Cleanup existing directories, fixes
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parent
740070ea9c
commit
7d5c29b674
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@ -4,6 +4,7 @@ __pycache__
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/venv
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/venv
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/tmp
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/tmp
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/model.ckpt
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/model.ckpt
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/models/**/*
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/models/*.ckpt
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/models/*.ckpt
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/GFPGANv1.3.pth
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/GFPGANv1.3.pth
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/gfpgan/weights/*.pth
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/gfpgan/weights/*.pth
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@ -5,14 +5,13 @@ import traceback
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import cv2
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import cv2
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import torch
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import torch
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import modules.face_restoration
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import modules.shared
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from modules import shared, devices, modelloader
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from modules import shared, devices, modelloader
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from modules.paths import script_path, models_path
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from modules.paths import script_path, models_path
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import modules.shared
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import modules.face_restoration
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from importlib import reload
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# codeformer people made a choice to include modified basicsr library to their project, which makes
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# codeformer people made a choice to include modified basicsr library to their project which makes
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# it utterly impossible to use it alongside other libraries that also use basicsr, like GFPGAN.
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# it utterly impossible to use it alongside with other libraries that also use basicsr, like GFPGAN.
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# I am making a choice to include some files from codeformer to work around this issue.
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# I am making a choice to include some files from codeformer to work around this issue.
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model_dir = "Codeformer"
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model_dir = "Codeformer"
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model_path = os.path.join(models_path, model_dir)
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model_path = os.path.join(models_path, model_dir)
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@ -31,11 +30,6 @@ def setup_model(dirname):
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if path is None:
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if path is None:
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return
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return
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# both GFPGAN and CodeFormer use bascisr, one has it installed from pip the other uses its own
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#stored_sys_path = sys.path
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#sys.path = [path] + sys.path
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try:
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try:
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from torchvision.transforms.functional import normalize
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from torchvision.transforms.functional import normalize
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from modules.codeformer.codeformer_arch import CodeFormer
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from modules.codeformer.codeformer_arch import CodeFormer
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@ -67,7 +61,6 @@ def setup_model(dirname):
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print("Unable to load codeformer model.")
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print("Unable to load codeformer model.")
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return None, None
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return None, None
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net = net_class(dim_embd=512, codebook_size=1024, n_head=8, n_layers=9, connect_list=['32', '64', '128', '256']).to(devices.device_codeformer)
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net = net_class(dim_embd=512, codebook_size=1024, n_head=8, n_layers=9, connect_list=['32', '64', '128', '256']).to(devices.device_codeformer)
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ckpt_path = load_file_from_url(url=pretrain_model_url, model_dir=os.path.join(path, 'weights/CodeFormer'), progress=True)
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checkpoint = torch.load(ckpt_path)['params_ema']
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checkpoint = torch.load(ckpt_path)['params_ema']
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net.load_state_dict(checkpoint)
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net.load_state_dict(checkpoint)
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net.eval()
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net.eval()
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@ -18,7 +18,7 @@ from modules.shared import opts
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model_dir = "ESRGAN"
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model_dir = "ESRGAN"
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model_path = os.path.join(models_path, model_dir)
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model_path = os.path.join(models_path, model_dir)
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model_url = "https://drive.google.com/u/0/uc?id=1TPrz5QKd8DHHt1k8SRtm6tMiPjz_Qene&export=download"
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model_url = "https://drive.google.com/u/0/uc?id=1TPrz5QKd8DHHt1k8SRtm6tMiPjz_Qene&export=download"
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model_name = "ESRGAN_x4.pth"
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model_name = "ESRGAN_x4"
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def load_model(path: str, name: str):
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def load_model(path: str, name: str):
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@ -27,7 +27,7 @@ def load_model(path: str, name: str):
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global model_dir
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global model_dir
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global model_name
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global model_name
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if "http" in path:
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if "http" in path:
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filename = load_file_from_url(url=model_url, model_dir=model_path, file_name=model_name, progress=True)
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filename = load_file_from_url(url=model_url, model_dir=model_path, file_name="%s.pth" % model_name, progress=True)
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else:
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else:
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filename = path
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filename = path
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if not os.path.exists(filename) or filename is None:
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if not os.path.exists(filename) or filename is None:
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@ -19,7 +19,7 @@ have_ldsr = False
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LDSR_obj = None
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LDSR_obj = None
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class UpscalerLDSR(modules.images.Upscaler):
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class UpscalerLDSR(images.Upscaler):
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def __init__(self, steps):
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def __init__(self, steps):
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self.steps = steps
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self.steps = steps
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self.name = "LDSR"
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self.name = "LDSR"
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@ -1,8 +1,11 @@
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import os
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import os
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import shutil
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from urllib.parse import urlparse
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from urllib.parse import urlparse
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from basicsr.utils.download_util import load_file_from_url
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from basicsr.utils.download_util import load_file_from_url
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from modules.paths import script_path, models_path
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def load_models(model_path: str, model_url: str = None, command_path: str = None, dl_name: str = None, existing=None,
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def load_models(model_path: str, model_url: str = None, command_path: str = None, dl_name: str = None, existing=None,
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ext_filter=None) -> list:
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ext_filter=None) -> list:
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@ -63,3 +66,38 @@ def friendly_name(file: str):
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model_name, extension = os.path.splitext(file)
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model_name, extension = os.path.splitext(file)
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model_name = model_name.replace("_", " ").title()
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model_name = model_name.replace("_", " ").title()
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return model_name
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return model_name
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def cleanup_models():
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root_path = script_path
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src_path = os.path.join(root_path, "ESRGAN")
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dest_path = os.path.join(models_path, "ESRGAN")
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move_files(src_path, dest_path)
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src_path = os.path.join(root_path, "gfpgan")
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dest_path = os.path.join(models_path, "GFPGAN")
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move_files(src_path, dest_path)
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src_path = os.path.join(root_path, "SwinIR")
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dest_path = os.path.join(models_path, "SwinIR")
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move_files(src_path, dest_path)
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src_path = os.path.join(root_path, "repositories/latent-diffusion/experiments/pretrained_models/")
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dest_path = os.path.join(models_path, "LDSR")
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move_files(src_path, dest_path)
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def move_files(src_path: str, dest_path: str):
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try:
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if not os.path.exists(dest_path):
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os.makedirs(dest_path)
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if os.path.exists(src_path):
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for file in os.listdir(src_path):
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if os.path.isfile(file):
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fullpath = os.path.join(src_path, file)
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print("Moving file: %s to %s" % (fullpath, dest_path))
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try:
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shutil.move(fullpath, dest_path)
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except:
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pass
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print("Removing folder: %s" % src_path)
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shutil.rmtree(src_path, True)
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except:
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pass
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2
webui.py
2
webui.py
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@ -18,9 +18,11 @@ import modules.shared as shared
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import modules.swinir_model as swinir
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import modules.swinir_model as swinir
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import modules.txt2img
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import modules.txt2img
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import modules.ui
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import modules.ui
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from modules import modelloader
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from modules.paths import script_path
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from modules.paths import script_path
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from modules.shared import cmd_opts
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from modules.shared import cmd_opts
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modelloader.cleanup_models()
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codeformer.setup_model(cmd_opts.codeformer_models_path)
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codeformer.setup_model(cmd_opts.codeformer_models_path)
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gfpgan.setup_model(cmd_opts.gfpgan_models_path)
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gfpgan.setup_model(cmd_opts.gfpgan_models_path)
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shared.face_restorers.append(modules.face_restoration.FaceRestoration())
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shared.face_restorers.append(modules.face_restoration.FaceRestoration())
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