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 "mps" model_name = "timbrooks/instruct-pix2pix" @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 20 model = ModelManager( name=model_name, device=torch.device(device), 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 20 model = ModelManager( name=model_name, device=torch.device(device), 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", )