Merge pull request #24 from longgui0318/main

* diffusers 0.26 support . from https://github.com/levihsu/OOTDiffusion/issues/44#issuecomment-1968365131

---------

Co-authored-by: gubei <>

pipelines_ootd/transformer_garm_2d.py

@@ -26,7 +26,7 @@ from diffusers.configuration_utils import ConfigMixin, register_to_config
 from diffusers.models.embeddings import ImagePositionalEmbeddings
 from diffusers.utils import USE_PEFT_BACKEND, BaseOutput, deprecate
 # from diffusers.models.attention import BasicTransformerBlock
-from diffusers.models.embeddings import CaptionProjection, PatchEmbed
+from diffusers.models.embeddings import PixArtAlphaTextProjection, PatchEmbed
 from diffusers.models.lora import LoRACompatibleConv, LoRACompatibleLinear
 from diffusers.models.modeling_utils import ModelMixin
 from diffusers.models.normalization import AdaLayerNormSingle
@@ -237,7 +237,7 @@ class Transformer2DModel(ModelMixin, ConfigMixin):
 
         self.caption_projection = None
         if caption_channels is not None:
-            self.caption_projection = CaptionProjection(in_features=caption_channels, hidden_size=inner_dim)
+            self.caption_projection = PixArtAlphaTextProjection(in_features=caption_channels, hidden_size=inner_dim)
 
         self.gradient_checkpointing = False
 

pipelines_ootd/transformer_vton_2d.py

@@ -26,7 +26,7 @@ from diffusers.configuration_utils import ConfigMixin, register_to_config
 from diffusers.models.embeddings import ImagePositionalEmbeddings
 from diffusers.utils import USE_PEFT_BACKEND, BaseOutput, deprecate
 # from diffusers.models.attention import BasicTransformerBlock
-from diffusers.models.embeddings import CaptionProjection, PatchEmbed
+from diffusers.models.embeddings import PixArtAlphaTextProjection, PatchEmbed
 from diffusers.models.lora import LoRACompatibleConv, LoRACompatibleLinear
 from diffusers.models.modeling_utils import ModelMixin
 from diffusers.models.normalization import AdaLayerNormSingle
@@ -237,7 +237,7 @@ class Transformer2DModel(ModelMixin, ConfigMixin):
 
         self.caption_projection = None
         if caption_channels is not None:
-            self.caption_projection = CaptionProjection(in_features=caption_channels, hidden_size=inner_dim)
+            self.caption_projection = PixArtAlphaTextProjection(in_features=caption_channels, hidden_size=inner_dim)
 
         self.gradient_checkpointing = False
 

pipelines_ootd/unet_garm_2d_condition.py

@@ -44,7 +44,7 @@ from diffusers.models.embeddings import (
     ImageHintTimeEmbedding,
     ImageProjection,
     ImageTimeEmbedding,
-    PositionNet,
+    GLIGENTextBoundingboxProjection,
     TextImageProjection,
     TextImageTimeEmbedding,
     TextTimeEmbedding,
@@ -624,7 +624,7 @@ class UNetGarm2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoadersMi
                 positive_len = cross_attention_dim[0]
 
             feature_type = "text-only" if attention_type == "gated" else "text-image"
-            self.position_net = PositionNet(
+            self.position_net = GLIGENTextBoundingboxProjection(
                 positive_len=positive_len, out_dim=cross_attention_dim, feature_type=feature_type
             )
 

pipelines_ootd/unet_vton_2d_condition.py

@@ -44,7 +44,7 @@ from diffusers.models.embeddings import (
     ImageHintTimeEmbedding,
     ImageProjection,
     ImageTimeEmbedding,
-    PositionNet,
+    GLIGENTextBoundingboxProjection,
     TextImageProjection,
     TextImageTimeEmbedding,
     TextTimeEmbedding,
@@ -624,7 +624,7 @@ class UNetVton2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoadersMi
                 positive_len = cross_attention_dim[0]
 
             feature_type = "text-only" if attention_type == "gated" else "text-image"
-            self.position_net = PositionNet(
+            self.position_net = GLIGENTextBoundingboxProjection(
                 positive_len=positive_len, out_dim=cross_attention_dim, feature_type=feature_type
             )
 

requirements.txt

@@ -5,7 +5,7 @@ scipy
 scikit-image
 opencv-python
 pillow
-diffusers==0.24.0
+diffusers>=0.26.0
 transformers
 accelerate
 matplotlib