import os import logging import picklescan.scanner import rich from sd_internal import app from modules import model_loader from modules.types import Context log = logging.getLogger() KNOWN_MODEL_TYPES = ['stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan'] MODEL_EXTENSIONS = { 'stable-diffusion': ['.ckpt', '.safetensors'], 'vae': ['.vae.pt', '.ckpt'], 'hypernetwork': ['.pt'], 'gfpgan': ['.pth'], 'realesrgan': ['.pth'], } DEFAULT_MODELS = { 'stable-diffusion': [ # needed to support the legacy installations 'custom-model', # only one custom model file was supported initially, creatively named 'custom-model' 'sd-v1-4', # Default fallback. ], 'gfpgan': ['GFPGANv1.3'], 'realesrgan': ['RealESRGAN_x4plus'], } known_models = {} def init(): make_model_folders() getModels() # run this once, to cache the picklescan results def load_default_models(context: Context): # init default model paths for model_type in KNOWN_MODEL_TYPES: context.model_paths[model_type] = resolve_model_to_use(model_type=model_type) # load mandatory models model_loader.load_model(context, 'stable-diffusion') def unload_all(context: Context): for model_type in KNOWN_MODEL_TYPES: model_loader.unload_model(context, model_type) def resolve_model_to_use(model_name:str=None, model_type:str=None): model_extensions = MODEL_EXTENSIONS.get(model_type, []) default_models = DEFAULT_MODELS.get(model_type, []) config = app.getConfig() model_dirs = [os.path.join(app.MODELS_DIR, model_type), app.SD_DIR] if not model_name: # When None try user configured model. # config = getConfig() if 'model' in config and model_type in config['model']: model_name = config['model'][model_type] if model_name: is_sd2 = config.get('test_sd2', False) if model_name.startswith('sd2_') and not is_sd2: # temp hack, until SD2 is unified with 1.4 log.error('ERROR: Cannot use SD 2.0 models with SD 1.0 code. Using the sd-v1-4 model instead!') model_name = 'sd-v1-4' # Check models directory models_dir_path = os.path.join(app.MODELS_DIR, model_type, model_name) for model_extension in model_extensions: if os.path.exists(models_dir_path + model_extension): return models_dir_path + model_extension if os.path.exists(model_name + model_extension): return os.path.abspath(model_name + model_extension) # Default locations if model_name in default_models: default_model_path = os.path.join(app.SD_DIR, model_name) for model_extension in model_extensions: if os.path.exists(default_model_path + model_extension): return default_model_path + model_extension # Can't find requested model, check the default paths. for default_model in default_models: for model_dir in model_dirs: default_model_path = os.path.join(model_dir, default_model) for model_extension in model_extensions: if os.path.exists(default_model_path + model_extension): if model_name is not None: log.warn(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}') return default_model_path + model_extension return None def make_model_folders(): for model_type in KNOWN_MODEL_TYPES: model_dir_path = os.path.join(app.MODELS_DIR, model_type) os.makedirs(model_dir_path, exist_ok=True) help_file_name = f'Place your {model_type} model files here.txt' help_file_contents = f'Supported extensions: {" or ".join(MODEL_EXTENSIONS.get(model_type))}' with open(os.path.join(model_dir_path, help_file_name), 'w', encoding='utf-8') as f: f.write(help_file_contents) def is_malicious_model(file_path): try: scan_result = picklescan.scanner.scan_file_path(file_path) if scan_result.issues_count > 0 or scan_result.infected_files > 0: log.warn(":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files)) return True else: log.debug("Scan %s: [green]%d scanned, %d issue, %d infected.[/green]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files)) return False except Exception as e: log.error(f'error while scanning: {file_path}, error: {e}') return False def getModels(): models = { 'active': { 'stable-diffusion': 'sd-v1-4', 'vae': '', 'hypernetwork': '', }, 'options': { 'stable-diffusion': ['sd-v1-4'], 'vae': [], 'hypernetwork': [], }, } models_scanned = 0 def listModels(model_type): nonlocal models_scanned model_extensions = MODEL_EXTENSIONS.get(model_type, []) models_dir = os.path.join(app.MODELS_DIR, model_type) if not os.path.exists(models_dir): os.makedirs(models_dir) for file in os.listdir(models_dir): for model_extension in model_extensions: if not file.endswith(model_extension): continue model_path = os.path.join(models_dir, file) mtime = os.path.getmtime(model_path) mod_time = known_models[model_path] if model_path in known_models else -1 if mod_time != mtime: models_scanned += 1 if is_malicious_model(model_path): models['scan-error'] = file return known_models[model_path] = mtime model_name = file[:-len(model_extension)] models['options'][model_type].append(model_name) models['options'][model_type] = [*set(models['options'][model_type])] # remove duplicates models['options'][model_type].sort() # custom models listModels(model_type='stable-diffusion') listModels(model_type='vae') listModels(model_type='hypernetwork') if models_scanned > 0: log.info(f'[green]Scanned {models_scanned} models. Nothing infected[/]') # legacy custom_weight_path = os.path.join(app.SD_DIR, 'custom-model.ckpt') if os.path.exists(custom_weight_path): models['options']['stable-diffusion'].append('custom-model') return models