2.1.826

.gitignore

@@ -8,6 +8,8 @@ __pycache__
 *.backup
 *.corrupted
 sorted_styles.json
+/input
+/cache
 /language/default.json
 lena.png
 lena_result.png
@@ -16,8 +18,6 @@ config.txt
 config_modification_tutorial.txt
 user_path_config.txt
 user_path_config-deprecated.txt
-build_chb.py
-experiment.py
 /modules/*.png
 /repositories
 /venv

args_manager.py

@@ -1,33 +1,31 @@
-from fcbh.options import enable_args_parsing
-enable_args_parsing(False)
-import fcbh.cli_args as fcbh_cli
+import ldm_patched.modules.args_parser as args_parser
 
 
-fcbh_cli.parser.add_argument("--share", action='store_true', help="Set whether to share on Gradio.")
-fcbh_cli.parser.add_argument("--preset", type=str, default=None, help="Apply specified UI preset.")
+args_parser.parser.add_argument("--share", action='store_true', help="Set whether to share on Gradio.")
+args_parser.parser.add_argument("--preset", type=str, default=None, help="Apply specified UI preset.")
 
-fcbh_cli.parser.add_argument("--language", type=str, default='default',
-                             help="Translate UI using json files in [language] folder. "
+args_parser.parser.add_argument("--language", type=str, default='default',
+                                help="Translate UI using json files in [language] folder. "
                                   "For example, [--language example] will use [language/example.json] for translation.")
 
 # For example, https://github.com/lllyasviel/Fooocus/issues/849
-fcbh_cli.parser.add_argument("--enable-smart-memory", action="store_true",
-                             help="Force loading models to vram when the unload can be avoided. "
+args_parser.parser.add_argument("--disable-offload-from-vram", action="store_true",
+                                help="Force loading models to vram when the unload can be avoided. "
                                   "Some Mac users may need this.")
 
-fcbh_cli.parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None)
-fcbh_cli.parser.add_argument("--disable-image-log", action='store_true',
-                             help="Prevent writing images and logs to hard drive.")
+args_parser.parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None)
+args_parser.parser.add_argument("--disable-image-log", action='store_true',
+                                help="Prevent writing images and logs to hard drive.")
 
-fcbh_cli.parser.set_defaults(
+args_parser.parser.set_defaults(
     disable_cuda_malloc=True,
     auto_launch=True,
     port=None
 )
 
-fcbh_cli.args = fcbh_cli.parser.parse_args()
+args_parser.args = args_parser.parser.parse_args()
 
 # (Disable by default because of issues like https://github.com/lllyasviel/Fooocus/issues/724)
-fcbh_cli.args.disable_smart_memory = not fcbh_cli.args.enable_smart_memory
+args_parser.args.always_offload_from_vram = not args_parser.args.disable_offload_from_vram
 
-args = fcbh_cli.args
+args = args_parser.args

fooocus_extras/face_crop.py → extras/face_crop.py

@@ -25,11 +25,11 @@ def crop_image(img_rgb):
     global faceRestoreHelper
 
     if faceRestoreHelper is None:
-        from fooocus_extras.facexlib.utils.face_restoration_helper import FaceRestoreHelper
+        from extras.facexlib.utils.face_restoration_helper import FaceRestoreHelper
         faceRestoreHelper = FaceRestoreHelper(
             upscale_factor=1,
             model_rootpath=modules.config.path_controlnet,
-            device='cpu'  # use cpu is safer since we are out of fcbh management
+            device='cpu'  # use cpu is safer since we are out of memory management
         )
 
     faceRestoreHelper.clean_all()

fooocus_extras/facexlib/detection/__init__.py → extras/facexlib/detection/__init__.py

@@ -1,7 +1,7 @@
 import torch
 from copy import deepcopy
 
-from fooocus_extras.facexlib.utils import load_file_from_url
+from extras.facexlib.utils import load_file_from_url
 from .retinaface import RetinaFace
 
 

fooocus_extras/facexlib/detection/retinaface.py → extras/facexlib/detection/retinaface.py

@@ -6,9 +6,9 @@
 from PIL import Image
 from torchvision.models._utils import IntermediateLayerGetter as IntermediateLayerGetter
 
-from fooocus_extras.facexlib.detection.align_trans import get_reference_facial_points, warp_and_crop_face
-from fooocus_extras.facexlib.detection.retinaface_net import FPN, SSH, MobileNetV1, make_bbox_head, make_class_head, make_landmark_head
-from fooocus_extras.facexlib.detection.retinaface_utils import (PriorBox, batched_decode, batched_decode_landm, decode, decode_landm,
+from extras.facexlib.detection.align_trans import get_reference_facial_points, warp_and_crop_face
+from extras.facexlib.detection.retinaface_net import FPN, SSH, MobileNetV1, make_bbox_head, make_class_head, make_landmark_head
+from extras.facexlib.detection.retinaface_utils import (PriorBox, batched_decode, batched_decode_landm, decode, decode_landm,
                                                  py_cpu_nms)
 
 

fooocus_extras/facexlib/parsing/__init__.py → extras/facexlib/parsing/__init__.py

@@ -1,6 +1,6 @@
 import torch
 
-from fooocus_extras.facexlib.utils import load_file_from_url
+from extras.facexlib.utils import load_file_from_url
 from .bisenet import BiSeNet
 from .parsenet import ParseNet
 

fooocus_extras/facexlib/utils/face_restoration_helper.py → extras/facexlib/utils/face_restoration_helper.py

@@ -4,9 +4,9 @@
 import torch
 from torchvision.transforms.functional import normalize
 
-from fooocus_extras.facexlib.detection import init_detection_model
-from fooocus_extras.facexlib.parsing import init_parsing_model
-from fooocus_extras.facexlib.utils.misc import img2tensor, imwrite
+from extras.facexlib.detection import init_detection_model
+from extras.facexlib.parsing import init_parsing_model
+from extras.facexlib.utils.misc import img2tensor, imwrite
 
 
 def get_largest_face(det_faces, h, w):

fooocus_extras/facexlib/utils/face_utils.py → extras/facexlib/utils/face_utils.py

@@ -211,9 +211,9 @@ def paste_face_back(img, face, inverse_affine):
 if __name__ == '__main__':
     import os
 
-    from fooocus_extras.facexlib.detection import init_detection_model
-    from fooocus_extras.facexlib.utils.face_restoration_helper import get_largest_face
-    from fooocus_extras.facexlib.visualization import visualize_detection
+    from extras.facexlib.detection import init_detection_model
+    from extras.facexlib.utils.face_restoration_helper import get_largest_face
+    from extras.facexlib.visualization import visualize_detection
 
     img_path = '/home/wxt/datasets/ffhq/ffhq_wild/00009.png'
     img_name = os.splitext(os.path.basename(img_path))[0]

fooocus_extras/ip_adapter.py → extras/ip_adapter.py

@@ -1,12 +1,12 @@
 import torch
-import fcbh.clip_vision
+import ldm_patched.modules.clip_vision
 import safetensors.torch as sf
-import fcbh.model_management as model_management
+import ldm_patched.modules.model_management as model_management
 import contextlib
-import fcbh.ldm.modules.attention as attention
+import ldm_patched.ldm.modules.attention as attention
 
-from fooocus_extras.resampler import Resampler
-from fcbh.model_patcher import ModelPatcher
+from extras.resampler import Resampler
+from ldm_patched.modules.model_patcher import ModelPatcher
 from modules.core import numpy_to_pytorch
 
 
@@ -82,7 +82,7 @@ def __init__(self, state_dict, plus, cross_attention_dim=768, clip_embeddings_di
         self.ip_layers.load_state_dict_ordered(state_dict["ip_adapter"])
 
 
-clip_vision: fcbh.clip_vision.ClipVisionModel = None
+clip_vision: ldm_patched.modules.clip_vision.ClipVisionModel = None
 ip_negative: torch.Tensor = None
 ip_adapters: dict = {}
 
@@ -91,7 +91,7 @@ def load_ip_adapter(clip_vision_path, ip_negative_path, ip_adapter_path):
     global clip_vision, ip_negative, ip_adapters
 
     if clip_vision is None and isinstance(clip_vision_path, str):
-        clip_vision = fcbh.clip_vision.load(clip_vision_path)
+        clip_vision = ldm_patched.modules.clip_vision.load(clip_vision_path)
 
     if ip_negative is None and isinstance(ip_negative_path, str):
         ip_negative = sf.load_file(ip_negative_path)['data']
@@ -165,33 +165,28 @@ def preprocess(img, ip_adapter_path):
     global ip_adapters
     entry = ip_adapters[ip_adapter_path]
 
-    fcbh.model_management.load_model_gpu(clip_vision.patcher)
+    ldm_patched.modules.model_management.load_model_gpu(clip_vision.patcher)
     pixel_values = clip_preprocess(numpy_to_pytorch(img).to(clip_vision.load_device))
 
     if clip_vision.dtype != torch.float32:
         precision_scope = torch.autocast
     else:
         precision_scope = lambda a, b: contextlib.nullcontext(a)
 
-    with precision_scope(fcbh.model_management.get_autocast_device(clip_vision.load_device), torch.float32):
-        outputs = clip_vision.model(pixel_values=pixel_values, output_hidden_states=True)
+    with precision_scope(ldm_patched.modules.model_management.get_autocast_device(clip_vision.load_device), torch.float32):
+        outputs = clip_vision.model(pixel_values=pixel_values, intermediate_output=-2)
 
     ip_adapter = entry['ip_adapter']
     ip_layers = entry['ip_layers']
     image_proj_model = entry['image_proj_model']
     ip_unconds = entry['ip_unconds']
 
-    if ip_adapter.plus:
-        cond = outputs.hidden_states[-2]
-    else:
-        cond = outputs.image_embeds
-
-    cond = cond.to(device=ip_adapter.load_device, dtype=ip_adapter.dtype)
+    cond = outputs[1].to(device=ip_adapter.load_device, dtype=ip_adapter.dtype)
 
-    fcbh.model_management.load_model_gpu(image_proj_model)
+    ldm_patched.modules.model_management.load_model_gpu(image_proj_model)
     cond = image_proj_model.model(cond).to(device=ip_adapter.load_device, dtype=ip_adapter.dtype)
 
-    fcbh.model_management.load_model_gpu(ip_layers)
+    ldm_patched.modules.model_management.load_model_gpu(ip_layers)
 
     if ip_unconds is None:
         uncond = ip_negative.to(device=ip_adapter.load_device, dtype=ip_adapter.dtype)

fooocus_extras/vae_interpose.py → extras/vae_interpose.py

@@ -4,9 +4,9 @@
 import torch
 import safetensors.torch as sf
 import torch.nn as nn
-import fcbh.model_management
+import ldm_patched.modules.model_management
 
-from fcbh.model_patcher import ModelPatcher
+from ldm_patched.modules.model_patcher import ModelPatcher
 from modules.config import path_vae_approx
 
 
@@ -76,17 +76,17 @@ def parse(x):
         model.eval()
         sd = sf.load_file(vae_approx_filename)
         model.load_state_dict(sd)
-        fp16 = fcbh.model_management.should_use_fp16()
+        fp16 = ldm_patched.modules.model_management.should_use_fp16()
         if fp16:
             model = model.half()
         vae_approx_model = ModelPatcher(
             model=model,
-            load_device=fcbh.model_management.get_torch_device(),
+            load_device=ldm_patched.modules.model_management.get_torch_device(),
             offload_device=torch.device('cpu')
         )
         vae_approx_model.dtype = torch.float16 if fp16 else torch.float32
 
-    fcbh.model_management.load_model_gpu(vae_approx_model)
+    ldm_patched.modules.model_management.load_model_gpu(vae_approx_model)
 
     x = x_origin.to(device=vae_approx_model.load_device, dtype=vae_approx_model.dtype)
     x = vae_approx_model.model(x).to(x_origin)

face_experiments.py

@@ -1,5 +1,5 @@
 import cv2
-import fooocus_extras.face_crop as cropper
+import extras.face_crop as cropper
 
 
 img = cv2.imread('lena.png')

fooocus_version.py

@@ -1 +1 @@
-version = '2.1.825'
+version = '2.1.826'

launch.py

@@ -5,10 +5,9 @@
 print('[System ARGV] ' + str(sys.argv))
 
 root = os.path.dirname(os.path.abspath(__file__))
-backend_path = os.path.join(root, 'backend', 'headless')
-sys.path += [root, backend_path]
-
+sys.path.append(root)
 os.chdir(root)
+
 os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
 os.environ["PYTORCH_MPS_HIGH_WATERMARK_RATIO"] = "0.0"
 os.environ["GRADIO_SERVER_PORT"] = "7865"
@@ -88,19 +87,19 @@ def download_models():
     return
 
 
-def ini_fcbh_args():
+def ini_args():
     from args_manager import args
     return args
 
 
 prepare_environment()
 build_launcher()
-args = ini_fcbh_args()
+args = ini_args()
 
 
-if args.cuda_device is not None:
-    os.environ['CUDA_VISIBLE_DEVICES'] = str(args.cuda_device)
-    print("Set device to:", args.cuda_device)
+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)
 
 
 download_models()