Update README.md

README.md

@@ -7,4 +7,25 @@ tags:
 - 2D_Pose_Estimation
 - MMPOSE
 - RTMO
----
+---
+
+# Retrainable RTMO-s Model
+
+This repository provides a fully **retrainable** RTMO-s checkpoint for 2D human pose estimation in the MMPOSE framework.
+
+The RTMO one-stage model family (variants T, S, M, L) was originally released by the OpenMMLab team with pre-trained weights, but those official PyTorch `.pth` checkpoints do **not** preserve all parameter keys—making fine-tuning or re-training impossible within MMPOSE (see [discussion #3076](https://github.com/open-mmlab/mmpose/discussions/3076)).  
+
+To address this limitation, PESI has faithfully reproduced the RTMO-s training procedure on the MS COCO 2017 dataset using the exact configuration from the official MMPOSE RTMO project. Our checkpoint preserves every model key, enabling you to fine-tune on custom datasets (e.g. Body7, MPII) or continue training from this strong baseline.
+
+- **Original implementation & configs**: [MMPOSE RTMO project](https://github.com/open-mmlab/mmpose/tree/main/projects/rtmo)  
+- **Issue on missing keys**: [MMPOSE #3076](https://github.com/open-mmlab/mmpose/discussions/3076)  
+
+## Key Features
+
+- **One-stage RTMO-s architecture** as described in the MMPOSE RTMO project  
+- **All keys retained** in the PyTorch checkpoint for full retrainability (unlike the official weights)  
+
+## References
+
+1. OpenMMLab MMPOSE RTMO project: “RTMO: Real-time One-Stage Multi-person Pose Estimation”  
+2. Issue discussion on missing keys in official RTMO checkpoints