import os import shutil from urllib.parse import urlparse from basicsr.utils.download_util import load_file_from_url from modules.paths import script_path, models_path def load_models(model_path: str, model_url: str = None, command_path: str = None, dl_name: str = None, existing=None, ext_filter=None) -> list: """ A one-and done loader to try finding the desired models in specified directories. @param dl_name: The file name to use for downloading a model. If not specified, it will be used from the URL. @param model_url: If specified, attempt to download model from the given URL. @param model_path: The location to store/find models in. @param command_path: A command-line argument to search for models in first. @param existing: An array of existing model paths. @param ext_filter: An optional list of filename extensions to filter by @return: A list of paths containing the desired model(s) """ if ext_filter is None: ext_filter = [] if existing is None: existing = [] try: places = [] if command_path is not None and command_path != model_path: pretrained_path = os.path.join(command_path, 'experiments/pretrained_models') if os.path.exists(pretrained_path): places.append(pretrained_path) elif os.path.exists(command_path): places.append(command_path) places.append(model_path) for place in places: if os.path.exists(place): for file in os.listdir(place): if os.path.isdir(file): continue if len(ext_filter) != 0: model_name, extension = os.path.splitext(file) if extension not in ext_filter: continue if file not in existing: path = os.path.join(place, file) existing.append(path) if model_url is not None and len(existing) == 0: if dl_name is not None: model_file = load_file_from_url(url=model_url, model_dir=model_path, file_name=dl_name, progress=True) else: model_file = load_file_from_url(url=model_url, model_dir=model_path, progress=True) if os.path.exists(model_file) and os.path.isfile(model_file) and model_file not in existing: existing.append(model_file) except: pass return existing def friendly_name(file: str): if "http" in file: file = urlparse(file).path file = os.path.basename(file) model_name, extension = os.path.splitext(file) model_name = model_name.replace("_", " ").title() return model_name def cleanup_models(): # This code could probably be more efficient if we used a tuple list or something to store the src/destinations # and then enumerate that, but this works for now. In the future, it'd be nice to just have every "model" scaler # somehow auto-register and just do these things... root_path = script_path src_path = models_path dest_path = os.path.join(models_path, "Stable-diffusion") move_files(src_path, dest_path, ".ckpt") src_path = os.path.join(root_path, "ESRGAN") dest_path = os.path.join(models_path, "ESRGAN") move_files(src_path, dest_path) src_path = os.path.join(root_path, "gfpgan") dest_path = os.path.join(models_path, "GFPGAN") move_files(src_path, dest_path) src_path = os.path.join(root_path, "SwinIR") dest_path = os.path.join(models_path, "SwinIR") move_files(src_path, dest_path) src_path = os.path.join(root_path, "repositories/latent-diffusion/experiments/pretrained_models/") dest_path = os.path.join(models_path, "LDSR") move_files(src_path, dest_path) def move_files(src_path: str, dest_path: str, ext_filter: str = None): try: if not os.path.exists(dest_path): os.makedirs(dest_path) if os.path.exists(src_path): for file in os.listdir(src_path): fullpath = os.path.join(src_path, file) if os.path.isfile(fullpath): if ext_filter is not None: if ext_filter not in file: continue print(f"Moving {file} from {src_path} to {dest_path}.") try: shutil.move(fullpath, dest_path) except: pass if len(os.listdir(src_path)) == 0: print(f"Removing empty folder: {src_path}") shutil.rmtree(src_path, True) except: pass