mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
implemented tabbed model selection; not wired to backend yet
This commit is contained in:
Lincoln Stein
parent
d6530df635
commit
e9821ab711
@ -6,6 +6,7 @@ import re
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import shutil
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import sys
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import warnings
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from dataclasses import dataclass
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from pathlib import Path
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from tempfile import TemporaryFile
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from typing import List, Dict
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@ -20,9 +21,8 @@ from tqdm import tqdm
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import invokeai.configs as configs
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from invokeai.app.services.config import get_invokeai_config
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from ..model_management import ModelManager
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from ..stable_diffusion import StableDiffusionGeneratorPipeline
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from ..util.logging import InvokeAILogger
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warnings.filterwarnings("ignore")
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@ -37,6 +37,9 @@ Dataset_path = Path(configs.__path__[0]) / "INITIAL_MODELS.yaml"
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# initial models omegaconf
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Datasets = None
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# logger
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logger = InvokeAILogger.getLogger(name='InvokeAI')
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Config_preamble = """
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# This file describes the alternative machine learning models
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# available to InvokeAI script.
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@ -47,6 +50,11 @@ Config_preamble = """
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# was trained on.
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"""
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@dataclass
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class ModelInstallList:
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'''Class for listing models to be installed/removed'''
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install_models: List[str]
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remove_models: List[str]
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def default_config_file():
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return config.model_conf_path
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@ -61,11 +69,11 @@ def initial_models():
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return (Datasets := OmegaConf.load(Dataset_path)['diffusers'])
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def install_requested_models(
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install_initial_models: List[str] = None,
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remove_models: List[str] = None,
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install_cn_models: List[str] = None,
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remove_cn_models: List[str] = None,
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cn_model_map: Dict[str,str] = None,
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diffusers: ModelInstallList = None,
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controlnet: ModelInstallList = None,
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lora: ModelInstallList = None,
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ti: ModelInstallList = None,
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cn_model_map: Dict[str,str] = None, # temporary - move to model manager
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scan_directory: Path = None,
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external_models: List[str] = None,
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scan_at_startup: bool = False,
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@ -81,33 +89,30 @@ def install_requested_models(
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if not config_file_path.exists():
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open(config_file_path, "w")
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install_controlnet_models(
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install_cn_models,
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short_name_map = cn_model_map,
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precision=precision,
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access_token=access_token,
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)
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delete_controlnet_models(remove_cn_models)
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# prevent circular import here
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from ..model_management import ModelManager
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model_manager = ModelManager(OmegaConf.load(config_file_path), precision=precision)
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model_manager.install_controlnet_models(controlnet.install_models, access_token=access_token)
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model_manager.delete_controlnet_models(controlnet.remove_models)
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if remove_models and len(remove_models) > 0:
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print("== DELETING UNCHECKED STARTER MODELS ==")
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for model in remove_models:
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print(f"{model}...")
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# TODO: Replace next three paragraphs with calls into new model manager
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if diffusers.remove_models and len(diffusers.remove_models) > 0:
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logger.info("DELETING UNCHECKED STARTER MODELS")
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for model in diffusers.remove_models:
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logger.info(f"{model}...")
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model_manager.del_model(model, delete_files=purge_deleted)
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model_manager.commit(config_file_path)
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if install_initial_models and len(install_initial_models) > 0:
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print("== INSTALLING SELECTED STARTER MODELS ==")
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if diffusers.install_models and len(diffusers.install_models) > 0:
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logger.info("INSTALLING SELECTED STARTER MODELS")
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successfully_downloaded = download_weight_datasets(
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models=install_initial_models,
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models=diffusers.install_initial_models,
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access_token=None,
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precision=precision,
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) # FIX: for historical reasons, we don't use model manager here
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update_config_file(successfully_downloaded, config_file_path)
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if len(successfully_downloaded) < len(install_initial_models):
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print("** Some of the model downloads were not successful")
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if len(successfully_downloaded) < len(diffusers.install_models):
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logger.warning("Some of the model downloads were not successful")
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# due to above, we have to reload the model manager because conf file
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# was changed behind its back
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@ -118,7 +123,7 @@ def install_requested_models(
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external_models.append(str(scan_directory))
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if len(external_models) > 0:
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print("== INSTALLING EXTERNAL MODELS ==")
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logger.info("INSTALLING EXTERNAL MODELS")
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for path_url_or_repo in external_models:
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try:
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model_manager.heuristic_import(
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@ -190,10 +195,10 @@ def migrate_models_ckpt():
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if not os.path.exists(os.path.join(model_path, "model.ckpt")):
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return
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new_name = initial_models()["stable-diffusion-1.4"]["file"]
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print(
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logger.warning(
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'The Stable Diffusion v4.1 "model.ckpt" is already installed. The name will be changed to {new_name} to avoid confusion.'
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)
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print(f"model.ckpt => {new_name}")
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logger.warning(f"model.ckpt => {new_name}")
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os.replace(
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os.path.join(model_path, "model.ckpt"), os.path.join(model_path, new_name)
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)
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@ -206,7 +211,7 @@ def download_weight_datasets(
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migrate_models_ckpt()
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successful = dict()
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for mod in models:
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print(f"Downloading {mod}:")
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logger.info(f"Downloading {mod}:")
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successful[mod] = _download_repo_or_file(
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initial_models()[mod], access_token, precision=precision
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)
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@ -240,68 +245,6 @@ def _download_ckpt_weights(mconfig: DictConfig, access_token: str) -> Path:
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)
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# ---------------------------------------------
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def install_controlnet_models(
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short_names: List[str],
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short_name_map: Dict[str,str],
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precision: str='float16',
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access_token: str = None,
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):
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'''
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Download list of controlnet models, using their HuggingFace
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repo_ids.
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'''
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dest_dir = config.controlnet_path
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if not dest_dir.exists():
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dest_dir.mkdir(parents=True,exist_ok=False)
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# The model file may be fp32 or fp16, and may be either a
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# .bin file or a .safetensors. We try each until we get one,
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# preferring 'fp16' if using half precision, and preferring
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# safetensors over over bin.
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precisions = ['.fp16',''] if precision=='float16' else ['']
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formats = ['.safetensors','.bin']
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possible_filenames = list()
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for p in precisions:
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for f in formats:
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possible_filenames.append(Path(f'diffusion_pytorch_model{p}{f}'))
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for directory_name in short_names:
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repo_id = short_name_map[directory_name]
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safe_name = directory_name.replace('/','--')
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print(f'Downloading ControlNet model {directory_name} ({repo_id})')
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hf_download_with_resume(
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repo_id = repo_id,
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model_dir = dest_dir / safe_name,
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model_name = 'config.json',
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access_token = access_token
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)
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path = None
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for filename in possible_filenames:
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suffix = filename.suffix
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dest_filename = Path(f'diffusion_pytorch_model{suffix}')
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print(f'Probing {directory_name}/{filename}...')
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path = hf_download_with_resume(
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repo_id = repo_id,
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model_dir = dest_dir / safe_name,
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model_name = str(filename),
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access_token = access_token,
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model_dest = Path(dest_dir, safe_name, dest_filename),
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)
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if path:
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(path.parent / '.download_complete').touch()
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break
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# ---------------------------------------------
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def delete_controlnet_models(short_names: List[str]):
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for name in short_names:
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safe_name = name.replace('/','--')
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directory = config.controlnet_path / safe_name
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if directory.exists():
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print(f'Purging controlnet model {name}')
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shutil.rmtree(str(directory))
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# ---------------------------------------------
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def download_from_hf(
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model_class: object, model_name: str, **kwargs
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@ -340,7 +283,7 @@ def _download_diffusion_weights(
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if str(e).startswith("fp16 is not a valid"):
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pass
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else:
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print(f"An unexpected error occurred while downloading the model: {e})")
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logger.error(f"An unexpected error occurred while downloading the model: {e})")
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if path:
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break
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return path
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@ -374,17 +317,17 @@ def hf_download_with_resume(
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if (
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resp.status_code == 416
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): # "range not satisfiable", which means nothing to return
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print(f"* {model_name}: complete file found. Skipping.")
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logger.info(f"{model_name}: complete file found. Skipping.")
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return model_dest
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elif resp.status_code == 404:
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print("** File not found")
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logger.warning("File not found")
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return None
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elif resp.status_code != 200:
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print(f"** Warning: {model_name}: {resp.reason}")
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logger.warning(f"{model_name}: {resp.reason}")
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elif exist_size > 0:
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print(f"* {model_name}: partial file found. Resuming...")
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logger.info(f"{model_name}: partial file found. Resuming...")
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else:
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print(f"* {model_name}: Downloading...")
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logger.info(f"{model_name}: Downloading...")
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try:
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with open(model_dest, open_mode) as file, tqdm(
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@ -399,7 +342,7 @@ def hf_download_with_resume(
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size = file.write(data)
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bar.update(size)
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except Exception as e:
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print(f"An error occurred while downloading {model_name}: {str(e)}")
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logger.error(f"An error occurred while downloading {model_name}: {str(e)}")
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return None
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return model_dest
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@ -424,8 +367,8 @@ def update_config_file(successfully_downloaded: dict, config_file: Path):
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try:
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backup = None
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if os.path.exists(config_file):
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print(
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f"** {config_file.name} exists. Renaming to {config_file.stem}.yaml.orig"
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logger.warning(
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f"{config_file.name} exists. Renaming to {config_file.stem}.yaml.orig"
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)
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backup = config_file.with_suffix(".yaml.orig")
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## Ugh. Windows is unable to overwrite an existing backup file, raises a WinError 183
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@ -442,16 +385,16 @@ def update_config_file(successfully_downloaded: dict, config_file: Path):
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new_config.write(tmp.read())
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except Exception as e:
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print(f"**Error creating config file {config_file}: {str(e)} **")
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logger.error(f"Error creating config file {config_file}: {str(e)}")
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if backup is not None:
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print("restoring previous config file")
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logger.info("restoring previous config file")
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## workaround, for WinError 183, see above
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if sys.platform == "win32" and config_file.is_file():
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config_file.unlink()
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backup.rename(config_file)
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return
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print(f"Successfully created new configuration file {config_file}")
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logger.info(f"Successfully created new configuration file {config_file}")
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# ---------------------------------------------
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@ -518,8 +461,8 @@ def delete_weights(model_name: str, conf_stanza: dict):
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if re.match("/VAE/", conf_stanza.get("config")):
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return
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print(
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f"\n** The checkpoint version of {model_name} is superseded by the diffusers version. Deleting the original file {weights}?"
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logger.warning(
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f"\nThe checkpoint version of {model_name} is superseded by the diffusers version. Deleting the original file {weights}?"
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)
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weights = Path(weights)
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@ -528,4 +471,4 @@ def delete_weights(model_name: str, conf_stanza: dict):
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try:
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weights.unlink()
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except OSError as e:
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print(str(e))
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logger.error(str(e))
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@ -11,6 +11,7 @@ import gc
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import hashlib
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import os
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import re
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import shutil
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import sys
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import textwrap
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import time
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@ -49,6 +50,10 @@ from ..stable_diffusion import (
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StableDiffusionGeneratorPipeline,
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)
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from invokeai.app.services.config import get_invokeai_config
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from ..install.model_install_backend import (
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Dataset_path,
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hf_download_with_resume,
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)
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from ..util import CUDA_DEVICE, ask_user, download_with_resume
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class SDLegacyType(Enum):
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@ -1316,3 +1321,74 @@ class ModelManager(object):
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return (
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os.getenv("HF_HOME") is not None or os.getenv("XDG_CACHE_HOME") is not None
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)
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def list_controlnet_models(self)->Dict[str,bool]:
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'''Return a dict of installed controlnet models; key is repo_id or short name
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of model (defined in INITIAL_MODELS), and valule is True if installed'''
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cn_models = OmegaConf.load(Dataset_path).get('controlnet') or {}
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installed_models = {x: False for x in cn_models.keys()}
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cn_dir = self.globals.controlnet_path
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installed_cn_models = dict()
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for root, dirs, files in os.walk(cn_dir):
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for name in dirs:
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if Path(root, name, '.download_complete').exists():
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installed_models.update({name.replace('--','/'): True})
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return installed_models
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def install_controlnet_models(self, model_names: list[str], access_token: str=None):
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'''Download list of controlnet models; provide either repo_id or short name listed in INITIAL_MODELS.yaml'''
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short_names = OmegaConf.load(Dataset_path).get('controlnet') or {}
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dest_dir = self.globals.controlnet_path
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dest_dir.mkdir(parents=True,exist_ok=True)
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# The model file may be fp32 or fp16, and may be either a
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# .bin file or a .safetensors. We try each until we get one,
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# preferring 'fp16' if using half precision, and preferring
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# safetensors over over bin.
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precisions = ['.fp16',''] if self.precision=='float16' else ['']
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formats = ['.safetensors','.bin']
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possible_filenames = list()
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for p in precisions:
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for f in formats:
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possible_filenames.append(Path(f'diffusion_pytorch_model{p}{f}'))
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for directory_name in model_names:
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repo_id = short_names.get(directory_name) or directory_name
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safe_name = directory_name.replace('/','--')
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self.logger.info(f'Downloading ControlNet model {directory_name} ({repo_id})')
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hf_download_with_resume(
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repo_id = repo_id,
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model_dir = dest_dir / safe_name,
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model_name = 'config.json',
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access_token = access_token
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)
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path = None
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for filename in possible_filenames:
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suffix = filename.suffix
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dest_filename = Path(f'diffusion_pytorch_model{suffix}')
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self.logger.info(f'Checking availability of {directory_name}/{filename}...')
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path = hf_download_with_resume(
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repo_id = repo_id,
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model_dir = dest_dir / safe_name,
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model_name = str(filename),
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access_token = access_token,
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model_dest = Path(dest_dir, safe_name, dest_filename),
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)
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if path:
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(path.parent / '.download_complete').touch()
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break
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def delete_controlnet_models(self, model_names: List[str]):
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'''Remove the list of controlnet models'''
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for name in model_names:
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safe_name = name.replace('/','--')
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directory = self.globals.controlnet_path / safe_name
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if directory.exists():
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self.logger.info(f'Purging controlnet model {name}')
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shutil.rmtree(str(directory))
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@ -30,11 +30,15 @@ from ...backend.install.model_install_backend import (
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default_dataset,
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install_requested_models,
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recommended_datasets,
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ModelInstallList,
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dataclass,
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)
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from ...backend import ModelManager
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from ...backend.util import choose_precision, choose_torch_device
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from .widgets import (
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CenteredTitleText,
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MultiSelectColumns,
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SingleSelectColumns,
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OffsetButtonPress,
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TextBox,
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set_min_terminal_size,
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@ -53,12 +57,12 @@ class addModelsForm(npyscreen.FormMultiPage):
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def __init__(self, parentApp, name, multipage=False, *args, **keywords):
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self.multipage = multipage
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model_manager = ModelManager(config.model_conf_path)
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self.initial_models = OmegaConf.load(Dataset_path)['diffusers']
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self.control_net_models = OmegaConf.load(Dataset_path)['controlnet']
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self.installed_cn_models = self._get_installed_cn_models()
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self._add_additional_cn_models(self.control_net_models,self.installed_cn_models)
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self.installed_cn_models = model_manager.list_controlnet_models()
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try:
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self.existing_models = OmegaConf.load(default_config_file())
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except:
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@ -79,7 +83,7 @@ class addModelsForm(npyscreen.FormMultiPage):
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[x for x in list(self.initial_models.keys()) if x in self.existing_models]
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)
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cn_model_list = sorted(self.control_net_models.keys())
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cn_model_list = sorted(self.installed_cn_models.keys())
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self.nextrely -= 1
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self.add_widget_intelligent(
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@ -180,16 +184,34 @@ class addModelsForm(npyscreen.FormMultiPage):
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||||
relx=4,
|
||||
scroll_exit=True,
|
||||
)
|
||||
|
||||
self.add_widget_intelligent(
|
||||
CenteredTitleText,
|
||||
name="== CONTROLNET MODELS ==",
|
||||
name='_' * (window_width-5),
|
||||
editable=False,
|
||||
color="CONTROL",
|
||||
labelColor='CAUTION'
|
||||
)
|
||||
self.nextrely -= 1
|
||||
self.add_widget_intelligent(
|
||||
|
||||
self.nextrely += 1
|
||||
self.tabs = self.add_widget_intelligent(
|
||||
SingleSelectColumns,
|
||||
values=['ADD CONTROLNET MODELS','ADD LORA/LYCORIS MODELS', 'ADD TEXTUAL INVERSION MODELS'],
|
||||
value=0,
|
||||
columns = 4,
|
||||
max_height = 2,
|
||||
relx=8,
|
||||
scroll_exit = True,
|
||||
)
|
||||
# self.add_widget_intelligent(
|
||||
# CenteredTitleText,
|
||||
# name="== CONTROLNET MODELS ==",
|
||||
# editable=False,
|
||||
# color="CONTROL",
|
||||
# )
|
||||
top_of_table = self.nextrely
|
||||
self.cn_label_1 = self.add_widget_intelligent(
|
||||
CenteredTitleText,
|
||||
name="Select the desired ControlNet models. Unchecked models will be purged from disk.",
|
||||
name="Select the desired models to install. Unchecked models will be purged from disk.",
|
||||
editable=False,
|
||||
labelColor="CAUTION",
|
||||
)
|
||||
@ -202,14 +224,14 @@ class addModelsForm(npyscreen.FormMultiPage):
|
||||
value=[
|
||||
cn_model_list.index(x)
|
||||
for x in cn_model_list
|
||||
if x in self.installed_cn_models
|
||||
if self.installed_cn_models[x]
|
||||
],
|
||||
max_height=len(cn_model_list)//columns + 1,
|
||||
relx=4,
|
||||
scroll_exit=True,
|
||||
)
|
||||
self.nextrely += 1
|
||||
self.add_widget_intelligent(
|
||||
self.cn_label_2 = self.add_widget_intelligent(
|
||||
npyscreen.TitleFixedText,
|
||||
name='Additional ControlNet HuggingFace repo_ids to install (Space separated. Use shift-control-V to paste):',
|
||||
relx=4,
|
||||
@ -221,6 +243,55 @@ class addModelsForm(npyscreen.FormMultiPage):
|
||||
self.additional_controlnet_ids = self.add_widget_intelligent(
|
||||
TextBox, max_height=2, scroll_exit=True, editable=True, relx=4
|
||||
)
|
||||
|
||||
bottom_of_table = self.nextrely
|
||||
self.nextrely = top_of_table
|
||||
self.lora_label_1 = self.add_widget_intelligent(
|
||||
npyscreen.TitleFixedText,
|
||||
name='LoRA/LYCORIS models to download and install (Space separated. Use shift-control-V to paste):',
|
||||
relx=4,
|
||||
color='CONTROL',
|
||||
editable=False,
|
||||
hidden=True,
|
||||
scroll_exit=True
|
||||
)
|
||||
self.nextrely -= 1
|
||||
self.loras = self.add_widget_intelligent(
|
||||
TextBox,
|
||||
max_height=2,
|
||||
scroll_exit=True,
|
||||
editable=True,
|
||||
relx=4,
|
||||
hidden=True,
|
||||
)
|
||||
self.nextrely = top_of_table
|
||||
self.ti_label_1 = self.add_widget_intelligent(
|
||||
npyscreen.TitleFixedText,
|
||||
name='Textual Inversion models to download and install (Space separated. Use shift-control-V to paste):',
|
||||
relx=4,
|
||||
color='CONTROL',
|
||||
editable=False,
|
||||
hidden=True,
|
||||
scroll_exit=True
|
||||
)
|
||||
self.nextrely -= 1
|
||||
self.tis = self.add_widget_intelligent(
|
||||
TextBox,
|
||||
max_height=2,
|
||||
scroll_exit=True,
|
||||
editable=True,
|
||||
relx=4,
|
||||
hidden=True,
|
||||
)
|
||||
self.nextrely = bottom_of_table
|
||||
self.nextrely += 1
|
||||
self.add_widget_intelligent(
|
||||
CenteredTitleText,
|
||||
name='_' * (window_width-5),
|
||||
editable=False,
|
||||
labelColor='CAUTION'
|
||||
)
|
||||
|
||||
self.cancel = self.add_widget_intelligent(
|
||||
npyscreen.ButtonPress,
|
||||
name="CANCEL",
|
||||
@ -254,6 +325,9 @@ class addModelsForm(npyscreen.FormMultiPage):
|
||||
for i in [self.autoload_directory, self.autoscan_on_startup]:
|
||||
self.show_directory_fields.addVisibleWhenSelected(i)
|
||||
|
||||
# self.tabs.when_value_edited = self._toggle_tables
|
||||
self.tabs.on_changed = self._toggle_tables
|
||||
|
||||
self.show_directory_fields.when_value_edited = self._clear_scan_directory
|
||||
|
||||
def resize(self):
|
||||
@ -261,6 +335,21 @@ class addModelsForm(npyscreen.FormMultiPage):
|
||||
if hasattr(self, "models_selected"):
|
||||
self.models_selected.values = self._get_starter_model_labels()
|
||||
|
||||
def _toggle_tables(self, value=None):
|
||||
selected_tab = value[0] if value else self.tabs.value[0]
|
||||
widgets = [
|
||||
[self.cn_label_1, self.cn_models_selected, self.cn_label_2, self.additional_controlnet_ids],
|
||||
[self.lora_label_1,self.loras],
|
||||
[self.ti_label_1,self.tis],
|
||||
]
|
||||
|
||||
for group in widgets:
|
||||
for w in group:
|
||||
w.hidden = True
|
||||
for w in widgets[selected_tab]:
|
||||
w.hidden = False
|
||||
self.display()
|
||||
|
||||
def _clear_scan_directory(self):
|
||||
if not self.show_directory_fields.value:
|
||||
self.autoload_directory.value = ""
|
||||
@ -361,20 +450,18 @@ class addModelsForm(npyscreen.FormMultiPage):
|
||||
selections.install_models = [x for x in starter_models if x not in self.existing_models]
|
||||
selections.remove_models = [x for x in self.starter_model_list if x in self.existing_models and x not in starter_models]
|
||||
|
||||
selections.control_net_map = self.control_net_models
|
||||
selections.install_cn_models = [self.cn_models_selected.values[x]
|
||||
for x in self.cn_models_selected.value
|
||||
if self.cn_models_selected.values[x] not in self.installed_cn_models
|
||||
if not self.installed_cn_models[self.cn_models_selected.values[x]]
|
||||
]
|
||||
selections.remove_cn_models = [x
|
||||
for x in self.cn_models_selected.values
|
||||
if x in self.installed_cn_models
|
||||
if self.installed_cn_models[x]
|
||||
and self.cn_models_selected.values.index(x) not in self.cn_models_selected.value
|
||||
]
|
||||
if (additional_cns := self.additional_controlnet_ids.value.split()):
|
||||
valid_cns = [x for x in additional_cns if '/' in x]
|
||||
selections.install_cn_models.extend(valid_cns)
|
||||
selections.control_net_map.update({x: x for x in valid_cns})
|
||||
|
||||
# load directory and whether to scan on startup
|
||||
if self.show_directory_fields.value:
|
||||
@ -387,22 +474,22 @@ class addModelsForm(npyscreen.FormMultiPage):
|
||||
# URLs and the like
|
||||
selections.import_model_paths = self.import_model_paths.value.split()
|
||||
|
||||
|
||||
@dataclass
|
||||
class UserSelections():
|
||||
install_models: List[str]=None
|
||||
remove_models: List[str]=None
|
||||
purge_deleted_models: bool=False,
|
||||
install_cn_models: List[str] = None,
|
||||
remove_cn_models: List[str] = None,
|
||||
scan_directory: Path=None,
|
||||
autoscan_on_startup: bool=False,
|
||||
import_model_paths: str=None,
|
||||
|
||||
class AddModelApplication(npyscreen.NPSAppManaged):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.user_cancelled = False
|
||||
self.user_selections = Namespace(
|
||||
install_models=None,
|
||||
remove_models=None,
|
||||
purge_deleted_models=False,
|
||||
install_cn_models = None,
|
||||
remove_cn_models = None,
|
||||
control_net_map = None,
|
||||
scan_directory=None,
|
||||
autoscan_on_startup=None,
|
||||
import_model_paths=None,
|
||||
)
|
||||
self.user_selections = UserSelections()
|
||||
|
||||
def onStart(self):
|
||||
npyscreen.setTheme(npyscreen.Themes.DefaultTheme)
|
||||
@ -418,15 +505,9 @@ def process_and_execute(opt: Namespace, selections: Namespace):
|
||||
directory_to_scan = selections.scan_directory
|
||||
scan_at_startup = selections.autoscan_on_startup
|
||||
potential_models_to_install = selections.import_model_paths
|
||||
print(f'selections.install_cn_models={selections.install_cn_models}')
|
||||
print(f'selections.remove_cn_models={selections.remove_cn_models}')
|
||||
print(f'selections.cn_model_map={selections.control_net_map}')
|
||||
install_requested_models(
|
||||
install_initial_models=models_to_install,
|
||||
remove_models=models_to_remove,
|
||||
install_cn_models=selections.install_cn_models,
|
||||
remove_cn_models=selections.remove_cn_models,
|
||||
cn_model_map=selections.control_net_map,
|
||||
diffusers = ModelInstallList(models_to_install, models_to_remove),
|
||||
controlnet = ModelInstallList(selections.install_cn_models, selections.remove_cn_models),
|
||||
scan_directory=Path(directory_to_scan) if directory_to_scan else None,
|
||||
external_models=potential_models_to_install,
|
||||
scan_at_startup=scan_at_startup,
|
||||
|
||||
@ -94,13 +94,7 @@ class FloatTitleSlider(npyscreen.TitleText):
|
||||
_entry_type = FloatSlider
|
||||
|
||||
|
||||
class MultiSelectColumns(npyscreen.MultiSelect):
|
||||
def __init__(self, screen, columns: int = 1, values: list = [], **keywords):
|
||||
self.columns = columns
|
||||
self.value_cnt = len(values)
|
||||
self.rows = math.ceil(self.value_cnt / self.columns)
|
||||
super().__init__(screen, values=values, **keywords)
|
||||
|
||||
class SelectColumnBase():
|
||||
def make_contained_widgets(self):
|
||||
self._my_widgets = []
|
||||
column_width = self.width // self.columns
|
||||
@ -150,6 +144,32 @@ class MultiSelectColumns(npyscreen.MultiSelect):
|
||||
def h_cursor_line_right(self, ch):
|
||||
super().h_cursor_line_down(ch)
|
||||
|
||||
class MultiSelectColumns( SelectColumnBase, npyscreen.MultiSelect):
|
||||
def __init__(self, screen, columns: int = 1, values: list = [], **keywords):
|
||||
self.columns = columns
|
||||
self.value_cnt = len(values)
|
||||
self.rows = math.ceil(self.value_cnt / self.columns)
|
||||
super().__init__(screen, values=values, **keywords)
|
||||
|
||||
|
||||
class SingleSelectColumns(SelectColumnBase, npyscreen.SelectOne):
|
||||
def __init__(self, screen, columns: int = 1, values: list = [], **keywords):
|
||||
self.columns = columns
|
||||
self.value_cnt = len(values)
|
||||
self.rows = math.ceil(self.value_cnt / self.columns)
|
||||
self.on_changed = None
|
||||
super().__init__(screen, values=values, **keywords)
|
||||
|
||||
def h_select(self,ch):
|
||||
super().h_select(ch)
|
||||
if self.on_changed:
|
||||
self.on_changed(self.value)
|
||||
|
||||
def when_value_edited(self):
|
||||
self.h_select(self.cursor_line)
|
||||
|
||||
def when_cursor_moved(self):
|
||||
self.h_select(self.cursor_line)
|
||||
|
||||
class TextBox(npyscreen.MultiLineEdit):
|
||||
def update(self, clear=True):
|
||||
|
||||
Loading…
Reference in New Issue
Block a user