# Main real-world inference configuration
seed: 42
max_layer_num: 52

# Size configuration
source_size: 1024
target_size: 1024

# Real-world inference defaults. The Gradio demo and unified CLI override these
# paths per uploaded image; direct `infer/infer.py` runs can point them to a
# prepared local JSONL/image directory.
data_dir: "demo/outputs/real_world_demo"
image_dir: "demo/outputs/real_world_demo/layers_real_test_1024"
test_jsonl: "demo/outputs/real_world_demo/caption_bbox_infer.jsonl"

# Model paths
pretrained_model_name_or_path: "SynLayers_checkpoints/FLUX.1-dev"
pretrained_adapter_path: "SynLayers_checkpoints/FLUX.1-dev-Controlnet-Inpainting-Alpha"
transp_vae_path: "ckpt/trans_vae/0008000.pt"

# Pre-trained LoRA weights
pretrained_lora_dir: "ckpt/pre_trained_LoRA"
artplus_lora_dir: "ckpt/prism_ft_LoRA"

# unified real-world decomposition checkpoint
lora_ckpt: "SynLayers_ckpt/step_120000/transformer"
layer_ckpt: "SynLayers_ckpt/step_120000"
adapter_lora_dir: "SynLayers_ckpt/step_120000/adapter"

# Inference settings
cfg: 4.0
adapter_scale: 0.9
max_sequence_length: 1024

save_dir: "demo/outputs/real_world_infer/results"
#run_name: "step_120000"  # optional manual override

# Sample range control (1-based indexing)
start_idx: 1
#end_idx: 147
#max_samples: 147