Update README.md

README.md

@@ -31,7 +31,33 @@ Compare embeddings using cosine similarity.
 
 Suggested initial threshold:
 - 0.93
+- 
+## Training data
 
+This model was trained on a curated dataset of 23,660 face images.
+
+The dataset contains cropped and aligned face images and was assembled to include variation in apparent age, sex presentation, accessories, and appearance, including examples with hats and glasses.
+
+The training set was built from sources that were identified by the curator as providing permissive reuse terms and/or explicit permission for access and reuse. Where images were discovered through search engines, they were not treated as licensed merely because they appeared in search results; inclusion was intended only where the original source indicated free-use terms, permissive licensing, or other documented authorization.
+
+## Data provenance and legal notice
+
+Face images may constitute personal data and, when used for face recognition or identity-related processing, may fall within the scope of biometric data under applicable data protection law. Accordingly, this model card should not be read as a blanket statement that any downstream use is lawful in every jurisdiction.
+
+The publisher represents that the dataset curation process sought to limit training data to images believed to be available under free-use terms and/or explicit authorization. However, users remain responsible for conducting their own legal review regarding copyright, privacy, data protection, biometric-data compliance, and any sector-specific rules that may apply in their jurisdiction.
+
+## Preprocessing
+
+All training images were face-cropped and aligned before training. The model expects:
+- RGB face image
+- cropped/aligned face
+- size: 112x112
+- dtype: float32
+- normalization: [-1, 1]
+
+## Limitations
+
+This model does not perform face detection on its own and assumes that the face is already cropped and aligned. It is not a certified biometric identification system and may perform poorly under extreme pose, occlusion, poor lighting, or partial-face conditions.
 ## Limitations
 - it does not perform face detection on its own
 - it assumes the face is already cropped/aligned