From ad0637884ff26410fea1005df3d9a130dc3062e7 Mon Sep 17 00:00:00 2001
From: smthem <2102561739@qq.com>
Date: Wed, 4 Jun 2025 15:01:30 +0800
Subject: [PATCH] init
---
OmniConsistency/README.md | 164 ++++
.../__pycache__/infer.cpython-311.pyc | Bin 0 -> 818 bytes
OmniConsistency/app.py | 210 +++++
OmniConsistency/figure/teaser.png | Bin 0 -> 3419724 bytes
OmniConsistency/figure/test.png | Bin 0 -> 102778 bytes
OmniConsistency/infer.py | 54 ++
OmniConsistency/requirements.txt | 17 +
OmniConsistency/src_inference/__init__.py | 0
.../__pycache__/__init__.cpython-311.pyc | Bin 0 -> 208 bytes
.../__pycache__/layers_cache.cpython-311.pyc | Bin 0 -> 21920 bytes
.../__pycache__/lora_helper.cpython-311.pyc | Bin 0 -> 16825 bytes
.../__pycache__/pipeline.cpython-311.pyc | Bin 0 -> 36468 bytes
OmniConsistency/src_inference/layers_cache.py | 366 +++++++++
OmniConsistency/src_inference/lora_helper.py | 194 +++++
OmniConsistency/src_inference/pipeline.py | 749 ++++++++++++++++++
OmniConsistency/src_inference/pipeline_.py | 746 +++++++++++++++++
OmniConsistency/test_imgs/00.png | Bin 0 -> 65646 bytes
OmniConsistency/test_imgs/01.png | Bin 0 -> 41478 bytes
OmniConsistency/test_imgs/02.png | Bin 0 -> 74212 bytes
OmniConsistency/test_imgs/03.png | Bin 0 -> 44992 bytes
OmniConsistency/test_imgs/04.png | Bin 0 -> 46228 bytes
Storydiffusion_node.py | 62 +-
model_loader_utils.py | 93 +++
23 files changed, 2652 insertions(+), 3 deletions(-)
create mode 100644 OmniConsistency/README.md
create mode 100644 OmniConsistency/__pycache__/infer.cpython-311.pyc
create mode 100644 OmniConsistency/app.py
create mode 100644 OmniConsistency/figure/teaser.png
create mode 100644 OmniConsistency/figure/test.png
create mode 100644 OmniConsistency/infer.py
create mode 100644 OmniConsistency/requirements.txt
create mode 100644 OmniConsistency/src_inference/__init__.py
create mode 100644 OmniConsistency/src_inference/__pycache__/__init__.cpython-311.pyc
create mode 100644 OmniConsistency/src_inference/__pycache__/layers_cache.cpython-311.pyc
create mode 100644 OmniConsistency/src_inference/__pycache__/lora_helper.cpython-311.pyc
create mode 100644 OmniConsistency/src_inference/__pycache__/pipeline.cpython-311.pyc
create mode 100644 OmniConsistency/src_inference/layers_cache.py
create mode 100644 OmniConsistency/src_inference/lora_helper.py
create mode 100644 OmniConsistency/src_inference/pipeline.py
create mode 100644 OmniConsistency/src_inference/pipeline_.py
create mode 100644 OmniConsistency/test_imgs/00.png
create mode 100644 OmniConsistency/test_imgs/01.png
create mode 100644 OmniConsistency/test_imgs/02.png
create mode 100644 OmniConsistency/test_imgs/03.png
create mode 100644 OmniConsistency/test_imgs/04.png
diff --git a/OmniConsistency/README.md b/OmniConsistency/README.md
new file mode 100644
index 0000000..5a4a5da
--- /dev/null
+++ b/OmniConsistency/README.md
@@ -0,0 +1,164 @@
+# OmniConsistency
+
+> **OmniConsistency: Learning Style-Agnostic
+Consistency from Paired Stylization Data**
+>
+> [Yiren Song](https://scholar.google.com.hk/citations?user=L2YS0jgAAAAJ),
+> [Cheng Liu](https://scholar.google.com.hk/citations?hl=zh-CN&user=TvdVuAYAAAAJ),
+> and
+> [Mike Zheng Shou](https://sites.google.com/view/showlab)
+>
+> [Show Lab](https://sites.google.com/view/showlab), National University of Singapore
+>
+
+
+
+
+
+
+
+
+
+
+## News
+- **2025‑06‑01**: 🚀 Released the **OmniConsistency Generator** [ComfyUI node](https://github.com/lc03lc/Comfyui_OmniConsistency) – one‑click FLUX + OmniConsistency (with any LoRA) inside ComfyUI.
+
+
+## Installation
+
+We recommend using Python 3.10 and PyTorch with CUDA support. To set up the environment:
+
+```bash
+# Create a new conda environment
+conda create -n omniconsistency python=3.10
+conda activate omniconsistency
+
+# Install other dependencies
+pip install -r requirements.txt
+```
+
+## Download
+
+You can download the OmniConsistency model and trained LoRAs directly from [Hugging Face](https://huggingface.co/showlab/OmniConsistency).
+Or download using Python script:
+
+### OmniConsistency Model
+
+```python
+from huggingface_hub import hf_hub_download
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/3D_Chibi_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/American_Cartoon_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Chinese_Ink_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Clay_Toy_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Fabric_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Ghibli_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Irasutoya_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Jojo_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/LEGO_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Line_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Macaron_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Oil_Painting_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Origami_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Paper_Cutting_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Picasso_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Pixel_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Poly_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Pop_Art_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Rick_Morty_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Snoopy_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Van_Gogh_rank128_bf16.safetensors", local_dir="./LoRAs")
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="LoRAs/Vector_rank128_bf16.safetensors", local_dir="./LoRAs")
+```
+### Trained LoRAs
+```python
+from huggingface_hub import hf_hub_download
+hf_hub_download(repo_id="showlab/OmniConsistency", filename="OmniConsistency.safetensors", local_dir="./Model")
+```
+
+## Usage
+Here's a basic example of using OmniConsistency:
+
+### Model Initialization
+```python
+import time
+import torch
+from PIL import Image
+from src_inference.pipeline import FluxPipeline
+from src_inference.lora_helper import set_single_lora
+
+def clear_cache(transformer):
+ for name, attn_processor in transformer.attn_processors.items():
+ attn_processor.bank_kv.clear()
+
+# Initialize model
+device = "cuda"
+base_path = "/path/to/black-forest-labs/FLUX.1-dev"
+pipe = FluxPipeline.from_pretrained(base_path, torch_dtype=torch.bfloat16).to("cuda")
+
+# Load OmniConsistency model
+set_single_lora(pipe.transformer,
+ "/path/to/OmniConsistency.safetensors",
+ lora_weights=[1], cond_size=512)
+
+# Load external LoRA
+pipe.unload_lora_weights()
+pipe.load_lora_weights("/path/to/lora_folder",
+ weight_name="lora_name.safetensors")
+```
+
+### Style Inference
+```python
+image_path1 = "figure/test.png"
+prompt = "3D Chibi style, Three individuals standing together in the office."
+
+subject_images = []
+spatial_image = [Image.open(image_path1).convert("RGB")]
+
+width, height = 1024, 1024
+
+start_time = time.time()
+
+image = pipe(
+ prompt,
+ height=height,
+ width=width,
+ guidance_scale=3.5,
+ num_inference_steps=25,
+ max_sequence_length=512,
+ generator=torch.Generator("cpu").manual_seed(5),
+ spatial_images=spatial_image,
+ subject_images=subject_images,
+ cond_size=512,
+).images[0]
+
+end_time = time.time()
+elapsed_time = end_time - start_time
+print(f"code running time: {elapsed_time} s")
+
+# Clear cache after generation
+clear_cache(pipe.transformer)
+
+image.save("results/output.png")
+```
+
+## Datasets
+Our datasets have been uploaded to the [Hugging Face](https://huggingface.co/datasets/showlab/OmniConsistency). and is available for direct use via the datasets library.
+
+You can easily load any of the 22 style subsets like this:
+```python
+from datasets import load_dataset
+
+# Load a single style (e.g., Ghibli)
+ds = load_dataset("showlab/OmniConsistency", split="Ghibli")
+print(ds[0])
+```
+
+## Citation
+```
+@inproceedings{Song2025OmniConsistencyLS,
+ title={OmniConsistency: Learning Style-Agnostic Consistency from Paired Stylization Data},
+ author={Yiren Song and Cheng Liu and Mike Zheng Shou},
+ year={2025},
+ url={https://api.semanticscholar.org/CorpusID:278905729}
+}
+```
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diff --git a/OmniConsistency/app.py b/OmniConsistency/app.py
new file mode 100644
index 0000000..937391b
--- /dev/null
+++ b/OmniConsistency/app.py
@@ -0,0 +1,210 @@
+# import spaces
+import os
+import time
+import torch
+# import gradio as gr
+from PIL import Image
+from huggingface_hub import hf_hub_download, list_repo_files
+from src_inference.pipeline import FluxPipeline
+from src_inference.lora_helper import set_single_lora
+
+BASE_PATH = "black-forest-labs/FLUX.1-dev"
+LOCAL_LORA_DIR = "./LoRAs"
+CUSTOM_LORA_DIR = "./Custom_LoRAs"
+os.makedirs(LOCAL_LORA_DIR, exist_ok=True)
+os.makedirs(CUSTOM_LORA_DIR, exist_ok=True)
+
+print("downloading OmniConsistency base LoRA …")
+omni_consistency_path = hf_hub_download(
+ repo_id="showlab/OmniConsistency",
+ filename="OmniConsistency.safetensors",
+ local_dir="./Model"
+)
+
+print("loading base pipeline …")
+pipe = FluxPipeline.from_pretrained(
+ BASE_PATH, torch_dtype=torch.bfloat16
+).to("cuda")
+set_single_lora(pipe.transformer, omni_consistency_path,
+ lora_weights=[1], cond_size=512)
+
+def download_all_loras():
+ lora_names = [
+ "3D_Chibi", "American_Cartoon", "Chinese_Ink", "Clay_Toy",
+ "Fabric", "Ghibli", "Irasutoya", "Jojo", "LEGO", "Line",
+ "Macaron", "Oil_Painting", "Origami", "Paper_Cutting",
+ "Picasso", "Pixel", "Poly", "Pop_Art", "Rick_Morty",
+ "Snoopy", "Van_Gogh", "Vector"
+ ]
+ for name in lora_names:
+ hf_hub_download(
+ repo_id="showlab/OmniConsistency",
+ filename=f"LoRAs/{name}_rank128_bf16.safetensors",
+ local_dir=LOCAL_LORA_DIR,
+ )
+download_all_loras()
+
+def clear_cache(transformer):
+ for _, attn_processor in transformer.attn_processors.items():
+ attn_processor.bank_kv.clear()
+
+# @spaces.GPU()
+def generate_image(
+ lora_name,
+ custom_repo_id,
+ prompt,
+ uploaded_image,
+ width, height,
+ guidance_scale,
+ num_inference_steps,
+ seed
+):
+ width, height = int(width), int(height)
+ generator = torch.Generator("cpu").manual_seed(seed)
+
+ if custom_repo_id and custom_repo_id.strip():
+ repo_id = custom_repo_id.strip()
+ try:
+ files = list_repo_files(repo_id)
+ print("using custom LoRA from:", repo_id)
+ safetensors_files = [f for f in files if f.endswith(".safetensors")]
+ print("found safetensors files:", safetensors_files)
+ if not safetensors_files:
+ raise ValueError("No .safetensors files were found in this repo")
+ fname = safetensors_files[0]
+ lora_path = hf_hub_download(
+ repo_id=repo_id,
+ filename=fname,
+ local_dir=CUSTOM_LORA_DIR,
+ )
+ except Exception as e:
+ raise gr.Error(f"Load custom LoRA failed: {e}")
+ else:
+ lora_path = os.path.join(
+ f"{LOCAL_LORA_DIR}/LoRAs", f"{lora_name}_rank128_bf16.safetensors"
+ )
+
+ pipe.unload_lora_weights()
+ try:
+ pipe.load_lora_weights(
+ os.path.dirname(lora_path),
+ weight_name=os.path.basename(lora_path)
+ )
+ except Exception as e:
+ raise gr.Error(f"Load LoRA failed: {e}")
+
+ spatial_image = [uploaded_image.convert("RGB")]
+ subject_images = []
+ start = time.time()
+ out_img = pipe(
+ prompt,
+ height=(height // 8) * 8,
+ width=(width // 8) * 8,
+ guidance_scale=guidance_scale,
+ num_inference_steps=num_inference_steps,
+ max_sequence_length=512,
+ generator=generator,
+ spatial_images=spatial_image,
+ subject_images=subject_images,
+ cond_size=512,
+ ).images[0]
+ print(f"inference time: {time.time()-start:.2f}s")
+
+ clear_cache(pipe.transformer)
+ return uploaded_image, out_img
+
+# =============== Gradio UI ===============
+def create_interface():
+ demo_lora_names = [
+ "3D_Chibi", "American_Cartoon", "Chinese_Ink", "Clay_Toy",
+ "Fabric", "Ghibli", "Irasutoya", "Jojo", "LEGO", "Line",
+ "Macaron", "Oil_Painting", "Origami", "Paper_Cutting",
+ "Picasso", "Pixel", "Poly", "Pop_Art", "Rick_Morty",
+ "Snoopy", "Van_Gogh", "Vector"
+ ]
+
+ def update_trigger_word(lora_name, prompt):
+ for name in demo_lora_names:
+ trigger = " ".join(name.split("_")) + " style,"
+ prompt = prompt.replace(trigger, "")
+ new_trigger = " ".join(lora_name.split("_"))+ " style,"
+ return new_trigger + prompt
+
+ # Example data
+ examples = [
+ ["3D_Chibi", "", "3D Chibi style, Two smiling colleagues enthusiastically high-five in front of a whiteboard filled with technical notes about multimodal learning, reflecting a moment of success and collaboration at OpenAI.",
+ Image.open("./test_imgs/00.png"), 680, 1024, 3.5, 24, 42],
+ ["Clay_Toy", "", "Clay Toy style, Three team members from OpenAI are gathered around a laptop in a cozy, festive setting, with holiday decorations in the background; one waves cheerfully while the others engage in light conversation, reflecting a relaxed and collaborative atmosphere.",
+ Image.open("./test_imgs/01.png"), 560, 1024, 3.5, 24, 42],
+ ["American_Cartoon", "", "American Cartoon style, In a dramatic and comedic moment from a classic Chinese film, an intense elder with a white beard and red hat grips a younger man, declaring something with fervor, while the subtitle at the bottom reads 'I want them all' — capturing both tension and humor.",
+ Image.open("./test_imgs/02.png"), 568, 1024, 3.5, 24, 42],
+ ["Origami", "", "Origami style, A thrilled fan wearing a Portugal football kit poses energetically with a smiling Cristiano Ronaldo, who gives a thumbs-up, as they stand side by side in a casual, cheerful moment—capturing the excitement of meeting a football legend.",
+ Image.open("./test_imgs/03.png"), 768, 672, 3.5, 24, 42],
+ ["Vector", "", "Vector style, A man glances admiringly at a passing woman, while his girlfriend looks at him in disbelief, perfectly capturing the theme of shifting attention and misplaced priorities in a humorous, relatable way.",
+ Image.open("./test_imgs/04.png"), 512, 1024, 3.5, 24, 42]
+ ]
+
+ header = """
+
+"""
+
+ with gr.Blocks() as demo:
+ gr.Markdown("# OmniConsistency LoRA Image Generation")
+ gr.Markdown("Select a LoRA, enter a prompt, and upload an image to generate a new image with OmniConsistency.")
+ gr.HTML(header)
+
+ with gr.Row():
+ with gr.Column(scale=1):
+ image_input = gr.Image(type="pil", label="Upload Image")
+ prompt_box = gr.Textbox(label="Prompt",
+ value="3D Chibi style,",
+ info="Remember to include the necessary trigger words if you're using a custom LoRA."
+ )
+ lora_dropdown = gr.Dropdown(
+ demo_lora_names, label="Select built-in LoRA")
+ custom_repo_box = gr.Textbox(
+ label="Enter Custom LoRA",
+ placeholder="LoRA Hugging Face path (e.g., 'username/repo_name')",
+ info="If you want to use a custom LoRA, enter its Hugging Face repo ID here and built-in LoRA will be Overridden. Leave empty to use built-in LoRAs. [Check the list of FLUX LoRAs](https://huggingface.co/models?other=base_model:adapter:black-forest-labs/FLUX.1-dev)"
+ )
+ gen_btn = gr.Button("Generate")
+ with gr.Column(scale=1):
+ output_image = gr.ImageSlider(label="Generated Image")
+ with gr.Accordion("Advanced Options", open=False):
+ height_box = gr.Textbox(value="1024", label="Height")
+ width_box = gr.Textbox(value="1024", label="Width")
+ guidance_slider = gr.Slider(
+ 0.1, 20, value=3.5, step=0.1, label="Guidance Scale")
+ steps_slider = gr.Slider(
+ 1, 50, value=25, step=1, label="Inference Steps")
+ seed_slider = gr.Slider(
+ 1, 2_147_483_647, value=42, step=1, label="Seed")
+
+ lora_dropdown.select(fn=update_trigger_word, inputs=[lora_dropdown,prompt_box],
+ outputs=prompt_box)
+
+ gr.Examples(
+ examples=examples,
+ inputs=[lora_dropdown, custom_repo_box, prompt_box, image_input,
+ height_box, width_box, guidance_slider, steps_slider, seed_slider],
+ outputs=output_image,
+ fn=generate_image,
+ cache_examples=False,
+ label="Examples"
+ )
+
+ gen_btn.click(
+ fn=generate_image,
+ inputs=[lora_dropdown, custom_repo_box, prompt_box, image_input,
+ width_box, height_box, guidance_slider, steps_slider, seed_slider],
+ outputs=output_image
+ )
+ return demo
+
+if __name__ == "__main__":
+ demo = create_interface()
+ demo.launch(ssr_mode=False)
\ No newline at end of file
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