rename py/BiRefNet to py/BiRefNet_v2, for avoid module name conflicts

chflame163 · Sep 26, 2024 · d6c576a · d6c576a
1 parent ab0ec27
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diff --git a/py/BiRefNet/.gitignore b/py/BiRefNet/.gitignore
diff --git a/py/BiRefNet/LICENSE → py/BiRefNet_v2/LICENSE b/py/BiRefNet/LICENSE → py/BiRefNet_v2/LICENSE
diff --git a/py/BiRefNet/README.md → py/BiRefNet_v2/README.md b/py/BiRefNet/README.md → py/BiRefNet_v2/README.md
diff --git a/py/BiRefNet/__init__.py → py/BiRefNet_v2/__init__.py b/py/BiRefNet/__init__.py → py/BiRefNet_v2/__init__.py
diff --git a/py/BiRefNet/config.py → py/BiRefNet_v2/config.py b/py/BiRefNet/config.py → py/BiRefNet_v2/config.py
diff --git a/py/BiRefNet/dataset.py → py/BiRefNet_v2/dataset.py b/py/BiRefNet/dataset.py → py/BiRefNet_v2/dataset.py
@@ -5,9 +5,9 @@
 from torch.utils import data
 from torchvision import transforms
 
-from BiRefNet.image_proc import preproc
-from BiRefNet.config import Config
-from BiRefNet.utils import path_to_image
+from .image_proc import preproc
+from .config import Config
+from .utils import path_to_image
 
 
 Image.MAX_IMAGE_PIXELS = None       # remove DecompressionBombWarning

diff --git a/py/BiRefNet/eval_existingOnes.py → py/BiRefNet_v2/eval_existingOnes.py b/py/BiRefNet/eval_existingOnes.py → py/BiRefNet_v2/eval_existingOnes.py
@@ -3,8 +3,8 @@
 from glob import glob
 import prettytable as pt
 
-from BiRefNet.evaluation.evaluate import evaluator
-from BiRefNet.config import Config
+from .evaluation.evaluate import evaluator
+from .config import Config
 
 
 config = Config()

diff --git a/py/BiRefNet/evaluation/metrics.py → py/BiRefNet_v2/evaluation/metrics.py b/py/BiRefNet/evaluation/metrics.py → py/BiRefNet_v2/evaluation/metrics.py
diff --git a/py/BiRefNet/gen_best_ep.py → py/BiRefNet_v2/gen_best_ep.py b/py/BiRefNet/gen_best_ep.py → py/BiRefNet_v2/gen_best_ep.py
@@ -2,7 +2,7 @@
 from glob import glob
 import numpy as np
 
-from BiRefNet.config import Config
+from .config import Config
 
 
 config = Config()

diff --git a/py/BiRefNet/image_proc.py → py/BiRefNet_v2/image_proc.py b/py/BiRefNet/image_proc.py → py/BiRefNet_v2/image_proc.py
diff --git a/py/BiRefNet/inference.py → py/BiRefNet_v2/inference.py b/py/BiRefNet/inference.py → py/BiRefNet_v2/inference.py
@@ -5,10 +5,10 @@
 import cv2
 import torch
 
-from BiRefNet.dataset import MyData
-from BiRefNet.models.birefnet import BiRefNet
-from BiRefNet.utils import save_tensor_img, check_state_dict
-from BiRefNet.config import Config
+from .dataset import MyData
+from .models.birefnet import BiRefNet
+from .utils import save_tensor_img, check_state_dict
+from .config import Config
 
 
 config = Config()

diff --git a/py/BiRefNet/loss.py → py/BiRefNet_v2/loss.py b/py/BiRefNet/loss.py → py/BiRefNet_v2/loss.py
@@ -4,7 +4,7 @@
 from torch.autograd import Variable
 from math import exp
 
-from BiRefNet.config import Config
+from .config import Config
 
 
 class Discriminator(nn.Module):

diff --git a/py/BiRefNet/make_a_copy.sh → py/BiRefNet_v2/make_a_copy.sh b/py/BiRefNet/make_a_copy.sh → py/BiRefNet_v2/make_a_copy.sh
diff --git a/...RefNet/models/backbones/build_backbone.py → ...Net_v2/models/backbones/build_backbone.py b/...RefNet/models/backbones/build_backbone.py → ...Net_v2/models/backbones/build_backbone.py
@@ -2,9 +2,9 @@
 import torch.nn as nn
 from collections import OrderedDict
 from torchvision.models import vgg16, vgg16_bn, VGG16_Weights, VGG16_BN_Weights, resnet50, ResNet50_Weights
-from BiRefNet.models.backbones.pvt_v2 import pvt_v2_b0, pvt_v2_b1, pvt_v2_b2, pvt_v2_b5
-from BiRefNet.models.backbones.swin_v1 import swin_v1_t, swin_v1_s, swin_v1_b, swin_v1_l
-from BiRefNet.config import Config
+from ...models.backbones.pvt_v2 import pvt_v2_b0, pvt_v2_b1, pvt_v2_b2, pvt_v2_b5
+from ...models.backbones.swin_v1 import swin_v1_t, swin_v1_s, swin_v1_b, swin_v1_l
+from ...config import Config
 
 
 config = Config()

diff --git a/py/BiRefNet/models/backbones/pvt_v2.py → py/BiRefNet_v2/models/backbones/pvt_v2.py b/py/BiRefNet/models/backbones/pvt_v2.py → py/BiRefNet_v2/models/backbones/pvt_v2.py
@@ -7,7 +7,7 @@
 
 import math
 
-from BiRefNet.config import Config
+from ...config import Config
 
 config = Config()
 

diff --git a/py/BiRefNet/models/backbones/swin_v1.py → py/BiRefNet_v2/models/backbones/swin_v1.py b/py/BiRefNet/models/backbones/swin_v1.py → py/BiRefNet_v2/models/backbones/swin_v1.py
@@ -12,7 +12,7 @@
 import numpy as np
 from timm.models.layers import DropPath, to_2tuple, trunc_normal_
 
-from BiRefNet.config import Config
+from ...config import Config
 
 
 config = Config()

diff --git a/py/BiRefNet/models/birefnet.py → py/BiRefNet_v2/models/birefnet.py b/py/BiRefNet/models/birefnet.py → py/BiRefNet_v2/models/birefnet.py
@@ -4,14 +4,14 @@
 from kornia.filters import laplacian
 from huggingface_hub import PyTorchModelHubMixin
 
-from BiRefNet.config import Config
-from BiRefNet.dataset import class_labels_TR_sorted
-from BiRefNet.models.backbones.build_backbone import build_backbone
-from BiRefNet.models.modules.decoder_blocks import BasicDecBlk, ResBlk
-from BiRefNet.models.modules.lateral_blocks import BasicLatBlk
-from BiRefNet.models.modules.aspp import ASPP, ASPPDeformable
-from BiRefNet.models.refinement.refiner import Refiner, RefinerPVTInChannels4, RefUNet
-from BiRefNet.models.refinement.stem_layer import StemLayer
+from ..config import Config
+from ..dataset import class_labels_TR_sorted
+from ..models.backbones.build_backbone import build_backbone
+from ..models.modules.decoder_blocks import BasicDecBlk, ResBlk
+from ..models.modules.lateral_blocks import BasicLatBlk
+from ..models.modules.aspp import ASPP, ASPPDeformable
+from ..models.refinement.refiner import Refiner, RefinerPVTInChannels4, RefUNet
+from ..models.refinement.stem_layer import StemLayer
 
 
 class BiRefNet(

diff --git a/py/BiRefNet/models/modules/aspp.py → py/BiRefNet_v2/models/modules/aspp.py b/py/BiRefNet/models/modules/aspp.py → py/BiRefNet_v2/models/modules/aspp.py
@@ -2,8 +2,8 @@
 import torch.nn as nn
 import torch.nn.functional as F
 
-from BiRefNet.models.modules.deform_conv import DeformableConv2d
-from BiRefNet.config import Config
+from ...models.modules.deform_conv import DeformableConv2d
+from ...config import Config
 
 
 config = Config()

diff --git a/py/BiRefNet/models/modules/decoder_blocks.py → ...efNet_v2/models/modules/decoder_blocks.py b/py/BiRefNet/models/modules/decoder_blocks.py → ...efNet_v2/models/modules/decoder_blocks.py
@@ -1,8 +1,8 @@
 import torch
 import torch.nn as nn
 
-from BiRefNet.models.modules.aspp import ASPP, ASPPDeformable
-from BiRefNet.config import Config
+from ...models.modules.aspp import ASPP, ASPPDeformable
+from ...config import Config
 
 
 config = Config()

diff --git a/py/BiRefNet/models/modules/deform_conv.py → py/BiRefNet_v2/models/modules/deform_conv.py b/py/BiRefNet/models/modules/deform_conv.py → py/BiRefNet_v2/models/modules/deform_conv.py
diff --git a/py/BiRefNet/models/modules/lateral_blocks.py → ...efNet_v2/models/modules/lateral_blocks.py b/py/BiRefNet/models/modules/lateral_blocks.py → ...efNet_v2/models/modules/lateral_blocks.py
@@ -4,7 +4,7 @@
 import torch.nn.functional as F
 from functools import partial
 
-from BiRefNet.config import Config
+from ...config import Config
 
 
 config = Config()

diff --git a/py/BiRefNet/models/modules/mlp.py → py/BiRefNet_v2/models/modules/mlp.py b/py/BiRefNet/models/modules/mlp.py → py/BiRefNet_v2/models/modules/mlp.py
diff --git a/py/BiRefNet/models/modules/prompt_encoder.py → ...efNet_v2/models/modules/prompt_encoder.py b/py/BiRefNet/models/modules/prompt_encoder.py → ...efNet_v2/models/modules/prompt_encoder.py
diff --git a/py/BiRefNet/models/modules/utils.py → py/BiRefNet_v2/models/modules/utils.py b/py/BiRefNet/models/modules/utils.py → py/BiRefNet_v2/models/modules/utils.py
diff --git a/py/BiRefNet/models/refinement/refiner.py → py/BiRefNet_v2/models/refinement/refiner.py b/py/BiRefNet/models/refinement/refiner.py → py/BiRefNet_v2/models/refinement/refiner.py
@@ -7,12 +7,12 @@
 from torchvision.models import vgg16, vgg16_bn
 from torchvision.models import resnet50
 
-from BiRefNet.config import Config
-from BiRefNet.dataset import class_labels_TR_sorted
-from BiRefNet.models.backbones.build_backbone import build_backbone
-from BiRefNet.models.modules.decoder_blocks import BasicDecBlk
-from BiRefNet.models.modules.lateral_blocks import BasicLatBlk
-from BiRefNet.models.refinement.stem_layer import StemLayer
+from ...config import Config
+from ...dataset import class_labels_TR_sorted
+from ...models.backbones.build_backbone import build_backbone
+from ...models.modules.decoder_blocks import BasicDecBlk
+from ...models.modules.lateral_blocks import BasicLatBlk
+from ...models.refinement.stem_layer import StemLayer
 
 
 class RefinerPVTInChannels4(nn.Module):

diff --git a/py/BiRefNet/models/refinement/stem_layer.py → ...RefNet_v2/models/refinement/stem_layer.py b/py/BiRefNet/models/refinement/stem_layer.py → ...RefNet_v2/models/refinement/stem_layer.py
@@ -1,5 +1,5 @@
 import torch.nn as nn
-from BiRefNet.models.modules.utils import build_act_layer, build_norm_layer
+from ...models.modules.utils import build_act_layer, build_norm_layer
 
 
 class StemLayer(nn.Module):

diff --git a/py/BiRefNet/requirements.txt → py/BiRefNet_v2/requirements.txt b/py/BiRefNet/requirements.txt → py/BiRefNet_v2/requirements.txt
diff --git a/py/BiRefNet/rm_cache.sh → py/BiRefNet_v2/rm_cache.sh b/py/BiRefNet/rm_cache.sh → py/BiRefNet_v2/rm_cache.sh
diff --git a/py/BiRefNet/sub.sh → py/BiRefNet_v2/sub.sh b/py/BiRefNet/sub.sh → py/BiRefNet_v2/sub.sh
diff --git a/py/BiRefNet/test.sh → py/BiRefNet_v2/test.sh b/py/BiRefNet/test.sh → py/BiRefNet_v2/test.sh
diff --git a/py/BiRefNet/train.py → py/BiRefNet_v2/train.py b/py/BiRefNet/train.py → py/BiRefNet_v2/train.py
@@ -6,11 +6,11 @@
 import torch.optim as optim
 from torch.autograd import Variable
 
-from BiRefNet.config import Config
-from BiRefNet.loss import PixLoss, ClsLoss
-from BiRefNet.dataset import MyData
-from BiRefNet.models.birefnet import BiRefNet
-from BiRefNet.utils import Logger, AverageMeter, set_seed, check_state_dict
+from .config import Config
+from .loss import PixLoss, ClsLoss
+from .dataset import MyData
+from .models.birefnet import BiRefNet
+from .utils import Logger, AverageMeter, set_seed, check_state_dict
 
 from torch.utils.data.distributed import DistributedSampler
 from torch.nn.parallel import DistributedDataParallel as DDP

diff --git a/py/BiRefNet/train.sh → py/BiRefNet_v2/train.sh b/py/BiRefNet/train.sh → py/BiRefNet_v2/train.sh
diff --git a/py/BiRefNet/train_test.sh → py/BiRefNet_v2/train_test.sh b/py/BiRefNet/train_test.sh → py/BiRefNet_v2/train_test.sh
diff --git a/...RefNet/tutorials/BiRefNet_inference.ipynb → ...Net_v2/tutorials/BiRefNet_inference.ipynb b/...RefNet/tutorials/BiRefNet_inference.ipynb → ...Net_v2/tutorials/BiRefNet_inference.ipynb
diff --git a/...iRefNet/tutorials/BiRefNet_pth2onnx.ipynb → ...fNet_v2/tutorials/BiRefNet_pth2onnx.ipynb b/...iRefNet/tutorials/BiRefNet_pth2onnx.ipynb → ...fNet_v2/tutorials/BiRefNet_pth2onnx.ipynb
diff --git a/py/BiRefNet/utils.py → py/BiRefNet_v2/utils.py b/py/BiRefNet/utils.py → py/BiRefNet_v2/utils.py
diff --git a/py/birefnet_ultra_v2.py b/py/birefnet_ultra_v2.py
@@ -5,8 +5,8 @@
 import tqdm
 from .imagefunc import *
 from comfy.utils import ProgressBar
-# sys.path.append(os.path.join(os.path.dirname(__file__), 'BiRefNet'))
-from .BiRefNet.models.birefnet import BiRefNet
+sys.path.append(os.path.join(os.path.dirname(__file__), 'BiRefNet_v2'))
+
 
 def get_models():
     model_path = os.path.join(folder_paths.models_dir, 'BiRefNet', 'pth')
@@ -42,7 +42,8 @@ def INPUT_TYPES(s):
     CATEGORY = '😺dzNodes/LayerMask'
 
     def load_birefnet_model(self, model):
-        from .BiRefNet.utils import check_state_dict
+        from .BiRefNet_v2.models.birefnet import BiRefNet
+        from .BiRefNet_v2.utils import check_state_dict
         model_dict = get_models()
         self.birefnet = BiRefNet(bb_pretrained=False)
         self.state_dict = torch.load(model_dict[model], map_location='cpu', weights_only=True)

diff --git a/pyproject.toml b/pyproject.toml
@@ -1,7 +1,7 @@
 [project]
 name = "comfyui_layerstyle"
 description = "A set of nodes for ComfyUI it generate image like Adobe Photoshop's Layer Style. the Drop Shadow is first completed node, and follow-up work is in progress."
-version = "1.0.65"
+version = "1.0.66"
 license = "MIT"
 dependencies = ["numpy", "pillow", "torch", "matplotlib", "Scipy", "scikit_image", "scikit_learn", "opencv-contrib-python", "pymatting", "segment_anything", "timm", "addict", "yapf", "colour-science", "wget", "mediapipe", "loguru", "typer_config", "fastapi", "rich", "google-generativeai", "diffusers", "omegaconf", "tqdm", "transformers", "kornia", "image-reward", "ultralytics", "blend_modes", "blind-watermark", "qrcode", "pyzbar", "transparent-background", "huggingface_hub", "accelerate", "bitsandbytes", "torchscale", "wandb", "hydra-core", "psd-tools", "inference-cli[yolo-world]", "inference-gpu[yolo-world]", "onnxruntime"]