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gfpgan: just download the damn model

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AUTOMATIC 2022-09-23 10:26:00 +03:00
parent d6fd71f36f
commit d4205e66fa
2 changed files with 14 additions and 8 deletions
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19
modules/gfpgan_model.py
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@ -1,6 +1,7 @@
import os import os
import sys import sys
import traceback import traceback
from glob import glob
from modules import shared, devices from modules import shared, devices
from modules.shared import cmd_opts from modules.shared import cmd_opts
@ -11,14 +12,20 @@ import modules.face_restoration
def gfpgan_model_path(): def gfpgan_model_path():
from modules.shared import cmd_opts from modules.shared import cmd_opts
filemask = 'GFPGAN*.pth'
if cmd_opts.gfpgan_model is not None:
return cmd_opts.gfpgan_model
places = [script_path, '.', os.path.join(cmd_opts.gfpgan_dir, 'experiments/pretrained_models')] places = [script_path, '.', os.path.join(cmd_opts.gfpgan_dir, 'experiments/pretrained_models')]
files = [cmd_opts.gfpgan_model] + [os.path.join(dirname, cmd_opts.gfpgan_model) for dirname in places]
found = [x for x in files if os.path.exists(x)]
if len(found) == 0: filename = None
raise Exception("GFPGAN model not found in paths: " + ", ".join(files)) for place in places:
filename = next(iter(glob(os.path.join(place, filemask))), None)
if filename is not None:
break
return found[0] return filename
loaded_gfpgan_model = None loaded_gfpgan_model = None
@ -34,7 +41,7 @@ def gfpgan():
if gfpgan_constructor is None: if gfpgan_constructor is None:
return None return None
model = gfpgan_constructor(model_path=gfpgan_model_path(), upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None) model = gfpgan_constructor(model_path=gfpgan_model_path() or 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth', upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None)
model.gfpgan.to(shared.device) model.gfpgan.to(shared.device)
loaded_gfpgan_model = model loaded_gfpgan_model = model

3
modules/shared.py
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@ -2,7 +2,6 @@ import sys
import argparse import argparse
import json import json
import os import os
from glob import glob
import gradio as gr import gradio as gr
import tqdm import tqdm
@ -22,7 +21,7 @@ parser.add_argument("--config", type=str, default=os.path.join(sd_path, "configs
parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; this checkpoint will be added to the list of checkpoints and loaded by default if you don't have a checkpoint selected in settings",) parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; this checkpoint will be added to the list of checkpoints and loaded by default if you don't have a checkpoint selected in settings",)
parser.add_argument("--ckpt-dir", type=str, default=os.path.join(script_path, 'models'), help="path to directory with stable diffusion checkpoints",) parser.add_argument("--ckpt-dir", type=str, default=os.path.join(script_path, 'models'), help="path to directory with stable diffusion checkpoints",)
parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN')) parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN'))
parser.add_argument("--gfpgan-model", type=str, help="GFPGAN model file name", default=next(iter(glob('GFPGAN*.pth')), '')) parser.add_argument("--gfpgan-model", type=str, help="GFPGAN model file name", default=None)
parser.add_argument("--no-half", action='store_true', help="do not switch the model to 16-bit floats") parser.add_argument("--no-half", action='store_true', help="do not switch the model to 16-bit floats")
parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)") parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI") parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")