IC-Custom Application

A sophisticated image customization tool powered by advanced AI models.

📺 App Guide:
For a fast overview of how to use the app, watch this video:
IC-Custom App Usage Guide (YouTube)

---

🚀 Quick Start

if [ -z "$HF_TOKEN" ] && [ -z "$HF_CACHE_DIR" ] && [ -z "$ASSETS_CACHE_DIR" ]; then
    python src/app/app.py \
        --config configs/app/app.yaml \
        --save_results \
        --enable_ben2_for_mask_ref \
        --enable_vlm_for_prompt \
else
    python src/app/app.py \
        --config configs/app/app.yaml \
        --hf_token $HF_TOKEN \
        --hf_cache_dir $HF_CACHE_DIR \
        --assets_cache_dir $ASSETS_CACHE_DIR \
        --save_results \
        --enable_ben2_for_mask_ref \
        --enable_vlm_for_prompt \
fi

---

⚙️ Configuration & CLI Arguments

Argument	Type	Required	Default	Description
--config	str	✅	-	Path to app YAML config file
--hf_token	str	❌	-	Hugging Face access token.
--hf_cache_dir	str	❌	~/.cache/huggingface/hub	HF assets cache directory
--assets_cache_dir	str	❌	results/app	Output images & metadata directory
--save_results	bool	❌	False	Save generated results
--enable_ben2_for_mask_ref	bool	❌	False	Enable BEN2 background removal
--enable_vlm_for_prompt	bool	❌	False	Enable VLM prompt generation

Environment Variables

• HF_TOKEN ← --hf_token
• HF_HUB_CACHE ← --hf_cache_dir

---

📥 Model Downloads

Model checkpoints are required before running the app.
All required models will be automatically downloaded when you run the app, or you can manually download them and specify paths in configs/app/app.yaml.

Required Models

The following models are automatically downloaded when running the app:

Model	Purpose	Source
IC-Custom	Our customization model	TencentARC/IC-Custom
CLIP	Vision-language understanding	openai/clip-vit-large-patch14
T5	Text processing	google/t5-v1_1-xxl
SigLIP	Image understanding	google/siglip-so400m-patch14-384
Autoencoder	Image encoding/decoding	black-forest-labs/FLUX.1-Fill-dev
DIT	Diffusion model	black-forest-labs/FLUX.1-Fill-dev
Redux	Image processing	black-forest-labs/FLUX.1-Redux-dev
SAM-vit-h	Image segmentation	HCMUE-Research/SAM-vit-h

Optional Models (Selective Download)

BEN2 and Qwen2.5-VL models are disabled by default and only downloaded when explicitly enabled:

Model	Flag	Source	Purpose
BEN2	--enable_ben2_for_mask_ref True	PramaLLC/BEN2	Background removal
Qwen2.5-VL	--enable_vlm_for_prompt True	Qwen/Qwen2.5-VL-7B-Instruct	Prompt generation

Manual Configuration

Alternative: Manually download all models and specify paths in configs/app/app.yaml:

checkpoint_config:
  # Required models
  dit_path: "/path/to/flux1-fill-dev.safetensors"
  ae_path: "/path/to/ae.safetensors"
  t5_path: "/path/to/t5-v1_1-xxl"
  clip_path: "/path/to/clip-vit-large-patch14"
  siglip_path: "/path/to/siglip-so400m-patch14-384"
  redux_path: "/path/to/flux1-redux-dev.safetensors"
  # IC-Custom models
  lora_path: "/path/to/dit_lora_0x1561.safetensors"
  img_txt_in_path: "/path/to/dit_txt_img_in_0x1561.safetensors"
  boundary_embeddings_path: "/path/to/dit_boundary_embeddings_0x1561.safetensors"
  task_register_embeddings_path: "/path/to/dit_task_register_embeddings_0x1561.safetensors"
  # APP interactive models
  sam_path: "/path/to/sam_vit_h_4b8939.pth"
  # Optional models
  ben2_path: "/path/to/BEN2_Base.pth"
  vlm_path: "/path/to/Qwen2.5-VL-7B-Instruct"

APP Overview