docs: add Training data & PII section (submission-guideline compliance)

README.md

@@ -76,6 +76,17 @@ val heatmaps = outputs[0].readFloat()  // [1,32,32,19] -> argmax per keypoint in
 A complete Android sample (camera + gallery, skeleton overlay) is available in
 [google-ai-edge/litert-samples](https://github.com/google-ai-edge/litert-samples).
 
+## Training data & PII
+
+This is a weights-exact format conversion of the public **Lightweight OpenPose** model; no
+new training was performed. It was trained for 2D human-pose estimation on the **COCO 2017
+keypoints** dataset (web photos of people with keypoint annotations). These images contain
+people; the model outputs anonymous keypoint coordinates only and performs no
+identification. No PII was deliberately collected and this conversion adds none. Apply your
+own content/PII handling as appropriate. See the original
+[lightweight-human-pose-estimation](https://github.com/Daniil-Osokin/lightweight-human-pose-estimation.pytorch)
+repo for dataset details.
+
 ## License & attribution
 
 - License: **Apache-2.0**. Weights/model from