Merge branch 'AUTOMATIC1111:dev' into dev (9d8af4bd) · Commits · github_fork / Stable Diffusion Webui

.github/workflows/on_pull_request.yaml

+1 −1

Original line number	Diff line number	Diff line
		@@ -18,7 +18,7 @@ jobs:
		# not to have GHA download an (at the time of writing) 4 GB cache
		# of PyTorch and other dependencies.
		- name: Install Ruff
		run: pip install ruff==0.0.265
		run: pip install ruff==0.0.272
		- name: Run Ruff
		run: ruff .
		lint-js:

.github/workflows/run_tests.yaml

+1 −1

Original line number	Diff line number	Diff line
		@@ -50,7 +50,7 @@ jobs:
		python -m pytest -vv --junitxml=test/results.xml --cov . --cov-report=xml --verify-base-url test
		- name: Kill test server
		if: always()
		run: curl -vv -XPOST http://127.0.0.1:7860/_stop && sleep 10
		run: curl -vv -XPOST http://127.0.0.1:7860/sdapi/v1/server-stop && sleep 10
		- name: Show coverage
		run: \|
		python -m coverage combine .coverage*

extensions-builtin/LDSR/scripts/ldsr_model.py

+8 −12

Original line number	Diff line number	Diff line
		import os

		from basicsr.utils.download_util import load_file_from_url

		from modules.modelloader import load_file_from_url
		from modules.upscaler import Upscaler, UpscalerData
		from ldsr_model_arch import LDSR
		from modules import shared, script_callbacks, errors
		@@ -43,20 +42,17 @@ class UpscalerLDSR(Upscaler):
		if local_safetensors_path is not None and os.path.exists(local_safetensors_path):
		model = local_safetensors_path
		else:
		model = local_ckpt_path if local_ckpt_path is not None else load_file_from_url(url=self.model_url, model_dir=self.model_download_path, file_name="model.ckpt", progress=True)
		model = local_ckpt_path or load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name="model.ckpt")

		yaml = local_yaml_path if local_yaml_path is not None else load_file_from_url(url=self.yaml_url, model_dir=self.model_download_path, file_name="project.yaml", progress=True)
		yaml = local_yaml_path or load_file_from_url(self.yaml_url, model_dir=self.model_download_path, file_name="project.yaml")

		try:
		return LDSR(model, yaml)
		except Exception:
		errors.report("Error importing LDSR", exc_info=True)
		return None

		def do_upscale(self, img, path):
		try:
		ldsr = self.load_model(path)
		if ldsr is None:
		print("NO LDSR!")
		except Exception:
		errors.report(f"Failed loading LDSR model {path}", exc_info=True)
		return img
		ddim_steps = shared.opts.ldsr_steps
		return ldsr.super_resolution(img, ddim_steps, self.scale)

extensions-builtin/ScuNET/scripts/scunet_model.py

+11 −15

Original line number	Diff line number	Diff line
		import os.path
		import sys

		import PIL.Image
		@@ -6,12 +5,11 @@ import numpy as np
		import torch
		from tqdm import tqdm

		from basicsr.utils.download_util import load_file_from_url

		import modules.upscaler
		from modules import devices, modelloader, script_callbacks, errors
		from scunet_model_arch import SCUNet as net
		from scunet_model_arch import SCUNet

		from modules.modelloader import load_file_from_url
		from modules.shared import opts


		@@ -28,7 +26,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
		scalers = []
		add_model2 = True
		for file in model_paths:
		if "http" in file:
		if file.startswith("http"):
		name = self.model_name
		else:
		name = modelloader.friendly_name(file)
		@@ -89,9 +87,10 @@ class UpscalerScuNET(modules.upscaler.Upscaler):

		torch.cuda.empty_cache()

		try:
		model = self.load_model(selected_file)
		if model is None:
		print(f"ScuNET: Unable to load model from {selected_file}", file=sys.stderr)
		except Exception as e:
		print(f"ScuNET: Unable to load model from {selected_file}: {e}", file=sys.stderr)
		return img

		device = devices.get_device_for('scunet')
		@@ -119,15 +118,12 @@ class UpscalerScuNET(modules.upscaler.Upscaler):

		def load_model(self, path: str):
		device = devices.get_device_for('scunet')
		if "http" in path:
		filename = load_file_from_url(url=self.model_url, model_dir=self.model_download_path, file_name="%s.pth" % self.name, progress=True)
		if path.startswith("http"):
		# TODO: this doesn't use `path` at all?
		filename = load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name=f"{self.name}.pth")
		else:
		filename = path
		if not os.path.exists(os.path.join(self.model_path, filename)) or filename is None:
		print(f"ScuNET: Unable to load model from {filename}", file=sys.stderr)
		return None

		model = net(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64)
		model = SCUNet(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64)
		model.load_state_dict(torch.load(filename), strict=True)
		model.eval()
		for _, v in model.named_parameters():

extensions-builtin/SwinIR/scripts/swinir_model.py

+29 −28

Original line number	Diff line number	Diff line
		import os
		import sys

		import numpy as np
		import torch
		from PIL import Image
		from basicsr.utils.download_util import load_file_from_url
		from tqdm import tqdm

		from modules import modelloader, devices, script_callbacks, shared
		from modules.shared import opts, state
		from swinir_model_arch import SwinIR as net
		from swinir_model_arch_v2 import Swin2SR as net2
		from swinir_model_arch import SwinIR
		from swinir_model_arch_v2 import Swin2SR
		from modules.upscaler import Upscaler, UpscalerData

		SWINIR_MODEL_URL = "https://github.com/JingyunLiang/SwinIR/releases/download/v0.0/003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth"

		device_swinir = devices.get_device_for('swinir')

		@@ -19,16 +19,14 @@ device_swinir = devices.get_device_for('swinir')
		class UpscalerSwinIR(Upscaler):
		def __init__(self, dirname):
		self.name = "SwinIR"
		self.model_url = "https://github.com/JingyunLiang/SwinIR/releases/download/v0.0" \
		"/003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR" \
		"-L_x4_GAN.pth "
		self.model_url = SWINIR_MODEL_URL
		self.model_name = "SwinIR 4x"
		self.user_path = dirname
		super().__init__()
		scalers = []
		model_files = self.find_models(ext_filter=[".pt", ".pth"])
		for model in model_files:
		if "http" in model:
		if model.startswith("http"):
		name = self.model_name
		else:
		name = modelloader.friendly_name(model)
		@@ -37,8 +35,10 @@ class UpscalerSwinIR(Upscaler):
		self.scalers = scalers

		def do_upscale(self, img, model_file):
		try:
		model = self.load_model(model_file)
		if model is None:
		except Exception as e:
		print(f"Failed loading SwinIR model {model_file}: {e}", file=sys.stderr)
		return img
		model = model.to(device_swinir, dtype=devices.dtype)
		img = upscale(img, model)
		@@ -49,15 +49,16 @@ class UpscalerSwinIR(Upscaler):
		return img

		def load_model(self, path, scale=4):
		if "http" in path:
		dl_name = "%s%s" % (self.model_name.replace(" ", "_"), ".pth")
		filename = load_file_from_url(url=path, model_dir=self.model_download_path, file_name=dl_name, progress=True)
		if path.startswith("http"):
		filename = modelloader.load_file_from_url(
		url=path,
		model_dir=self.model_download_path,
		file_name=f"{self.model_name.replace(' ', '_')}.pth",
		)
		else:
		filename = path
		if filename is None or not os.path.exists(filename):
		return None
		if filename.endswith(".v2.pth"):
		model = net2(
		model = Swin2SR(
		upscale=scale,
		in_chans=3,
		img_size=64,
		@@ -72,7 +73,7 @@ class UpscalerSwinIR(Upscaler):
		)
		params = None
		else:
		model = net(
		model = SwinIR(
		upscale=scale,
		in_chans=3,
		img_size=64,

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