change path

app.py

@@ -34,6 +34,7 @@ if str(PROJECT_ROOT) not in sys.path:
 
 from demo.real_world_pipeline import (  # noqa: E402
     DEFAULT_BBOX_MODEL,
+    DEFAULT_MODEL_REPO_ID,
     DEFAULT_REAL_CONFIG_PATH,
     DEFAULT_RUN_NAME,
     DEFAULT_WORK_DIR,
@@ -43,7 +44,7 @@ from demo.real_world_pipeline import (  # noqa: E402
 DEFAULT_EXAMPLE_DIR = Path(
     os.environ.get(
         "SYNLAYERS_EXAMPLE_DIR",
-        "/project/llmsvgen/share/data/kmw_layered_dataset/real_world_inference/layers_real_test_1024",
+        str(PROJECT_ROOT / "demo" / "examples"),
     )
 )
 
@@ -106,7 +107,7 @@ def is_zero_gpu_space() -> bool:
 def get_runtime_status_markdown() -> str:
     accelerator = os.environ.get("ACCELERATOR", "unknown")
     space_id = os.environ.get("SPACE_ID", "local")
-    model_repo = os.environ.get("SYNLAYERS_MODEL_REPO", "(unset)")
+    model_repo = os.environ.get("SYNLAYERS_MODEL_REPO") or DEFAULT_MODEL_REPO_ID
     zero_gpu_enabled = is_zero_gpu_space()
 
     lines = ["## Runtime Status", f"- `SPACE_ID`: `{space_id}`", f"- `ACCELERATOR`: `{accelerator}`"]

demo/hf_repo_assets.py

@@ -6,9 +6,11 @@ from pathlib import Path
 
 from huggingface_hub import snapshot_download
 
+DEFAULT_MODEL_REPO_ID = "SynLayers/Bbox-caption-8b"
+
 
 def get_model_repo_id() -> str | None:
-    return os.environ.get("SYNLAYERS_MODEL_REPO")
+    return os.environ.get("SYNLAYERS_MODEL_REPO") or DEFAULT_MODEL_REPO_ID
 
 
 def get_cache_dir() -> str | None:

demo/infer/run_caption_bbox_infer.py

@@ -21,20 +21,14 @@ except ImportError:
     )
 
 PROJECT_ROOT = Path(__file__).resolve().parents[2]
+DEFAULT_MODEL_REPO_ID = "SynLayers/Bbox-caption-8b"
 
 
 def resolve_default_bbox_model() -> str:
     env_path = os.environ.get("SYNLAYERS_BBOX_MODEL") or os.environ.get("SYNLAYERS_MODEL_REPO")
-    candidates = [
-        Path(env_path) if env_path else None,
-        PROJECT_ROOT if (PROJECT_ROOT / "config.json").exists() and (PROJECT_ROOT / "tokenizer_config.json").exists() else None,
-        PROJECT_ROOT / "Bbox-caption-8b",
-        Path("/project/llmsvgen/share/data/kmw_layered_checkpoint/Bbox-caption-8b"),
-    ]
-    for candidate in candidates:
-        if candidate and candidate.exists():
-            return str(candidate)
-    return str(Path("/project/llmsvgen/share/data/kmw_layered_checkpoint/Bbox-caption-8b"))
+    if env_path and Path(env_path).exists():
+        return str(Path(env_path))
+    return env_path or DEFAULT_MODEL_REPO_ID
 
 
 CAPTION_BBOX_PROMPT_TOP_LEFT = (

demo/real_world_pipeline.py

@@ -35,6 +35,7 @@ DEFAULT_REAL_CONFIG_PATH = PROJECT_ROOT / "infer" / "infer.yaml"
 DEFAULT_WORK_DIR = PROJECT_ROOT / "demo" / "outputs" / "real_world_demo"
 DEFAULT_RUN_NAME = "step_120000"
 DEFAULT_TARGET_SIZE = 1024
+DEFAULT_MODEL_REPO_ID = "SynLayers/Bbox-caption-8b"
 
 _BBOX_CACHE: dict[str, object] = {"model_path": None, "model": None, "processor": None}
 _REAL_CACHE: dict[str, object] = {"key": None, "pipeline": None, "transp_vae": None}
@@ -59,9 +60,8 @@ DEFAULT_DECOMP_CKPT_ROOT = Path(
     resolve_existing_path(
         os.environ.get("SYNLAYERS_DECOMP_CKPT_ROOT"),
         PROJECT_ROOT / "SynLayers_ckpt" / "step_120000",
-        "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_ckpt/step_120000",
     )
-    or "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_ckpt/step_120000"
+    or PROJECT_ROOT / "SynLayers_ckpt" / "step_120000"
 )
 
 
@@ -148,7 +148,8 @@ def build_runtime_config(
     seed: int | None = None,
 ) -> dict:
     config = load_config(str(config_path))
-    repo_overrides = build_repo_asset_overrides(os.environ.get("SYNLAYERS_MODEL_REPO"))
+    model_repo = os.environ.get("SYNLAYERS_MODEL_REPO") or DEFAULT_MODEL_REPO_ID
+    repo_overrides = build_repo_asset_overrides(model_repo)
     decomp_ckpt_root = Path(
         os.environ.get("SYNLAYERS_DECOMP_CKPT_ROOT")
         or repo_overrides.get("decomp_ckpt_root")

demo/upload_used_bundle_to_hf.py

@@ -7,7 +7,7 @@ from pathlib import Path
 from huggingface_hub import HfApi
 
 PROJECT_ROOT = Path(__file__).resolve().parents[1]
-SHARE_ROOT = Path("/project/llmsvgen/share/data/kmw_layered_checkpoint")
+ASSET_ROOT = Path(os.environ.get("SYNLAYERS_UPLOAD_ASSET_ROOT", PROJECT_ROOT))
 
 USED_FILE_MAP = {
     PROJECT_ROOT / "demo" / "model_card.md": "README.md",
@@ -47,9 +47,9 @@ REQUIRED_ASSET_FILES = {
 }
 
 REQUIRED_ASSET_FOLDERS = {
-    SHARE_ROOT / "SynLayers_checkpoints" / "FLUX.1-dev": "SynLayers_checkpoints/FLUX.1-dev",
-    SHARE_ROOT / "SynLayers_ckpt" / "step_120000": "SynLayers_ckpt/step_120000",
-    SHARE_ROOT / "SynLayers_checkpoints" / "FLUX.1-dev-Controlnet-Inpainting-Alpha": "SynLayers_checkpoints/FLUX.1-dev-Controlnet-Inpainting-Alpha",
+    ASSET_ROOT / "SynLayers_checkpoints" / "FLUX.1-dev": "SynLayers_checkpoints/FLUX.1-dev",
+    ASSET_ROOT / "SynLayers_ckpt" / "step_120000": "SynLayers_ckpt/step_120000",
+    ASSET_ROOT / "SynLayers_checkpoints" / "FLUX.1-dev-Controlnet-Inpainting-Alpha": "SynLayers_checkpoints/FLUX.1-dev-Controlnet-Inpainting-Alpha",
 }
 
 

infer/infer.yaml

@@ -6,56 +6,33 @@ max_layer_num: 52
 source_size: 1024
 target_size: 1024
 
-# Real-world inference defaults
-data_dir: "/project/llmsvgen/share/data/kmw_layered_dataset/real_world_inference"
-image_dir: "/project/llmsvgen/share/data/kmw_layered_dataset/real_world_inference/layers_real_test_1024"
-test_jsonl: "/project/llmsvgen/share/data/kmw_layered_dataset/real_world_inference/caption_bbox_infer.jsonl"
+# 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: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_checkpoints/FLUX.1-dev"
-pretrained_adapter_path: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_checkpoints/FLUX.1-dev-Controlnet-Inpainting-Alpha"
+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"
 
-# below is for 18k dataset
-#lora_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_18k/step_90000/transformer"
-#layer_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_18k/step_90000"
-#adapter_lora_dir: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_18k/step_90000/adapter"
-
-# below is for 20k dataset
-#lora_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_20k/step_120000/transformer"
-#layer_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_20k/step_120000"
-#adapter_lora_dir: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_20k/step_120000/adapter"
-
-# below is for 30k dataset
-#lora_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_30k/step_150000/transformer"
-#layer_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_30k/step_150000"
-#adapter_lora_dir: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_30k/step_150000/adapter"
-
-# below is for 40k dataset
-#lora_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_40k/step_250000/transformer"
-#layer_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_40k/step_250000"
-#adapter_lora_dir: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_40k/step_250000/adapter"
-
-# below is for 50k dataset
-#lora_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_50k/step_200000/transformer"
-#layer_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_50k/step_200000"
-#adapter_lora_dir: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_train_dataset/ckpt_prism_scaleup_1024_50k/step_200000/adapter"
-
 # unified real-world decomposition checkpoint
-lora_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_ckpt/step_120000/transformer"
-layer_ckpt: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_ckpt/step_120000"
-adapter_lora_dir: "/project/llmsvgen/share/data/kmw_layered_checkpoint/SynLayers_ckpt/step_120000/adapter"
+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: "/project/llmsvgen/share/data/kmw_layered_dataset/real_world_inference/results"
+save_dir: "demo/outputs/real_world_infer/results"
 #run_name: "step_120000"  # optional manual override
 
 # Sample range control (1-based indexing)