lama_cleaner /tests /test_instruct_pix2pix.py
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from pathlib import Path
import pytest
import torch
from lama_cleaner.model_manager import ModelManager
from lama_cleaner.tests.test_model import get_config, assert_equal
from lama_cleaner.schema import HDStrategy
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'
@pytest.mark.parametrize("disable_nsfw", [True, False])
@pytest.mark.parametrize("cpu_offload", [False, True])
def test_instruct_pix2pix(disable_nsfw, cpu_offload):
sd_steps = 50 if device == 'cuda' else 1
model = ModelManager(name="instruct_pix2pix",
device=torch.device(device),
hf_access_token="",
sd_run_local=False,
disable_nsfw=disable_nsfw,
sd_cpu_textencoder=False,
cpu_offload=cpu_offload)
cfg = get_config(strategy=HDStrategy.ORIGINAL, prompt='What if it were snowing?', p2p_steps=sd_steps, sd_scale=1.1)
name = f"device_{device}_disnsfw_{disable_nsfw}_cpu_offload_{cpu_offload}"
assert_equal(
model,
cfg,
f"instruct_pix2pix_{name}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fx=1.3
)
@pytest.mark.parametrize("disable_nsfw", [False])
@pytest.mark.parametrize("cpu_offload", [False])
def test_instruct_pix2pix_snow(disable_nsfw, cpu_offload):
sd_steps = 50 if device == 'cuda' else 1
model = ModelManager(name="instruct_pix2pix",
device=torch.device(device),
hf_access_token="",
sd_run_local=False,
disable_nsfw=disable_nsfw,
sd_cpu_textencoder=False,
cpu_offload=cpu_offload)
cfg = get_config(strategy=HDStrategy.ORIGINAL, prompt='What if it were snowing?', p2p_steps=sd_steps)
name = f"snow"
assert_equal(
model,
cfg,
f"instruct_pix2pix_{name}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)