diff options
Diffstat (limited to 'extensions-builtin')
| -rw-r--r-- | extensions-builtin/LDSR/ldsr_model_arch.py | 8 | ||||
| -rw-r--r-- | extensions-builtin/LDSR/scripts/ldsr_model.py | 20 | ||||
| -rw-r--r-- | extensions-builtin/Lora/lora.py | 2 | ||||
| -rw-r--r-- | extensions-builtin/ScuNET/scripts/scunet_model.py | 30 | ||||
| -rw-r--r-- | extensions-builtin/SwinIR/scripts/swinir_model.py | 62 | ||||
| -rw-r--r-- | extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js | 30 | ||||
| -rw-r--r-- | extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py | 1 |
7 files changed, 85 insertions, 68 deletions
diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py index 7f450086..7cac36ce 100644 --- a/extensions-builtin/LDSR/ldsr_model_arch.py +++ b/extensions-builtin/LDSR/ldsr_model_arch.py @@ -12,7 +12,7 @@ import safetensors.torch from ldm.models.diffusion.ddim import DDIMSampler from ldm.util import instantiate_from_config, ismap -from modules import shared, sd_hijack +from modules import shared, sd_hijack, devices cached_ldsr_model: torch.nn.Module = None @@ -112,8 +112,7 @@ class LDSR: gc.collect() - if torch.cuda.is_available: - torch.cuda.empty_cache() + devices.torch_gc() im_og = image width_og, height_og = im_og.size @@ -150,8 +149,7 @@ class LDSR: del model gc.collect() - if torch.cuda.is_available: - torch.cuda.empty_cache() + devices.torch_gc() return a diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py index dbd6d331..bd78dece 100644 --- a/extensions-builtin/LDSR/scripts/ldsr_model.py +++ b/extensions-builtin/LDSR/scripts/ldsr_model.py @@ -1,7 +1,6 @@ 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 + return LDSR(model, yaml) def do_upscale(self, img, path): - ldsr = self.load_model(path) - if ldsr is None: - print("NO LDSR!") + try: + ldsr = self.load_model(path) + 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) diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index 34ff57dd..cd46e6c7 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -443,7 +443,7 @@ def list_available_loras(): os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True)
candidates = list(shared.walk_files(shared.cmd_opts.lora_dir, allowed_extensions=[".pt", ".ckpt", ".safetensors"]))
- for filename in sorted(candidates, key=str.lower):
+ for filename in candidates:
if os.path.isdir(filename):
continue
diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index 85b4505f..167d2f64 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -1,4 +1,3 @@ -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) @@ -87,11 +85,12 @@ class UpscalerScuNET(modules.upscaler.Upscaler): def do_upscale(self, img: PIL.Image.Image, selected_file): - torch.cuda.empty_cache() + devices.torch_gc() - model = self.load_model(selected_file) - if model is None: - print(f"ScuNET: Unable to load model from {selected_file}", file=sys.stderr) + try: + model = self.load_model(selected_file) + 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') @@ -111,7 +110,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): torch_output = torch_output[:, :h * 1, :w * 1] # remove padding, if any np_output: np.ndarray = torch_output.float().cpu().clamp_(0, 1).numpy() del torch_img, torch_output - torch.cuda.empty_cache() + devices.torch_gc() output = np_output.transpose((1, 2, 0)) # CHW to HWC output = output[:, :, ::-1] # BGR to RGB @@ -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(): diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index 1c7bf325..c2c2a43c 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/extensions-builtin/SwinIR/scripts/swinir_model.py @@ -1,17 +1,17 @@ -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) @@ -37,42 +35,42 @@ class UpscalerSwinIR(Upscaler): self.scalers = scalers def do_upscale(self, img, model_file): - model = self.load_model(model_file) - if model is None: + try: + model = self.load_model(model_file) + 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) - try: - torch.cuda.empty_cache() - except Exception: - pass + devices.torch_gc() 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( - upscale=scale, - in_chans=3, - img_size=64, - window_size=8, - img_range=1.0, - depths=[6, 6, 6, 6, 6, 6], - embed_dim=180, - num_heads=[6, 6, 6, 6, 6, 6], - mlp_ratio=2, - upsampler="nearest+conv", - resi_connection="1conv", + model = Swin2SR( + upscale=scale, + in_chans=3, + img_size=64, + window_size=8, + img_range=1.0, + depths=[6, 6, 6, 6, 6, 6], + embed_dim=180, + num_heads=[6, 6, 6, 6, 6, 6], + mlp_ratio=2, + upsampler="nearest+conv", + resi_connection="1conv", ) params = None else: - model = net( + model = SwinIR( upscale=scale, in_chans=3, img_size=64, diff --git a/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js b/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js index 5ebd2073..30199dcd 100644 --- a/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js +++ b/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js @@ -200,7 +200,8 @@ onUiLoaded(async() => { canvas_hotkey_move: "KeyF", canvas_hotkey_overlap: "KeyO", canvas_disabled_functions: [], - canvas_show_tooltip: true + canvas_show_tooltip: true, + canvas_blur_prompt: false }; const functionMap = { @@ -608,6 +609,19 @@ onUiLoaded(async() => { // Handle keydown events function handleKeyDown(event) { + // Disable key locks to make pasting from the buffer work correctly + if ((event.ctrlKey && event.code === 'KeyV') || (event.ctrlKey && event.code === 'KeyC') || event.code === "F5") { + return; + } + + // before activating shortcut, ensure user is not actively typing in an input field + if (!hotkeysConfig.canvas_blur_prompt) { + if (event.target.nodeName === 'TEXTAREA' || event.target.nodeName === 'INPUT') { + return; + } + } + + const hotkeyActions = { [hotkeysConfig.canvas_hotkey_reset]: resetZoom, [hotkeysConfig.canvas_hotkey_overlap]: toggleOverlap, @@ -686,6 +700,20 @@ onUiLoaded(async() => { // Handle the move event for pan functionality. Updates the panX and panY variables and applies the new transform to the target element. function handleMoveKeyDown(e) { + + // Disable key locks to make pasting from the buffer work correctly + if ((e.ctrlKey && e.code === 'KeyV') || (e.ctrlKey && event.code === 'KeyC') || e.code === "F5") { + return; + } + + // before activating shortcut, ensure user is not actively typing in an input field + if (!hotkeysConfig.canvas_blur_prompt) { + if (e.target.nodeName === 'TEXTAREA' || e.target.nodeName === 'INPUT') { + return; + } + } + + if (e.code === hotkeysConfig.canvas_hotkey_move) { if (!e.ctrlKey && !e.metaKey && isKeyDownHandlerAttached) { e.preventDefault(); diff --git a/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py b/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py index 1b6683aa..380176ce 100644 --- a/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py +++ b/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py @@ -9,5 +9,6 @@ shared.options_templates.update(shared.options_section(('canvas_hotkey', "Canvas "canvas_hotkey_reset": shared.OptionInfo("R", "Reset zoom and canvas positon"), "canvas_hotkey_overlap": shared.OptionInfo("O", "Toggle overlap").info("Technical button, neededs for testing"), "canvas_show_tooltip": shared.OptionInfo(True, "Enable tooltip on the canvas"), + "canvas_blur_prompt": shared.OptionInfo(False, "Take the focus off the prompt when working with a canvas"), "canvas_disabled_functions": shared.OptionInfo(["Overlap"], "Disable function that you don't use", gr.CheckboxGroup, {"choices": ["Zoom","Adjust brush size", "Moving canvas","Fullscreen","Reset Zoom","Overlap"]}), })) |