feat: support download of huggingface files from a mirror website (#2637)

* fix: load image number from preset (#2611)

* fix: add default_image_number to preset handling

* fix: use minimum image number of preset and config to prevent UI overflow

* fix: use correct base dimensions for outpaint mask padding (#2612)

* fix: add Civitai compatibility for LoRAs in a1111 metadata scheme by switching schema (#2615)

* feat: update sha256 generation functions

29be1da7cf/modules/hashes.py

* feat: add compatibility for LoRAs in a1111 metadata scheme

* feat: add backwards compatibility

* refactor: extract remove_special_loras

* fix: correctly apply LoRA weight for legacy schema

* docs: bump version number to 2.3.1, add changelog (#2616)

* feat:support download huggingface files from a  mirror site

---------

Co-authored-by: Manuel Schmid <9307310+mashb1t@users.noreply.github.com>

docker.md

@@ -54,6 +54,7 @@ Docker specified environments are there. They are used by 'entrypoint.sh'
 |CMDARGS|Arguments for [entry_with_update.py](entry_with_update.py) which is called by [entrypoint.sh](entrypoint.sh)|
 |config_path|'config.txt' location|
 |config_example_path|'config_modification_tutorial.txt' location|
+|HF_MIRROR| huggingface mirror site domain| 
 
 You can also use the same json key names and values explained in the 'config_modification_tutorial.txt' as the environments.
 See examples in the [docker-compose.yml](docker-compose.yml)

fooocus_version.py

@@ -1 +1 @@
-version = '2.3.0'
+version = '2.3.1'

launch.py

@@ -80,6 +80,10 @@ if args.gpu_device_id is not None:
     os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_device_id)
     print("Set device to:", args.gpu_device_id)
 
+if args.hf_mirror is not None : 
+    os.environ['HF_MIRROR'] = str(args.hf_mirror)
+    print("Set hf_mirror to:", args.hf_mirror)
+
 from modules import config
 
 os.environ['GRADIO_TEMP_DIR'] = config.temp_path

ldm_patched/modules/args_parser.py

@@ -37,6 +37,7 @@ parser.add_argument("--listen", type=str, default="127.0.0.1", metavar="IP", nar
 parser.add_argument("--port", type=int, default=8188)
 parser.add_argument("--disable-header-check", type=str, default=None, metavar="ORIGIN", nargs="?", const="*")
 parser.add_argument("--web-upload-size", type=float, default=100)
+parser.add_argument("--hf-mirror", type=str, default=None)
 
 parser.add_argument("--external-working-path", type=str, default=None, metavar="PATH", nargs='+', action='append')
 parser.add_argument("--output-path", type=str, default=None)

modules/async_worker.py

@@ -614,12 +614,12 @@ def worker():
 
                 H, W, C = inpaint_image.shape
                 if 'left' in outpaint_selections:
-                    inpaint_image = np.pad(inpaint_image, [[0, 0], [int(H * 0.3), 0], [0, 0]], mode='edge')
+                    inpaint_image = np.pad(inpaint_image, [[0, 0], [int(W * 0.3), 0], [0, 0]], mode='edge')
-                    inpaint_mask = np.pad(inpaint_mask, [[0, 0], [int(H * 0.3), 0]], mode='constant',
+                    inpaint_mask = np.pad(inpaint_mask, [[0, 0], [int(W * 0.3), 0]], mode='constant',
                                           constant_values=255)
                 if 'right' in outpaint_selections:
-                    inpaint_image = np.pad(inpaint_image, [[0, 0], [0, int(H * 0.3)], [0, 0]], mode='edge')
+                    inpaint_image = np.pad(inpaint_image, [[0, 0], [0, int(W * 0.3)], [0, 0]], mode='edge')
-                    inpaint_mask = np.pad(inpaint_mask, [[0, 0], [0, int(H * 0.3)]], mode='constant',
+                    inpaint_mask = np.pad(inpaint_mask, [[0, 0], [0, int(W * 0.3)]], mode='constant',
                                           constant_values=255)
 
                 inpaint_image = np.ascontiguousarray(inpaint_image.copy())

modules/config.py

@@ -485,6 +485,7 @@ possible_preset_keys = {
     "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",
@@ -538,6 +539,7 @@ 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_paths, extensions=None, name_filter=None):

modules/meta_parser.py

@@ -1,5 +1,4 @@
 import json
-import os
 import re
 from abc import ABC, abstractmethod
 from pathlib import Path
@@ -12,7 +11,7 @@ import modules.config
 import modules.sdxl_styles
 from modules.flags import MetadataScheme, Performance, Steps
 from modules.flags import SAMPLERS, CIVITAI_NO_KARRAS
-from modules.util import quote, unquote, extract_styles_from_prompt, is_json, get_file_from_folder_list, calculate_sha256
+from modules.util import quote, unquote, extract_styles_from_prompt, is_json, get_file_from_folder_list, sha256
 
 re_param_code = r'\s*(\w[\w \-/]+):\s*("(?:\\.|[^\\"])+"|[^,]*)(?:,|$)'
 re_param = re.compile(re_param_code)
@@ -27,8 +26,9 @@ def load_parameter_button_click(raw_metadata: dict | str, is_generating: bool):
         loaded_parameter_dict = json.loads(raw_metadata)
     assert isinstance(loaded_parameter_dict, dict)
 
-    results = [len(loaded_parameter_dict) > 0, 1]
+    results = [len(loaded_parameter_dict) > 0]
 
+    get_image_number('image_number', 'Image Number', loaded_parameter_dict, results)
     get_str('prompt', 'Prompt', loaded_parameter_dict, results)
     get_str('negative_prompt', 'Negative Prompt', loaded_parameter_dict, results)
     get_list('styles', 'Styles', loaded_parameter_dict, results)
@@ -92,13 +92,25 @@ def get_float(key: str, fallback: str | None, source_dict: dict, results: list,
         results.append(gr.update())
 
 
+def get_image_number(key: str, fallback: str | None, source_dict: dict, results: list, default=None):
+    try:
+        h = source_dict.get(key, source_dict.get(fallback, default))
+        assert h is not None
+        h = int(h)
+        h = min(h, modules.config.default_max_image_number)
+        results.append(h)
+    except:
+        results.append(1)
+
+
 def get_steps(key: str, fallback: str | None, source_dict: dict, results: list, default=None):
     try:
         h = source_dict.get(key, source_dict.get(fallback, default))
         assert h is not None
         h = int(h)
         # if not in steps or in steps and performance is not the same
-        if h not in iter(Steps) or Steps(h).name.casefold() != source_dict.get('performance', '').replace(' ', '_').casefold():
+        if h not in iter(Steps) or Steps(h).name.casefold() != source_dict.get('performance', '').replace(' ',
+                                                                                                          '_').casefold():
             results.append(h)
             return
         results.append(-1)
@@ -192,7 +204,8 @@ def get_lora(key: str, fallback: str | None, source_dict: dict, results: list):
 def get_sha256(filepath):
     global hash_cache
     if filepath not in hash_cache:
-        hash_cache[filepath] = calculate_sha256(filepath)
+        # is_safetensors = os.path.splitext(filepath)[1].lower() == '.safetensors'
+        hash_cache[filepath] = sha256(filepath)
 
     return hash_cache[filepath]
 
@@ -219,8 +232,9 @@ def parse_meta_from_preset(preset_content):
                 height = height[:height.index(" ")]
             preset_prepared[meta_key] = (width, height)
         else:
-            preset_prepared[meta_key] = items[settings_key] if settings_key in items and items[settings_key] is not None else getattr(modules.config, settings_key)
+            preset_prepared[meta_key] = items[settings_key] if settings_key in items and items[
-        
+                settings_key] is not None else getattr(modules.config, settings_key)
+
         if settings_key == "default_styles" or settings_key == "default_aspect_ratio":
             preset_prepared[meta_key] = str(preset_prepared[meta_key])
 
@@ -276,6 +290,12 @@ class MetadataParser(ABC):
                 lora_hash = get_sha256(lora_path)
                 self.loras.append((Path(lora_name).stem, lora_weight, lora_hash))
 
+    @staticmethod
+    def remove_special_loras(lora_filenames):
+        for lora_to_remove in modules.config.loras_metadata_remove:
+            if lora_to_remove in lora_filenames:
+                lora_filenames.remove(lora_to_remove)
+
 
 class A1111MetadataParser(MetadataParser):
     def get_scheme(self) -> MetadataScheme:
@@ -385,12 +405,19 @@ class A1111MetadataParser(MetadataParser):
                         data[key] = filename
                         break
 
-        if 'lora_hashes' in data and data['lora_hashes'] != '':
+        lora_data = ''
+        if 'lora_weights' in data and data['lora_weights'] != '':
+            lora_data = data['lora_weights']
+        elif 'lora_hashes' in data and data['lora_hashes'] != '' and data['lora_hashes'].split(', ')[0].count(':') == 2:
+            lora_data = data['lora_hashes']
+
+        if lora_data != '':
             lora_filenames = modules.config.lora_filenames.copy()
-            if modules.config.sdxl_lcm_lora in lora_filenames:
+            self.remove_special_loras(lora_filenames)
-                lora_filenames.remove(modules.config.sdxl_lcm_lora)
+            for li, lora in enumerate(lora_data.split(', ')):
-            for li, lora in enumerate(data['lora_hashes'].split(', ')):
+                lora_split = lora.split(': ')
-                lora_name, lora_hash, lora_weight = lora.split(': ')
+                lora_name = lora_split[0]
+                lora_weight = lora_split[2] if len(lora_split) == 3 else lora_split[1]
                 for filename in lora_filenames:
                     path = Path(filename)
                     if lora_name == path.stem:
@@ -441,11 +468,15 @@ class A1111MetadataParser(MetadataParser):
 
         if len(self.loras) > 0:
             lora_hashes = []
+            lora_weights = []
             for index, (lora_name, lora_weight, lora_hash) in enumerate(self.loras):
                 # workaround for Fooocus not knowing LoRA name in LoRA metadata
-                lora_hashes.append(f'{lora_name}: {lora_hash}: {lora_weight}')
+                lora_hashes.append(f'{lora_name}: {lora_hash}')
+                lora_weights.append(f'{lora_name}: {lora_weight}')
             lora_hashes_string = ', '.join(lora_hashes)
+            lora_weights_string = ', '.join(lora_weights)
             generation_params[self.fooocus_to_a1111['lora_hashes']] = lora_hashes_string
+            generation_params[self.fooocus_to_a1111['lora_weights']] = lora_weights_string
 
         generation_params[self.fooocus_to_a1111['version']] = data['version']
 
@@ -468,9 +499,7 @@ class FooocusMetadataParser(MetadataParser):
     def parse_json(self, metadata: dict) -> dict:
         model_filenames = modules.config.model_filenames.copy()
         lora_filenames = modules.config.lora_filenames.copy()
-        if modules.config.sdxl_lcm_lora in lora_filenames:
+        self.remove_special_loras(lora_filenames)
-            lora_filenames.remove(modules.config.sdxl_lcm_lora)
-
         for key, value in metadata.items():
             if value in ['', 'None']:
                 continue

modules/model_loader.py

@@ -14,6 +14,8 @@ def load_file_from_url(
 
     Returns the path to the downloaded file.
     """
+    domain = os.environ.get("HF_MIRROR", "https://huggingface.co").rstrip('/')
+    url = str.replace(url, "https://huggingface.co", domain, 1)
     os.makedirs(model_dir, exist_ok=True)
     if not file_name:
         parts = urlparse(url)

modules/util.py

@@ -7,9 +7,9 @@ import math
 import os
 import cv2
 import json
+import hashlib
 
 from PIL import Image
-from hashlib import sha256
 
 import modules.sdxl_styles
 
@@ -182,16 +182,44 @@ def get_files_from_folder(folder_path, extensions=None, name_filter=None):
     return filenames
 
 
-def calculate_sha256(filename, length=HASH_SHA256_LENGTH) -> str:
+def sha256(filename, use_addnet_hash=False, length=HASH_SHA256_LENGTH):
-    hash_sha256 = sha256()
+    print(f"Calculating sha256 for {filename}: ", end='')
+    if use_addnet_hash:
+        with open(filename, "rb") as file:
+            sha256_value = addnet_hash_safetensors(file)
+    else:
+        sha256_value = calculate_sha256(filename)
+    print(f"{sha256_value}")
+
+    return sha256_value[:length] if length is not None else sha256_value
+
+
+def addnet_hash_safetensors(b):
+    """kohya-ss hash for safetensors from https://github.com/kohya-ss/sd-scripts/blob/main/library/train_util.py"""
+    hash_sha256 = hashlib.sha256()
+    blksize = 1024 * 1024
+
+    b.seek(0)
+    header = b.read(8)
+    n = int.from_bytes(header, "little")
+
+    offset = n + 8
+    b.seek(offset)
+    for chunk in iter(lambda: b.read(blksize), b""):
+        hash_sha256.update(chunk)
+
+    return hash_sha256.hexdigest()
+
+
+def calculate_sha256(filename) -> str:
+    hash_sha256 = hashlib.sha256()
     blksize = 1024 * 1024
 
     with open(filename, "rb") as f:
         for chunk in iter(lambda: f.read(blksize), b""):
             hash_sha256.update(chunk)
 
-    res = hash_sha256.hexdigest()
+    return hash_sha256.hexdigest()
-    return res[:length] if length else res
 
 
 def quote(text):

readme.md

@@ -368,6 +368,7 @@ A safer way is just to try "run_anime.bat" or "run_realistic.bat" - they should
 entry_with_update.py  [-h] [--listen [IP]] [--port PORT]
                       [--disable-header-check [ORIGIN]]
                       [--web-upload-size WEB_UPLOAD_SIZE]
+                      [--hf-mirror HF_MIRROR]
                       [--external-working-path PATH [PATH ...]]
                       [--output-path OUTPUT_PATH] [--temp-path TEMP_PATH]
                       [--cache-path CACHE_PATH] [--in-browser]

update_log.md

@@ -1,3 +1,10 @@
+# [2.3.1](https://github.com/lllyasviel/Fooocus/releases/tag/2.3.1)
+
+* Remove positive prompt from anime prefix to not reset prompt after switching presets
+* Fix image number being reset to 1 when switching preset, now doesn't reset anymore
+* Fix outpainting dimension calculation when extending left/right
+* Fix LoRA compatibility for LoRAs in a1111 metadata scheme
+
 # [2.3.0](https://github.com/lllyasviel/Fooocus/releases/tag/2.3.0)
 
 * Add performance "lightning" (based on [SDXL-Lightning 4 step LoRA](https://huggingface.co/ByteDance/SDXL-Lightning/blob/main/sdxl_lightning_4step_lora.safetensors))