Merge branch 'main_upstream' into feature/add-nsfw-filter

# Conflicts: # modules/advanced_parameters.py # modules/async_worker.py # modules/config.py # webui.py
2026-08-16 13:13:16 +02:00 · 2024-05-17 23:10:12 +02:00
parent c4813810e3 6308fb8b54
commit 270ce71dbe
57 changed files with 2566 additions and 734 deletions
@@ -3,15 +3,26 @@ import json
 import math
 import numbers
 import args_manager
+import tempfile
 import modules.flags
 import modules.sdxl_styles

 from modules.model_loader import load_file_from_url
-from modules.util import get_files_from_folder
+from modules.util import get_files_from_folder, makedirs_with_log
+from modules.flags import OutputFormat, Performance, MetadataScheme


-config_path = os.path.abspath("./config.txt")
-config_example_path = os.path.abspath("config_modification_tutorial.txt")
+def get_config_path(key, default_value):
+    env = os.getenv(key)
+    if env is not None and isinstance(env, str):
+        print(f"Environment: {key} = {env}")
+        return env
+    else:
+        return os.path.abspath(default_value)
+
+
+config_path = get_config_path('config_path', "./config.txt")
+config_example_path = get_config_path('config_example_path', "config_modification_tutorial.txt")
 config_dict = {}
 always_save_keys = []
 visited_keys = []
@@ -86,23 +97,50 @@ def try_load_deprecated_user_path_config():

 try_load_deprecated_user_path_config()

+
+def get_presets():
+    preset_folder = 'presets'
+    presets = ['initial']
+    if not os.path.exists(preset_folder):
+        print('No presets found.')
+        return presets
+
+    return presets + [f[:f.index('.json')] for f in os.listdir(preset_folder) if f.endswith('.json')]
+
+
+def try_get_preset_content(preset):
+    if isinstance(preset, str):
+        preset_path = os.path.abspath(f'./presets/{preset}.json')
+        try:
+            if os.path.exists(preset_path):
+                with open(preset_path, "r", encoding="utf-8") as json_file:
+                    json_content = json.load(json_file)
+                    print(f'Loaded preset: {preset_path}')
+                    return json_content
+            else:
+                raise FileNotFoundError
+        except Exception as e:
+            print(f'Load preset [{preset_path}] failed')
+            print(e)
+    return {}
+
+available_presets = get_presets()
 preset = args_manager.args.preset
+config_dict.update(try_get_preset_content(preset))

-if isinstance(preset, str):
-    preset_path = os.path.abspath(f'./presets/{preset}.json')
-    try:
-        if os.path.exists(preset_path):
-            with open(preset_path, "r", encoding="utf-8") as json_file:
-                config_dict.update(json.load(json_file))
-                print(f'Loaded preset: {preset_path}')
-        else:
-            raise FileNotFoundError
-    except Exception as e:
-        print(f'Load preset [{preset_path}] failed')
-        print(e)
+def get_path_output() -> str:
+    """
+    Checking output path argument and overriding default path.
+    """
+    global config_dict
+    path_output = get_dir_or_set_default('path_outputs', '../outputs/', make_directory=True)
+    if args_manager.args.output_path:
+        print(f'Overriding config value path_outputs with {args_manager.args.output_path}')
+        config_dict['path_outputs'] = path_output = args_manager.args.output_path
+    return path_output


-def get_dir_or_set_default(key, default_value):
+def get_dir_or_set_default(key, default_value, as_array=False, make_directory=False):
    global config_dict, visited_keys, always_save_keys

    if key not in visited_keys:
@@ -111,20 +149,44 @@ def get_dir_or_set_default(key, default_value):
    if key not in always_save_keys:
        always_save_keys.append(key)

-    v = config_dict.get(key, None)
-    if isinstance(v, str) and os.path.exists(v) and os.path.isdir(v):
-        return v
+    v = os.getenv(key)
+    if v is not None:
+        print(f"Environment: {key} = {v}")
+        config_dict[key] = v
+    else:
+        v = config_dict.get(key, None)
+
+    if isinstance(v, str):
+        if make_directory:
+            makedirs_with_log(v)
+        if os.path.exists(v) and os.path.isdir(v):
+            return v if not as_array else [v]
+    elif isinstance(v, list):
+        if make_directory:
+            for d in v:
+                makedirs_with_log(d)
+        if all([os.path.exists(d) and os.path.isdir(d) for d in v]):
+            return v
+
+    if v is not None:
+        print(f'Failed to load config key: {json.dumps({key:v})} is invalid or does not exist; will use {json.dumps({key:default_value})} instead.')
+    if isinstance(default_value, list):
+        dp = []
+        for path in default_value:
+            abs_path = os.path.abspath(os.path.join(os.path.dirname(__file__), path))
+            dp.append(abs_path)
+            os.makedirs(abs_path, exist_ok=True)
    else:
-        if v is not None:
-            print(f'Failed to load config key: {json.dumps({key:v})} is invalid or does not exist; will use {json.dumps({key:default_value})} instead.')
        dp = os.path.abspath(os.path.join(os.path.dirname(__file__), default_value))
        os.makedirs(dp, exist_ok=True)
-        config_dict[key] = dp
-        return dp
+        if as_array:
+            dp = [dp]
+    config_dict[key] = dp
+    return dp


-path_checkpoints = get_dir_or_set_default('path_checkpoints', '../models/checkpoints/')
-path_loras = get_dir_or_set_default('path_loras', '../models/loras/')
+paths_checkpoints = get_dir_or_set_default('path_checkpoints', ['../models/checkpoints/'], True)
+paths_loras = get_dir_or_set_default('path_loras', ['../models/loras/'], True)
 path_embeddings = get_dir_or_set_default('path_embeddings', '../models/embeddings/')
 path_vae_approx = get_dir_or_set_default('path_vae_approx', '../models/vae_approx/')
 path_upscale_models = get_dir_or_set_default('path_upscale_models', '../models/upscale_models/')
@@ -132,8 +194,9 @@ path_inpaint = get_dir_or_set_default('path_inpaint', '../models/inpaint/')
 path_controlnet = get_dir_or_set_default('path_controlnet', '../models/controlnet/')
 path_clip_vision = get_dir_or_set_default('path_clip_vision', '../models/clip_vision/')
 path_fooocus_expansion = get_dir_or_set_default('path_fooocus_expansion', '../models/prompt_expansion/fooocus_expansion')
-path_outputs = get_dir_or_set_default('path_outputs', '../outputs/')
+path_wildcards = get_dir_or_set_default('path_wildcards', '../wildcards/')
 path_safety_checker_models = get_dir_or_set_default('path_safety_checker_models', '../models/safety_checker_models/')
+path_outputs = get_path_output()


 def get_config_item_or_set_default(key, default_value, validator, disable_empty_as_none=False):
@@ -142,6 +205,11 @@ def get_config_item_or_set_default(key, default_value, validator, disable_empty_
    if key not in visited_keys:
        visited_keys.append(key)
    
+    v = os.getenv(key)
+    if v is not None:
+        print(f"Environment: {key} = {v}")
+        config_dict[key] = v
+
    if key not in config_dict:
        config_dict[key] = default_value
        return default_value
@@ -159,7 +227,37 @@ def get_config_item_or_set_default(key, default_value, validator, disable_empty_
        return default_value


-default_base_model_name = get_config_item_or_set_default(
+def init_temp_path(path: str | None, default_path: str) -> str:
+    if args_manager.args.temp_path:
+        path = args_manager.args.temp_path
+
+    if path != '' and path != default_path:
+        try:
+            if not os.path.isabs(path):
+                path = os.path.abspath(path)
+            os.makedirs(path, exist_ok=True)
+            print(f'Using temp path {path}')
+            return path
+        except Exception as e:
+            print(f'Could not create temp path {path}. Reason: {e}')
+            print(f'Using default temp path {default_path} instead.')
+
+    os.makedirs(default_path, exist_ok=True)
+    return default_path
+
+
+default_temp_path = os.path.join(tempfile.gettempdir(), 'fooocus')
+temp_path = init_temp_path(get_config_item_or_set_default(
+    key='temp_path',
+    default_value=default_temp_path,
+    validator=lambda x: isinstance(x, str),
+), default_temp_path)
+temp_path_cleanup_on_launch = get_config_item_or_set_default(
+    key='temp_path_cleanup_on_launch',
+    default_value=True,
+    validator=lambda x: isinstance(x, bool)
+)
+default_base_model_name = default_model = get_config_item_or_set_default(
    key='default_model',
    default_value='model.safetensors',
    validator=lambda x: isinstance(x, str)
@@ -169,7 +267,7 @@ previous_default_models = get_config_item_or_set_default(
    default_value=[],
    validator=lambda x: isinstance(x, list) and all(isinstance(k, str) for k in x)
 )
-default_refiner_model_name = get_config_item_or_set_default(
+default_refiner_model_name = default_refiner = get_config_item_or_set_default(
    key='default_refiner',
    default_value='None',
    validator=lambda x: isinstance(x, str)
@@ -179,31 +277,55 @@ default_refiner_switch = get_config_item_or_set_default(
    default_value=0.8,
    validator=lambda x: isinstance(x, numbers.Number) and 0 <= x <= 1
 )
+default_loras_min_weight = get_config_item_or_set_default(
+    key='default_loras_min_weight',
+    default_value=-2,
+    validator=lambda x: isinstance(x, numbers.Number) and -10 <= x <= 10
+)
+default_loras_max_weight = get_config_item_or_set_default(
+    key='default_loras_max_weight',
+    default_value=2,
+    validator=lambda x: isinstance(x, numbers.Number) and -10 <= x <= 10
+)
 default_loras = get_config_item_or_set_default(
    key='default_loras',
    default_value=[
        [
+            True,
            "None",
            1.0
        ],
        [
+            True,
            "None",
            1.0
        ],
        [
+            True,
            "None",
            1.0
        ],
        [
+            True,
            "None",
            1.0
        ],
        [
+            True,
            "None",
            1.0
        ]
    ],
-    validator=lambda x: isinstance(x, list) and all(len(y) == 2 and isinstance(y[0], str) and isinstance(y[1], numbers.Number) for y in x)
+    validator=lambda x: isinstance(x, list) and all(
+        len(y) == 3 and isinstance(y[0], bool) and isinstance(y[1], str) and isinstance(y[2], numbers.Number)
+        or len(y) == 2 and isinstance(y[0], str) and isinstance(y[1], numbers.Number)
+        for y in x)
+)
+default_loras = [(y[0], y[1], y[2]) if len(y) == 3 else (True, y[0], y[1]) for y in default_loras]
+default_max_lora_number = get_config_item_or_set_default(
+    key='default_max_lora_number',
+    default_value=len(default_loras) if isinstance(default_loras, list) and len(default_loras) > 0 else 5,
+    validator=lambda x: isinstance(x, int) and x >= 1
 )
 default_cfg_scale = get_config_item_or_set_default(
    key='default_cfg_scale',
@@ -248,8 +370,8 @@ default_prompt = get_config_item_or_set_default(
 )
 default_performance = get_config_item_or_set_default(
    key='default_performance',
-    default_value='Speed',
-    validator=lambda x: x in modules.flags.performance_selections
+    default_value=Performance.SPEED.value,
+    validator=lambda x: x in Performance.list()
 )
 default_advanced_checkbox = get_config_item_or_set_default(
    key='default_advanced_checkbox',
@@ -261,6 +383,11 @@ default_max_image_number = get_config_item_or_set_default(
    default_value=32,
    validator=lambda x: isinstance(x, int) and x >= 1
 )
+default_output_format = get_config_item_or_set_default(
+    key='default_output_format',
+    default_value='png',
+    validator=lambda x: x in OutputFormat.list()
+)
 default_image_number = get_config_item_or_set_default(
    key='default_image_number',
    default_value=2,
@@ -324,36 +451,56 @@ example_inpaint_prompts = get_config_item_or_set_default(
    ],
    validator=lambda x: isinstance(x, list) and all(isinstance(v, str) for v in x)
 )
-
-example_inpaint_prompts = [[x] for x in example_inpaint_prompts]
-
+default_save_metadata_to_images = get_config_item_or_set_default(
+    key='default_save_metadata_to_images',
+    default_value=False,
+    validator=lambda x: isinstance(x, bool)
+)
+default_metadata_scheme = get_config_item_or_set_default(
+    key='default_metadata_scheme',
+    default_value=MetadataScheme.FOOOCUS.value,
+    validator=lambda x: x in [y[1] for y in modules.flags.metadata_scheme if y[1] == x]
+)
+metadata_created_by = get_config_item_or_set_default(
+    key='metadata_created_by',
+    default_value='',
+    validator=lambda x: isinstance(x, str)
+)
 default_black_out_nsfw = get_config_item_or_set_default(
    key='default_black_out_nsfw',
    default_value=False,
    validator=lambda x: isinstance(x, bool)
 )

-config_dict["default_loras"] = default_loras = default_loras[:5] + [['None', 1.0] for _ in range(5 - len(default_loras))]
+example_inpaint_prompts = [[x] for x in example_inpaint_prompts]

-possible_preset_keys = [
-    "default_model",
-    "default_refiner",
-    "default_refiner_switch",
-    "default_loras",
-    "default_cfg_scale",
-    "default_sample_sharpness",
-    "default_sampler",
-    "default_scheduler",
-    "default_performance",
-    "default_prompt",
-    "default_prompt_negative",
-    "default_styles",
-    "default_aspect_ratio",
-    "checkpoint_downloads",
-    "embeddings_downloads",
-    "lora_downloads",
-]
+config_dict["default_loras"] = default_loras = default_loras[:default_max_lora_number] + [[True, 'None', 1.0] for _ in range(default_max_lora_number - len(default_loras))]

+# mapping config to meta parameter 
+possible_preset_keys = {
+    "default_model": "base_model",
+    "default_refiner": "refiner_model",
+    "default_refiner_switch": "refiner_switch",
+    "previous_default_models": "previous_default_models",
+    "default_loras_min_weight": "default_loras_min_weight",
+    "default_loras_max_weight": "default_loras_max_weight",
+    "default_loras": "<processed>",
+    "default_cfg_scale": "guidance_scale",
+    "default_sample_sharpness": "sharpness",
+    "default_sampler": "sampler",
+    "default_scheduler": "scheduler",
+    "default_overwrite_step": "steps",
+    "default_performance": "performance",
+    "default_image_number": "image_number",
+    "default_prompt": "prompt",
+    "default_prompt_negative": "negative_prompt",
+    "default_styles": "styles",
+    "default_aspect_ratio": "resolution",
+    "default_save_metadata_to_images": "default_save_metadata_to_images",
+    "checkpoint_downloads": "checkpoint_downloads",
+    "embeddings_downloads": "embeddings_downloads",
+    "lora_downloads": "lora_downloads"
+}

 REWRITE_PRESET = False

@@ -392,21 +539,30 @@ with open(config_example_path, "w", encoding="utf-8") as json_file:
                      'and there is no "," before the last "}". \n\n\n')
    json.dump({k: config_dict[k] for k in visited_keys}, json_file, indent=4)

-
-os.makedirs(path_outputs, exist_ok=True)
-
 model_filenames = []
 lora_filenames = []
+wildcard_filenames = []
+
+sdxl_lcm_lora = 'sdxl_lcm_lora.safetensors'
+sdxl_lightning_lora = 'sdxl_lightning_4step_lora.safetensors'
+loras_metadata_remove = [sdxl_lcm_lora, sdxl_lightning_lora]


-def get_model_filenames(folder_path, name_filter=None):
-    return get_files_from_folder(folder_path, ['.pth', '.ckpt', '.bin', '.safetensors', '.fooocus.patch'], name_filter)
+def get_model_filenames(folder_paths, extensions=None, name_filter=None):
+    if extensions is None:
+        extensions = ['.pth', '.ckpt', '.bin', '.safetensors', '.fooocus.patch']
+    files = []
+    for folder in folder_paths:
+        files += get_files_from_folder(folder, extensions, name_filter)
+    return files


-def update_all_model_names():
-    global model_filenames, lora_filenames
-    model_filenames = get_model_filenames(path_checkpoints)
-    lora_filenames = get_model_filenames(path_loras)
+def update_files():
+    global model_filenames, lora_filenames, wildcard_filenames, available_presets
+    model_filenames = get_model_filenames(paths_checkpoints)
+    lora_filenames = get_model_filenames(paths_loras)
+    wildcard_filenames = get_files_from_folder(path_wildcards, ['.txt'])
+    available_presets = get_presets()
    return


@@ -451,10 +607,18 @@ def downloading_inpaint_models(v):
 def downloading_sdxl_lcm_lora():
    load_file_from_url(
        url='https://huggingface.co/lllyasviel/misc/resolve/main/sdxl_lcm_lora.safetensors',
-        model_dir=path_loras,
-        file_name='sdxl_lcm_lora.safetensors'
+        model_dir=paths_loras[0],
+        file_name=sdxl_lcm_lora
    )
-    return 'sdxl_lcm_lora.safetensors'
+    return sdxl_lcm_lora
+
+def downloading_sdxl_lightning_lora():
+    load_file_from_url(
+        url='https://huggingface.co/ByteDance/SDXL-Lightning/resolve/main/sdxl_lightning_4step_lora.safetensors',
+        model_dir=paths_loras[0],
+        file_name=sdxl_lightning_lora
+    )
+    return sdxl_lightning_lora


 def downloading_controlnet_canny():
@@ -522,4 +686,4 @@ def downloading_upscale_model():
    return os.path.join(path_upscale_models, 'fooocus_upscaler_s409985e5.bin')


-update_all_model_names()
+update_files()