mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
something is not quite right; when providing -G1 option on one prompt, and then omitting it on the next, I see a "images do not match" error from GFPGAN
This commit is contained in:
Lincoln Stein
@ -6,8 +6,10 @@ import shlex
|
||||
import os
|
||||
import sys
|
||||
import copy
|
||||
import warnings
|
||||
import ldm.dream.readline
|
||||
from ldm.dream.pngwriter import PngWriter,PromptFormatter
|
||||
|
||||
debugging = False
|
||||
|
||||
def main():
|
||||
@ -68,6 +70,29 @@ def main():
|
||||
|
||||
# preload the model
|
||||
t2i.load_model()
|
||||
|
||||
# load GFPGAN if requested
|
||||
if opt.use_gfpgan:
|
||||
print("\n* --gfpgan was specified, loading gfpgan...")
|
||||
with warnings.catch_warnings():
|
||||
warnings.filterwarnings("ignore", category=DeprecationWarning)
|
||||
|
||||
try:
|
||||
model_path = os.path.join(opt.gfpgan_dir, opt.gfpgan_model_path)
|
||||
if not os.path.isfile(model_path):
|
||||
raise Exception("GFPGAN model not found at path "+model_path)
|
||||
|
||||
sys.path.append(os.path.abspath(opt.gfpgan_dir))
|
||||
from gfpgan import GFPGANer
|
||||
|
||||
bg_upsampler = load_gfpgan_bg_upsampler(opt.gfpgan_bg_upsampler, opt.gfpgan_bg_tile)
|
||||
|
||||
t2i.gfpgan = GFPGANer(model_path=model_path, upscale=opt.gfpgan_upscale, arch='clean', channel_multiplier=2, bg_upsampler=bg_upsampler)
|
||||
except Exception:
|
||||
import traceback
|
||||
print("Error loading GFPGAN:", file=sys.stderr)
|
||||
print(traceback.format_exc(), file=sys.stderr)
|
||||
|
||||
print("\n* Initialization done! Awaiting your command (-h for help, 'q' to quit, 'cd' to change output dir, 'pwd' to print output dir)...")
|
||||
|
||||
log_path = os.path.join(opt.outdir,'dream_log.txt')
|
||||
@ -183,6 +208,32 @@ def main_loop(t2i,outdir,parser,log,infile):
|
||||
|
||||
print("goodbye!")
|
||||
|
||||
def load_gfpgan_bg_upsampler(bg_upsampler, bg_tile=400):
|
||||
import torch
|
||||
|
||||
if bg_upsampler == 'realesrgan':
|
||||
if not torch.cuda.is_available(): # CPU
|
||||
import warnings
|
||||
warnings.warn('The unoptimized RealESRGAN is slow on CPU. We do not use it. '
|
||||
'If you really want to use it, please modify the corresponding codes.')
|
||||
bg_upsampler = None
|
||||
else:
|
||||
from basicsr.archs.rrdbnet_arch import RRDBNet
|
||||
from realesrgan import RealESRGANer
|
||||
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
|
||||
bg_upsampler = RealESRGANer(
|
||||
scale=2,
|
||||
model_path='https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth',
|
||||
model=model,
|
||||
tile=bg_tile,
|
||||
tile_pad=10,
|
||||
pre_pad=0,
|
||||
half=True) # need to set False in CPU mode
|
||||
else:
|
||||
bg_upsampler = None
|
||||
|
||||
return bg_upsampler
|
||||
|
||||
# variant generation is going to be superseded by a generalized
|
||||
# "prompt-morph" functionality
|
||||
# def generate_variants(t2i,outdir,opt,previous_gens):
|
||||
@ -261,6 +312,31 @@ def create_argv_parser():
|
||||
type=str,
|
||||
default="cuda",
|
||||
help="device to run stable diffusion on. defaults to cuda `torch.cuda.current_device()` if avalible")
|
||||
# GFPGAN related args
|
||||
parser.add_argument('--gfpgan',
|
||||
dest='use_gfpgan',
|
||||
action='store_true',
|
||||
help="load gfpgan for use in the dreambot. Note: Enabling GFPGAN will require more GPU memory")
|
||||
parser.add_argument("--gfpgan_upscale",
|
||||
type=int,
|
||||
default=2,
|
||||
help="The final upsampling scale of the image. Default: 2. Only used if --gfpgan is specified")
|
||||
parser.add_argument("--gfpgan_bg_upsampler",
|
||||
type=str,
|
||||
default='realesrgan',
|
||||
help="Background upsampler. Default: None. Options: realesrgan, none. Only used if --gfpgan is specified")
|
||||
parser.add_argument("--gfpgan_bg_tile",
|
||||
type=int,
|
||||
default=400,
|
||||
help="Tile size for background sampler, 0 for no tile during testing. Default: 400. Only used if --gfpgan is specified")
|
||||
parser.add_argument("--gfpgan_model_path",
|
||||
type=str,
|
||||
default='experiments/pretrained_models/GFPGANv1.3.pth',
|
||||
help="indicates the path to the GFPGAN model, relative to --gfpgan_dir. Only used if --gfpgan is specified")
|
||||
parser.add_argument("--gfpgan_dir",
|
||||
type=str,
|
||||
default='../GFPGAN',
|
||||
help="indicates the directory containing the GFPGAN code. Only used if --gfpgan is specified")
|
||||
return parser
|
||||
|
||||
|
||||
@ -278,6 +354,7 @@ def create_cmd_parser():
|
||||
parser.add_argument('-i','--individual',action='store_true',help="generate individual files (default)")
|
||||
parser.add_argument('-I','--init_img',type=str,help="path to input image for img2img mode (supersedes width and height)")
|
||||
parser.add_argument('-f','--strength',default=0.75,type=float,help="strength for noising/unnoising. 0.0 preserves image exactly, 1.0 replaces it completely")
|
||||
parser.add_argument('-G','--gfpgan_strength', default=0.5, type=float, help="The strength at which to apply the GFPGAN model to the result, in order to improve faces.")
|
||||
# variants is going to be superseded by a generalized "prompt-morph" function
|
||||
# parser.add_argument('-v','--variants',type=int,help="in img2img mode, the first generated image will get passed back to img2img to generate the requested number of variants")
|
||||
parser.add_argument('-x','--skip_normalize',action='store_true',help="skip subprompt weight normalization")
|
||||
|
||||
@ -5,6 +5,8 @@
|
||||
# two machines must share a common .cache directory.
|
||||
import sys
|
||||
import transformers
|
||||
import os
|
||||
import warnings
|
||||
|
||||
transformers.logging.set_verbosity_error()
|
||||
|
||||
@ -15,15 +17,15 @@ tokenizer = BertTokenizerFast.from_pretrained("bert-base-uncased")
|
||||
print("...success")
|
||||
|
||||
# this will download requirements for Kornia
|
||||
print("preloading Kornia requirements (ignore the warnings)...")
|
||||
import kornia
|
||||
print("preloading Kornia requirements (ignore the deprecation warnings)...")
|
||||
with warnings.catch_warnings():
|
||||
warnings.filterwarnings("ignore", category=DeprecationWarning)
|
||||
import kornia
|
||||
print("...success")
|
||||
|
||||
# doesn't work - probably wrong logger
|
||||
# logging.getLogger('transformers.tokenization_utils').setLevel(logging.ERROR)
|
||||
version='openai/clip-vit-large-patch14'
|
||||
|
||||
print('preloading CLIP model (Ignore the warnings)...')
|
||||
print('preloading CLIP model (Ignore the deprecation warnings)...')
|
||||
sys.stdout.flush()
|
||||
import clip
|
||||
from transformers import CLIPTokenizer, CLIPTextModel
|
||||
@ -31,4 +33,28 @@ tokenizer =CLIPTokenizer.from_pretrained(version)
|
||||
transformer=CLIPTextModel.from_pretrained(version)
|
||||
print('\n\n...success')
|
||||
|
||||
# In the event that the user has installed GFPGAN and also elected to use
|
||||
# RealESRGAN, this will attempt to download the model needed by RealESRGANer
|
||||
gfpgan = False
|
||||
try:
|
||||
from realesrgan import RealESRGANer
|
||||
gfpgan = True
|
||||
except ModuleNotFoundError:
|
||||
pass
|
||||
|
||||
if gfpgan:
|
||||
print("Loading models from RealESRGAN and facexlib")
|
||||
try:
|
||||
from basicsr.archs.rrdbnet_arch import RRDBNet
|
||||
from facexlib.utils.face_restoration_helper import FaceRestoreHelper
|
||||
RealESRGANer(scale=2,
|
||||
model_path='https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth',
|
||||
model=RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2))
|
||||
FaceRestoreHelper(1,det_model='retinaface_resnet50')
|
||||
print("...success")
|
||||
except Exception:
|
||||
import traceback
|
||||
print("Error loading GFPGAN:")
|
||||
print(traceback.format_exc())
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user