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Renamed GFPGAN to extras 

Added Real-ESRGAN to extras tab
This commit is contained in:
AUTOMATIC 2022-08-26 11:16:57 +03:00
parent 055dd10aae
commit 155dd2fc0c
2 changed files with 89 additions and 23 deletions
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15
README.md
View File

@ -62,14 +62,25 @@ Open the URL in browser, and you are good to go.
The script creates a web UI for Stable Diffusion's txt2img and img2img scripts. Following are features added
that are not in original script.
### GFPGAN
### Extras tab
Additional neural network image improvement methods unrelated to stable diffusion.
#### GFPGAN
Lets you improve faces in pictures using the GFPGAN model. There is a checkbox in every tab to use GFPGAN at 100%, and
also a separate tab that just allows you to use GFPGAN on any picture, with a slider that controls how strongthe effect is.
![](images/GFPGAN.png)
#### Real-ESRGAN
Image upscaler. You can choose from multiple models by original author, and specify by how much the image should be upscaled.
Requires `realesrgan` librarty:
```commandline
pip install realesrgan
```
### Sampling method selection
Pick out of three sampling methods for txt2img: DDIM, PLMS, k-diffusion:
Pick out of multiple sampling methods for txt2img:
![](images/sampling.png)

97
webui.py
View File

@ -76,6 +76,38 @@ samplers = [
SamplerData('PLMS', lambda model: PLMSSampler(model)),
]
RealesrganModelInfo = namedtuple("RealesrganModelInfo", ["name", "location", "model", "netscale"])
try:
from basicsr.archs.rrdbnet_arch import RRDBNet
from realesrgan import RealESRGANer
from realesrgan.archs.srvgg_arch import SRVGGNetCompact
realesrgan_models = [
RealesrganModelInfo(
name="Real-ESRGAN 2x plus",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth",
netscale=2, model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
),
RealesrganModelInfo(
name="Real-ESRGAN 4x plus",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth",
netscale=4, model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
),
RealesrganModelInfo(
name="Real-ESRGAN 4x plus anime 6B",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth",
netscale=4, model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
),
]
have_realesrgan = True
except:
print("Error loading Real-ESRGAN:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
realesrgan_models = [RealesrganModelInfo('None', '', 0, None)]
have_realesrgan = False
class Options:
data = None
@ -196,10 +228,6 @@ def torch_gc():
torch.cuda.ipc_collect()
def sanitize_filename_part(text):
return text.replace(' ', '_').translate({ord(x): '' for x in invalid_filename_chars})[:128]
def save_image(image, path, basename, seed, prompt, extension, info=None, short_filename=False):
prompt = sanitize_filename_part(prompt)
@ -208,7 +236,7 @@ def save_image(image, path, basename, seed, prompt, extension, info=None, short_
else:
filename = f"{basename}-{seed}-{prompt[:128]}.{extension}"
if extension == 'png' and opts.enable_pnginfo:
if extension == 'png' and opts.enable_pnginfo and info is not None:
pnginfo = PngImagePlugin.PngInfo()
pnginfo.add_text("parameters", info)
else:
@ -217,6 +245,10 @@ def save_image(image, path, basename, seed, prompt, extension, info=None, short_
image.save(os.path.join(path, filename), quality=opts.jpeg_quality, pnginfo=pnginfo)
def sanitize_filename_part(text):
return text.replace(' ', '_').translate({ord(x): '' for x in invalid_filename_chars})[:128]
def plaintext_to_html(text):
text = "".join([f"<p>{html.escape(x)}</p>\n" for x in text.split('\n')])
return text
@ -835,7 +867,7 @@ def img2img(prompt: str, init_img, ddim_steps: int, use_GFPGAN: bool, prompt_mat
prompt_matrix=prompt_matrix,
use_GFPGAN=use_GFPGAN,
do_not_save_grid=True,
extra_generation_params = {"Denoising Strength": denoising_strength},
extra_generation_params={"Denoising Strength": denoising_strength},
)
if initial_seed is None:
@ -870,7 +902,7 @@ def img2img(prompt: str, init_img, ddim_steps: int, use_GFPGAN: bool, prompt_mat
height=height,
prompt_matrix=prompt_matrix,
use_GFPGAN=use_GFPGAN,
extra_generation_params = {"Denoising Strength": denoising_strength},
extra_generation_params={"Denoising Strength": denoising_strength},
)
del sampler
@ -908,30 +940,56 @@ img2img_interface = gr.Interface(
)
def run_GFPGAN(image, strength):
def run_extras(image, GFPGAN_strength, RealESRGAN_upscaling, RealESRGAN_model_index):
image = image.convert("RGB")
cropped_faces, restored_faces, restored_img = GFPGAN.enhance(np.array(image, dtype=np.uint8), has_aligned=False, only_center_face=False, paste_back=True)
res = Image.fromarray(restored_img)
outpath = opts.outdir or "outputs/extras-samples"
if strength < 1.0:
res = Image.blend(image, res, strength)
if GFPGAN is not None and GFPGAN_strength > 0:
cropped_faces, restored_faces, restored_img = GFPGAN.enhance(np.array(image, dtype=np.uint8), has_aligned=False, only_center_face=False, paste_back=True)
res = Image.fromarray(restored_img)
return res, 0, ''
if GFPGAN_strength < 1.0:
res = Image.blend(image, res, GFPGAN_strength)
image = res
if have_realesrgan and RealESRGAN_upscaling != 1.0:
info = realesrgan_models[RealESRGAN_model_index]
model = info.model()
upsampler = RealESRGANer(
scale=info.netscale,
model_path=info.location,
model=model,
half=True
)
upsampled = upsampler.enhance(np.array(image), outscale=RealESRGAN_upscaling)[0]
image = Image.fromarray(upsampled)
os.makedirs(outpath, exist_ok=True)
base_count = len(os.listdir(outpath))
save_image(image, outpath, f"{base_count:05}", None, '', opts.samples_format, short_filename=True)
return image, 0, ''
gfpgan_interface = gr.Interface(
run_GFPGAN,
extras_interface = gr.Interface(
wrap_gradio_call(run_extras),
inputs=[
gr.Image(label="Source", source="upload", interactive=True, type="pil"),
gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Effect strength", value=100),
gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN strength", value=1, interactive=GFPGAN is not None),
gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Real-ESRGAN upscaling", value=2, interactive=have_realesrgan),
gr.Radio(label='Real-ESRGAN model', choices=[x.name for x in realesrgan_models], value=realesrgan_models[0].name, type="index", interactive=have_realesrgan),
],
outputs=[
gr.Image(label="Result"),
gr.Number(label='Seed', visible=False),
gr.HTML(),
],
description="Fix faces on images",
allow_flagging="never",
)
@ -989,7 +1047,7 @@ settings_interface = gr.Interface(
interfaces = [
(txt2img_interface, "txt2img"),
(img2img_interface, "img2img"),
(gfpgan_interface, "GFPGAN"),
(extras_interface, "Extras"),
(settings_interface, "Settings"),
]
@ -1003,9 +1061,6 @@ text_inversion_embeddings = TextInversionEmbeddings()
if os.path.exists(cmd_opts.embeddings_dir):
text_inversion_embeddings.hijack(model)
if GFPGAN is None:
interfaces = [x for x in interfaces if x[0] != gfpgan_interface]
demo = gr.TabbedInterface(
interface_list=[x[0] for x in interfaces],
tab_names=[x[1] for x in interfaces],