121 lines
3.6 KiB
Python
121 lines
3.6 KiB
Python
import os
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os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
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from pathlib import Path
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import pytest
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import torch
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from lama_cleaner.model_manager import ModelManager
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from lama_cleaner.schema import HDStrategy, SDSampler
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from lama_cleaner.tests.test_model import get_config, assert_equal
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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.mkdir(exist_ok=True, parents=True)
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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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@pytest.mark.parametrize("name", ["sd1.5"])
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@pytest.mark.parametrize("sd_device", ["mps"])
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@pytest.mark.parametrize(
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"rect",
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[
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[0, -100, 512, 512 - 128 + 100],
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[0, 128, 512, 512 - 128 + 100],
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[128, 0, 512 - 128 + 100, 512],
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[-100, 0, 512 - 128 + 100, 512],
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[0, 0, 512, 512 + 200],
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[0, 0, 512 + 200, 512],
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[-100, -100, 512 + 200, 512 + 200],
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],
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)
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def test_outpainting(name, sd_device, rect):
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def callback(i, t, latents):
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pass
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if sd_device == "cuda" and not torch.cuda.is_available():
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return
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model = ModelManager(
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name=name,
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device=torch.device(sd_device),
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hf_access_token="",
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sd_run_local=True,
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disable_nsfw=True,
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sd_cpu_textencoder=False,
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callback=callback,
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)
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cfg = get_config(
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HDStrategy.ORIGINAL,
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prompt="a dog sitting on a bench in the park",
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sd_steps=50,
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use_croper=True,
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croper_is_outpainting=True,
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croper_x=rect[0],
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croper_y=rect[1],
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croper_width=rect[2],
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croper_height=rect[3],
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sd_guidance_scale=8.0,
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sd_sampler=SDSampler.dpm_plus_plus,
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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"{name.replace('.', '_')}_outpainting_dpm++_{'_'.join(map(str, rect))}.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("name", ["kandinsky2.2"])
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@pytest.mark.parametrize("sd_device", ["mps"])
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@pytest.mark.parametrize(
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"rect",
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[
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[-128, -128, 768, 768],
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],
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)
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def test_kandinsky_outpainting(name, sd_device, rect):
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def callback(i, t, latents):
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pass
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if sd_device == "cuda" and not torch.cuda.is_available():
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return
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model = ModelManager(
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name="sd1.5",
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device=torch.device(sd_device),
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hf_access_token="",
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sd_run_local=True,
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disable_nsfw=True,
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sd_cpu_textencoder=False,
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callback=callback,
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)
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cfg = get_config(
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HDStrategy.ORIGINAL,
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prompt="a cat",
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negative_prompt="lowres, text, error, cropped, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature",
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sd_steps=50,
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use_croper=True,
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croper_is_outpainting=True,
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croper_x=rect[0],
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croper_y=rect[1],
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croper_width=rect[2],
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croper_height=rect[3],
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sd_guidance_scale=7,
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sd_sampler=SDSampler.dpm_plus_plus,
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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"{name.replace('.', '_')}_outpainting_dpm++_{'_'.join(map(str, rect))}.png",
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img_p=current_dir / "cat.png",
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
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fx=1,
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fy=1,
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)
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