wangbo/ComfyUI
1
0
Fork 0
mirror of https://github.com/comfyanonymous/ComfyUI.git synced 2025-12-19 11:03:00 +08:00
Code Issues Actions 13 Packages Projects Releases Wiki Activity

Increase EliGen entity limit to 8

Browse Source
This commit is contained in:
nolan4 2025-11-09 16:10:07 -08:00
parent 242037fa32
commit 65935d512f
1 changed files with 24 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

28
comfy_extras/nodes_qwen.py
View File

@ -116,7 +116,7 @@ class TextEncodeQwenImageEliGen(io.ComfyNode):
spatial attention masking.
Features:
- Supports up to 3 entities per generation
- Supports up to 8 entities per generation
- Spatial attention masks prevent cross-entity contamination
- Separate RoPE embeddings per entity (research-accurate)
- Falls back to standard generation if no entities provided
@ -147,6 +147,16 @@ class TextEncodeQwenImageEliGen(io.ComfyNode):
io.String.Input("entity_prompt_2", multiline=True, dynamic_prompts=True, default=""),
io.Mask.Input("entity_mask_3", optional=True),
io.String.Input("entity_prompt_3", multiline=True, dynamic_prompts=True, default=""),
io.Mask.Input("entity_mask_4", optional=True),
io.String.Input("entity_prompt_4", multiline=True, dynamic_prompts=True, default=""),
io.Mask.Input("entity_mask_5", optional=True),
io.String.Input("entity_prompt_5", multiline=True, dynamic_prompts=True, default=""),
io.Mask.Input("entity_mask_6", optional=True),
io.String.Input("entity_prompt_6", multiline=True, dynamic_prompts=True, default=""),
io.Mask.Input("entity_mask_7", optional=True),
io.String.Input("entity_prompt_7", multiline=True, dynamic_prompts=True, default=""),
io.Mask.Input("entity_mask_8", optional=True),
io.String.Input("entity_prompt_8", multiline=True, dynamic_prompts=True, default=""),
],
outputs=[
io.Conditioning.Output(),
@ -164,7 +174,17 @@ class TextEncodeQwenImageEliGen(io.ComfyNode):
entity_prompt_2: str = "",
entity_mask_2: Optional[torch.Tensor] = None,
entity_prompt_3: str = "",
entity_mask_3: Optional[torch.Tensor] = None
entity_mask_3: Optional[torch.Tensor] = None,
entity_prompt_4: str = "",
entity_mask_4: Optional[torch.Tensor] = None,
entity_prompt_5: str = "",
entity_mask_5: Optional[torch.Tensor] = None,
entity_prompt_6: str = "",
entity_mask_6: Optional[torch.Tensor] = None,
entity_prompt_7: str = "",
entity_mask_7: Optional[torch.Tensor] = None,
entity_prompt_8: str = "",
entity_mask_8: Optional[torch.Tensor] = None
) -> io.NodeOutput:
# Extract dimensions from latent tensor
@ -188,8 +208,8 @@ class TextEncodeQwenImageEliGen(io.ComfyNode):
logging.debug(f"[EliGen] Target generation dimensions: {height}x{width} pixels ({latent_height}x{latent_width} latent)")
# Collect entity prompts and masks
entity_prompts = [entity_prompt_1, entity_prompt_2, entity_prompt_3]
entity_masks_raw = [entity_mask_1, entity_mask_2, entity_mask_3]
entity_prompts = [entity_prompt_1, entity_prompt_2, entity_prompt_3, entity_prompt_4, entity_prompt_5, entity_prompt_6, entity_prompt_7, entity_prompt_8]
entity_masks_raw = [entity_mask_1, entity_mask_2, entity_mask_3, entity_mask_4, entity_mask_5, entity_mask_6, entity_mask_7, entity_mask_8]
# Filter out entities with empty prompts or missing masks
valid_entities = []