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README.md

@@ -31,6 +31,43 @@ The full SynLayers system has two stages:
 
 This repository is intended for the SynLayers decomposition pipeline. It is not meant to be loaded as a single generic `DiffusionPipeline(prompt)` model.
 
+## Stage 2 Inference
+
+The standalone Stage 2 entrypoint is:
+
+- `infer/infer.py`
+- `infer/infer.yaml`
+
+Stage 2 expects images plus a JSONL file containing the whole-image caption and bounding boxes. The easiest way to get those inputs is to run Stage 1 first with [`SynLayers/Bbox-caption-8b`](https://huggingface.co/SynLayers/Bbox-caption-8b), or use the public Space for the full two-stage pipeline.
+
+After preparing your inputs, update these fields in `infer/infer.yaml`:
+
+```yaml
+data_dir: "path/to/your/work_dir"
+image_dir: "path/to/your/images"
+test_jsonl: "path/to/caption_bbox_infer.jsonl"
+save_dir: "path/to/save/results"
+```
+
+Then run:
+
+```bash
+python infer/infer.py \
+  --config_path infer/infer.yaml
+```
+
+The default checkpoint paths in `infer/infer.yaml` are repo-relative and point to the assets in this repository:
+
+```yaml
+pretrained_model_name_or_path: "SynLayers_checkpoints/FLUX.1-dev"
+pretrained_adapter_path: "SynLayers_checkpoints/FLUX.1-dev-Controlnet-Inpainting-Alpha"
+lora_ckpt: "SynLayers_ckpt/step_120000/transformer"
+layer_ckpt: "SynLayers_ckpt/step_120000"
+adapter_lora_dir: "SynLayers_ckpt/step_120000/adapter"
+```
+
+For most users, the public Space is the recommended interface because it runs both Stage 1 and Stage 2 in one workflow.
+
 For more details, please check our paper:
 [https://arxiv.org/abs/2605.15167](https://arxiv.org/abs/2605.15167)