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This commit is contained in:
Qing
2023-12-19 13:16:30 +08:00
parent f27fc51e34
commit 141936a937
18 changed files with 479 additions and 358 deletions
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5
lama_cleaner/tests/test_controlnet.py
View File

@@ -39,7 +39,6 @@ def test_runway_sd_1_5(
sd_controlnet=True,
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=False,
disable_nsfw=disable_nsfw,
sd_cpu_textencoder=cpu_textencoder,
sd_controlnet_method=sd_controlnet_method,
@@ -88,11 +87,9 @@ def test_local_file_path(sd_device, sampler):
sd_controlnet=True,
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=False,
disable_nsfw=True,
sd_cpu_textencoder=False,
cpu_offload=True,
sd_local_model_path="/Users/cwq/data/models/sd-v1-5-inpainting.ckpt",
sd_controlnet_method="control_v11p_sd15_canny",
)
cfg = get_config(
@@ -128,7 +125,6 @@ def test_local_file_path_controlnet_native_inpainting(sd_device, sampler):
sd_controlnet=True,
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=False,
disable_nsfw=True,
sd_cpu_textencoder=False,
cpu_offload=True,
@@ -170,7 +166,6 @@ def test_controlnet_switch(sd_device, sampler):
sd_controlnet=True,
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=False,
disable_nsfw=True,
sd_cpu_textencoder=False,
cpu_offload=True,

54
lama_cleaner/tests/test_instruct_pix2pix.py
View File

@@ -8,23 +8,30 @@ 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 = current_dir / "result"
save_dir.mkdir(exist_ok=True, parents=True)
device = 'cuda' if torch.cuda.is_available() else 'mps'
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="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)
sd_steps = 50 if device == "cuda" else 20
model = ModelManager(
name=model_name,
device=torch.device(device),
hf_access_token="",
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}"
@@ -34,22 +41,27 @@ def test_instruct_pix2pix(disable_nsfw, cpu_offload):
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
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="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_steps = 50 if device == "cuda" else 20
model = ModelManager(
name=model_name,
device=torch.device(device),
hf_access_token="",
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"

2
lama_cleaner/tests/test_model_md5.py
View File

@@ -20,8 +20,6 @@ def test_load_model():
hf_access_token="",
disable_nsfw=False,
sd_cpu_textencoder=True,
sd_run_local=True,
local_files_only=True,
cpu_offload=True,
enable_xformers=False,
)

80
lama_cleaner/tests/test_model_switch.py
View File

@@ -0,0 +1,80 @@
import logging
import os
from lama_cleaner.schema import Config
os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
import torch
from lama_cleaner.model_manager import ModelManager
def test_model_switch():
model = ModelManager(
name="runwayml/stable-diffusion-inpainting",
sd_controlnet=True,
sd_controlnet_method="lllyasviel/control_v11p_sd15_canny",
device=torch.device("mps"),
hf_access_token="",
disable_nsfw=True,
sd_cpu_textencoder=True,
cpu_offload=False,
enable_xformers=False,
callback=None,
)
model.switch("lama")
def test_controlnet_switch_onoff(caplog):
name = "runwayml/stable-diffusion-inpainting"
model = ModelManager(
name=name,
sd_controlnet=True,
sd_controlnet_method="lllyasviel/control_v11p_sd15_canny",
device=torch.device("mps"),
hf_access_token="",
disable_nsfw=True,
sd_cpu_textencoder=True,
cpu_offload=False,
enable_xformers=False,
callback=None,
)
model.switch_controlnet_method(
Config(
name=name,
controlnet_enabled=False,
)
)
assert "Disable controlnet" in caplog.text
def test_controlnet_switch_method(caplog):
name = "runwayml/stable-diffusion-inpainting"
old_method = "lllyasviel/control_v11p_sd15_canny"
new_method = "lllyasviel/control_v11p_sd15_openpose"
model = ModelManager(
name=name,
sd_controlnet=True,
sd_controlnet_method=old_method,
device=torch.device("mps"),
hf_access_token="",
disable_nsfw=True,
sd_cpu_textencoder=True,
cpu_offload=False,
enable_xformers=False,
callback=None,
)
model.switch_controlnet_method(
Config(
name=name,
controlnet_enabled=True,
controlnet_method=new_method,
)
)
assert f"Switch Controlnet method from {old_method} to {new_method}" in caplog.text

34
lama_cleaner/tests/test_outpainting.py
View File

@@ -17,7 +17,7 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
device = torch.device(device)
@pytest.mark.parametrize("name", ["sd1.5"])
@pytest.mark.parametrize("name", ["runwayml/stable-diffusion-inpainting"])
@pytest.mark.parametrize("sd_device", ["mps"])
@pytest.mark.parametrize(
"rect",
@@ -42,7 +42,6 @@ def test_outpainting(name, sd_device, rect):
name=name,
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=True,
disable_nsfw=True,
sd_cpu_textencoder=False,
callback=callback,
@@ -51,12 +50,11 @@ def test_outpainting(name, sd_device, rect):
HDStrategy.ORIGINAL,
prompt="a dog sitting on a bench in the park",
sd_steps=50,
use_croper=True,
croper_is_outpainting=True,
croper_x=rect[0],
croper_y=rect[1],
croper_width=rect[2],
croper_height=rect[3],
use_extender=True,
extender_x=rect[0],
extender_y=rect[1],
extender_width=rect[2],
extender_height=rect[3],
sd_guidance_scale=8.0,
sd_sampler=SDSampler.dpm_plus_plus,
)
@@ -64,13 +62,13 @@ def test_outpainting(name, sd_device, rect):
assert_equal(
model,
cfg,
f"{name.replace('.', '_')}_outpainting_dpm++_{'_'.join(map(str, rect))}.png",
f"{name.replace('/', '--')}_outpainting_dpm++_{'_'.join(map(str, rect))}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("name", ["kandinsky2.2"])
@pytest.mark.parametrize("name", ["kandinsky-community/kandinsky-2-2-decoder-inpaint"])
@pytest.mark.parametrize("sd_device", ["mps"])
@pytest.mark.parametrize(
"rect",
@@ -86,10 +84,9 @@ def test_kandinsky_outpainting(name, sd_device, rect):
return
model = ModelManager(
name="sd1.5",
name=name,
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=True,
disable_nsfw=True,
sd_cpu_textencoder=False,
callback=callback,
@@ -99,12 +96,11 @@ def test_kandinsky_outpainting(name, sd_device, rect):
prompt="a cat",
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",
sd_steps=50,
use_croper=True,
croper_is_outpainting=True,
croper_x=rect[0],
croper_y=rect[1],
croper_width=rect[2],
croper_height=rect[3],
use_extender=True,
extender_x=rect[0],
extender_y=rect[1],
extender_width=rect[2],
extender_height=rect[3],
sd_guidance_scale=7,
sd_sampler=SDSampler.dpm_plus_plus,
)
@@ -112,7 +108,7 @@ def test_kandinsky_outpainting(name, sd_device, rect):
assert_equal(
model,
cfg,
f"{name.replace('.', '_')}_outpainting_dpm++_{'_'.join(map(str, rect))}.png",
f"{name.replace('/', '--')}_outpainting_dpm++_{'_'.join(map(str, rect))}.png",
img_p=current_dir / "cat.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fx=1,

77
lama_cleaner/tests/test_paint_by_example.py
View File

@@ -10,15 +10,19 @@ from lama_cleaner.schema import HDStrategy
from lama_cleaner.tests.test_model import get_config, get_data
current_dir = Path(__file__).parent.absolute().resolve()
save_dir = current_dir / 'result'
save_dir = current_dir / "result"
save_dir.mkdir(exist_ok=True, parents=True)
device = 'cuda' if torch.cuda.is_available() else 'cpu'
device = "cuda" if torch.cuda.is_available() else "mps"
device = torch.device(device)
model_name = "Fantasy-Studio/Paint-by-Example"
def assert_equal(
model, config, gt_name,
fx: float = 1, fy: float = 1,
model,
config,
gt_name,
fx: float = 1,
fy: float = 1,
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
example_p=current_dir / "bunny.jpeg",
@@ -27,7 +31,9 @@ def assert_equal(
example_image = cv2.imread(str(example_p))
example_image = cv2.cvtColor(example_image, cv2.COLOR_BGRA2RGB)
example_image = cv2.resize(example_image, None, fx=fx, fy=fy, interpolation=cv2.INTER_AREA)
example_image = cv2.resize(
example_image, None, fx=fx, fy=fy, interpolation=cv2.INTER_AREA
)
print(f"Input image shape: {img.shape}, example_image: {example_image.shape}")
config.paint_by_example_example_image = Image.fromarray(example_image)
@@ -35,14 +41,13 @@ def assert_equal(
cv2.imwrite(str(save_dir / gt_name), res)
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_paint_by_example(strategy):
model = ModelManager(name="paint_by_example", device=device, disable_nsfw=True)
cfg = get_config(strategy, paint_by_example_steps=30)
def test_paint_by_example():
model = ModelManager(name=model_name, device=device, disable_nsfw=True)
cfg = get_config(HDStrategy.ORIGINAL, sd_steps=30)
assert_equal(
model,
cfg,
f"paint_by_example_{strategy.capitalize()}.png",
f"paint_by_example.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fy=0.9,
@@ -50,57 +55,31 @@ def test_paint_by_example(strategy):
)
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_paint_by_example_disable_nsfw(strategy):
model = ModelManager(name="paint_by_example", device=device, disable_nsfw=False)
cfg = get_config(strategy, paint_by_example_steps=30)
def test_paint_by_example_cpu_offload():
model = ModelManager(
name=model_name, device=device, cpu_offload=True, disable_nsfw=False
)
cfg = get_config(HDStrategy.ORIGINAL, sd_steps=30)
assert_equal(
model,
cfg,
f"paint_by_example_{strategy.capitalize()}_disable_nsfw.png",
f"paint_by_example_cpu_offload.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_paint_by_example_sd_scale(strategy):
model = ModelManager(name="paint_by_example", device=device, disable_nsfw=True)
cfg = get_config(strategy, paint_by_example_steps=30, sd_scale=0.85)
def test_paint_by_example_cpu_offload_cpu_device():
model = ModelManager(
name=model_name, device=torch.device("cpu"), cpu_offload=True, disable_nsfw=True
)
cfg = get_config(HDStrategy.ORIGINAL, sd_steps=1)
assert_equal(
model,
cfg,
f"paint_by_example_{strategy.capitalize()}_sdscale.png",
f"paint_by_example_cpu_offload_cpu_device.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fy=0.9,
fx=1.3
)
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_paint_by_example_cpu_offload(strategy):
model = ModelManager(name="paint_by_example", device=device, cpu_offload=True, disable_nsfw=False)
cfg = get_config(strategy, paint_by_example_steps=30, sd_scale=0.85)
assert_equal(
model,
cfg,
f"paint_by_example_{strategy.capitalize()}_cpu_offload.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
def test_paint_by_example_cpu_offload_cpu_device(strategy):
model = ModelManager(name="paint_by_example", device=torch.device('cpu'), cpu_offload=True, disable_nsfw=True)
cfg = get_config(strategy, paint_by_example_steps=1, sd_scale=0.85)
assert_equal(
model,
cfg,
f"paint_by_example_{strategy.capitalize()}_cpu_offload_cpu_device.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fy=0.9,
fx=1.3
fx=1.3,
)

246
lama_cleaner/tests/test_sd_model.py
View File

@@ -7,7 +7,7 @@ import pytest
import torch
from lama_cleaner.model_manager import ModelManager
from lama_cleaner.schema import HDStrategy, SDSampler
from lama_cleaner.schema import HDStrategy, SDSampler, FREEUConfig
from lama_cleaner.tests.test_model import get_config, assert_equal
current_dir = Path(__file__).parent.absolute().resolve()
@@ -16,178 +16,127 @@ save_dir.mkdir(exist_ok=True, parents=True)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
@pytest.mark.parametrize("cpu_textencoder", [True, False])
@pytest.mark.parametrize("disable_nsfw", [True, False])
def test_runway_sd_1_5_ddim(
sd_device, strategy, sampler, cpu_textencoder, disable_nsfw
):
def callback(i, t, latents):
pass
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 50 if sd_device == "cuda" else 1
model = ModelManager(
name="sd1.5",
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=True,
disable_nsfw=disable_nsfw,
sd_cpu_textencoder=cpu_textencoder,
callback=callback,
)
cfg = get_config(strategy, prompt="a fox sitting on a bench", sd_steps=sd_steps)
cfg.sd_sampler = sampler
name = f"device_{sd_device}_{sampler}_cpu_textencoder_{cpu_textencoder}_disnsfw_{disable_nsfw}"
assert_equal(
model,
cfg,
f"runway_sd_{strategy.capitalize()}_{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("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize(
"sampler", [SDSampler.pndm, SDSampler.k_lms, SDSampler.k_euler, SDSampler.k_euler_a]
"sampler",
[
SDSampler.ddim,
SDSampler.pndm,
SDSampler.k_lms,
SDSampler.k_euler,
SDSampler.k_euler_a,
SDSampler.lcm,
],
)
@pytest.mark.parametrize("cpu_textencoder", [False])
@pytest.mark.parametrize("disable_nsfw", [True])
def test_runway_sd_1_5(sd_device, strategy, sampler, cpu_textencoder, disable_nsfw):
def callback(i, t, latents):
print(f"sd_step_{i}")
def test_runway_sd_1_5_all_samplers(
sd_device,
sampler,
):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 50 if sd_device == "cuda" else 1
sd_steps = 30
model = ModelManager(
name="sd1.5",
name="runwayml/stable-diffusion-inpainting",
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=True,
disable_nsfw=disable_nsfw,
sd_cpu_textencoder=cpu_textencoder,
callback=callback,
disable_nsfw=True,
sd_cpu_textencoder=False,
)
cfg = get_config(
HDStrategy.ORIGINAL, prompt="a fox sitting on a bench", sd_steps=sd_steps
)
cfg = get_config(strategy, prompt="a fox sitting on a bench", sd_steps=sd_steps)
cfg.sd_sampler = sampler
name = f"device_{sd_device}_{sampler}_cpu_textencoder_{cpu_textencoder}_disnsfw_{disable_nsfw}"
name = f"device_{sd_device}_{sampler}"
assert_equal(
model,
cfg,
f"runway_sd_{strategy.capitalize()}_{name}.png",
f"runway_sd_{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("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
@pytest.mark.parametrize("sd_prevent_unmasked_area", [False, True])
def test_runway_sd_1_5_negative_prompt(
sd_device, strategy, sampler, sd_prevent_unmasked_area
):
def callback(i, t, latents):
pass
@pytest.mark.parametrize("sampler", [SDSampler.lcm])
def test_runway_sd_lcm_lora(sd_device, strategy, sampler):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 50 if sd_device == "cuda" else 20
sd_steps = 5
model = ModelManager(
name="sd1.5",
name="runwayml/stable-diffusion-inpainting",
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=True,
disable_nsfw=False,
disable_nsfw=True,
sd_cpu_textencoder=False,
callback=callback,
)
cfg = get_config(
strategy,
prompt="face of a fox, sitting on a bench",
sd_steps=sd_steps,
prompt="Face of a fox, high resolution, sitting on a park bench",
negative_prompt="orange, yellow, small",
sd_sampler=sampler,
sd_match_histograms=True,
sd_prevent_unmasked_area=sd_prevent_unmasked_area,
)
name = f"{sampler}_negative_prompt"
assert_equal(
model,
cfg,
f"runway_sd_{strategy.capitalize()}_{name}_prevent_unmasked_area_{sd_prevent_unmasked_area}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fx=1,
)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.k_euler_a])
@pytest.mark.parametrize("cpu_textencoder", [False])
@pytest.mark.parametrize("disable_nsfw", [False])
def test_runway_sd_1_5_sd_scale(
sd_device, strategy, sampler, cpu_textencoder, disable_nsfw
):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 50 if sd_device == "cuda" else 20
model = ModelManager(
name="sd1.5",
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=True,
disable_nsfw=disable_nsfw,
sd_cpu_textencoder=cpu_textencoder,
)
cfg = get_config(
strategy, prompt="a fox sitting on a bench", sd_steps=sd_steps, sd_scale=0.85
sd_guidance_scale=2,
sd_lcm_lora=True,
)
cfg.sd_sampler = sampler
name = f"device_{sd_device}_{sampler}_cpu_textencoder_{cpu_textencoder}_disnsfw_{disable_nsfw}"
assert_equal(
model,
cfg,
f"runway_sd_{strategy.capitalize()}_{name}_sdscale.png",
f"runway_sd_1_5_lcm_lora.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fx=1.3,
)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.k_euler_a])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
def test_runway_sd_freeu(sd_device, strategy, sampler):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 30
model = ModelManager(
name="runwayml/stable-diffusion-inpainting",
device=torch.device(sd_device),
hf_access_token="",
disable_nsfw=True,
sd_cpu_textencoder=False,
)
cfg = get_config(
strategy,
prompt="face of a fox, sitting on a bench",
sd_steps=sd_steps,
sd_guidance_scale=7.5,
sd_freeu=True,
sd_freeu_config=FREEUConfig(),
)
cfg.sd_sampler = sampler
assert_equal(
model,
cfg,
f"runway_sd_1_5_freeu.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
def test_runway_sd_sd_strength(sd_device, strategy, sampler):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 50 if sd_device == "cuda" else 20
sd_steps = 30
model = ModelManager(
name="sd1.5",
name="runwayml/stable-diffusion-inpainting",
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=True,
disable_nsfw=True,
sd_cpu_textencoder=False,
)
@@ -205,6 +154,33 @@ def test_runway_sd_sd_strength(sd_device, strategy, sampler):
)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
def test_runway_norm_sd_model(sd_device, strategy, sampler):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 30
model = ModelManager(
name="runwayml/stable-diffusion-v1-5",
device=torch.device(sd_device),
hf_access_token="",
disable_nsfw=True,
sd_cpu_textencoder=False,
)
cfg = get_config(strategy, prompt="face of a fox, sitting on a bench", sd_steps=sd_steps)
cfg.sd_sampler = sampler
assert_equal(
model,
cfg,
f"runway_{sd_device}_norm_sd_model.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("sd_device", ["cuda"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.k_euler_a])
@@ -212,19 +188,16 @@ def test_runway_sd_1_5_cpu_offload(sd_device, strategy, sampler):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 50 if sd_device == "cuda" else 20
sd_steps = 30
model = ModelManager(
name="sd1.5",
name="runwayml/stable-diffusion-inpainting",
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=True,
disable_nsfw=True,
sd_cpu_textencoder=False,
cpu_offload=True,
)
cfg = get_config(
strategy, prompt="a fox sitting on a bench", sd_steps=sd_steps, sd_scale=0.85
)
cfg = get_config(strategy, prompt="a fox sitting on a bench", sd_steps=sd_steps)
cfg.sd_sampler = sampler
name = f"device_{sd_device}_{sampler}"
@@ -239,28 +212,27 @@ def test_runway_sd_1_5_cpu_offload(sd_device, strategy, sampler):
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("sampler", [SDSampler.uni_pc])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
@pytest.mark.parametrize(
"local_model_path",
"name",
[
"/Users/cwq/data/models/sd-v1-5-inpainting.ckpt",
"/Users/cwq/data/models/sd-v1-5-inpainting.safetensors",
"sd-v1-5-inpainting.ckpt",
"sd-v1-5-inpainting.safetensors",
"v1-5-pruned-emaonly.safetensors",
],
)
def test_local_file_path(sd_device, sampler, local_model_path):
def test_local_file_path(sd_device, sampler, name):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 1 if sd_device == "cpu" else 30
sd_steps = 30
model = ModelManager(
name="sd1.5",
name=name,
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=True,
disable_nsfw=True,
sd_cpu_textencoder=False,
cpu_offload=True,
sd_local_model_path=local_model_path,
cpu_offload=False,
)
cfg = get_config(
HDStrategy.ORIGINAL,
@@ -269,7 +241,7 @@ def test_local_file_path(sd_device, sampler, local_model_path):
)
cfg.sd_sampler = sampler
name = f"device_{sd_device}_{sampler}_{Path(local_model_path).stem}"
name = f"device_{sd_device}_{sampler}_{name}"
assert_equal(
model,

101
lama_cleaner/tests/test_sdxl.py
View File

@@ -7,7 +7,7 @@ import pytest
import torch
from lama_cleaner.model_manager import ModelManager
from lama_cleaner.schema import HDStrategy, SDSampler
from lama_cleaner.schema import HDStrategy, SDSampler, FREEUConfig
from lama_cleaner.tests.test_model import get_config, assert_equal
current_dir = Path(__file__).parent.absolute().resolve()
@@ -15,12 +15,10 @@ save_dir = current_dir / "result"
save_dir.mkdir(exist_ok=True, parents=True)
@pytest.mark.parametrize("sd_device", ["mps"])
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
@pytest.mark.parametrize("cpu_textencoder", [False])
@pytest.mark.parametrize("disable_nsfw", [True])
def test_sdxl(sd_device, strategy, sampler, cpu_textencoder, disable_nsfw):
def test_sdxl(sd_device, strategy, sampler):
def callback(i, t, latents):
pass
@@ -29,24 +27,23 @@ def test_sdxl(sd_device, strategy, sampler, cpu_textencoder, disable_nsfw):
sd_steps = 20
model = ModelManager(
name="sdxl",
name="diffusers/stable-diffusion-xl-1.0-inpainting-0.1",
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=False,
disable_nsfw=disable_nsfw,
sd_cpu_textencoder=cpu_textencoder,
disable_nsfw=True,
sd_cpu_textencoder=False,
callback=callback,
)
cfg = get_config(
strategy,
prompt="a fox sitting on a bench",
prompt="face of a fox, sitting on a bench",
sd_steps=sd_steps,
sd_strength=0.99,
sd_strength=1.0,
sd_guidance_scale=7.0,
)
cfg.sd_sampler = sampler
name = f"device_{sd_device}_{sampler}_cpu_textencoder_{cpu_textencoder}_disnsfw_{disable_nsfw}"
name = f"device_{sd_device}_{sampler}"
assert_equal(
model,
@@ -59,6 +56,67 @@ def test_sdxl(sd_device, strategy, sampler, cpu_textencoder, disable_nsfw):
)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
def test_sdxl_lcm_lora_and_freeu(sd_device, strategy, sampler):
def callback(i, t, latents):
pass
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 5
model = ModelManager(
name="diffusers/stable-diffusion-xl-1.0-inpainting-0.1",
device=torch.device(sd_device),
hf_access_token="",
disable_nsfw=True,
sd_cpu_textencoder=False,
callback=callback,
)
cfg = get_config(
strategy,
prompt="face of a fox, sitting on a bench",
sd_steps=sd_steps,
sd_strength=1.0,
sd_guidance_scale=2.0,
sd_lcm_lora=True,
)
cfg.sd_sampler = sampler
name = f"device_{sd_device}_{sampler}"
assert_equal(
model,
cfg,
f"sdxl_{name}_lcm_lora.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fx=2,
fy=2,
)
cfg = get_config(
strategy,
prompt="face of a fox, sitting on a bench",
sd_steps=sd_steps,
sd_guidance_scale=7.5,
sd_freeu=True,
sd_freeu_config=FREEUConfig(),
)
assert_equal(
model,
cfg,
f"sdxl_{name}_freeu.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
fx=2,
fy=2,
)
@pytest.mark.parametrize("sd_device", ["mps"])
@pytest.mark.parametrize(
"rect",
@@ -67,33 +125,26 @@ def test_sdxl(sd_device, strategy, sampler, cpu_textencoder, disable_nsfw):
],
)
def test_sdxl_outpainting(sd_device, rect):
def callback(i, t, latents):
pass
if sd_device == "cuda" and not torch.cuda.is_available():
return
model = ModelManager(
name="sdxl",
name="diffusers/stable-diffusion-xl-1.0-inpainting-0.1",
device=torch.device(sd_device),
hf_access_token="",
sd_run_local=True,
disable_nsfw=True,
sd_cpu_textencoder=False,
callback=callback,
)
cfg = get_config(
HDStrategy.ORIGINAL,
prompt="a dog sitting on a bench in the park",
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",
sd_steps=20,
use_croper=True,
croper_is_outpainting=True,
croper_x=rect[0],
croper_y=rect[1],
croper_width=rect[2],
croper_height=rect[3],
use_extender=True,
extender_x=rect[0],
extender_y=rect[1],
extender_width=rect[2],
extender_height=rect[3],
sd_strength=1.0,
sd_guidance_scale=8.0,
sd_sampler=SDSampler.ddim,