Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+library_name: onnxruntime
+tags:
+- onnx
+- onnxruntime
+- face-recognition
+- face-embedding
+- computer-vision
+---
+
+# VirtuoTuring Face Embedder
+
+ONNX model for generating facial embeddings and comparing two faces.
+
+## What it does
+This model takes an aligned face as input and returns a 512-dimensional facial embedding.
+
+## Expected input
+- RGB image
+- cropped/aligned face
+- size: 112x112
+- type: float32
+- normalization: [-1, 1]
+
+## Output
+- 512-dimensional float32 embedding
+
+## Comparison
+Compare embeddings using cosine similarity.
+
+Suggested initial threshold:
+- 0.93
+
+## Limitations
+- it does not perform face detection on its own
+- it assumes the face is already cropped/aligned
+- it is not a certified biometric system
+- it may fail with extreme pose, occlusions, poor lighting, or partial faces
+
+## Files
+- `virtuoturing.onnx`
+- external weights file `.data`
+
+## Usage example
+```python
+import onnxruntime as ort
+sess = ort.InferenceSession("virtuoturing.onnx")
+print(sess.get_inputs()[0].name, sess.get_inputs()[0].shape)
+print(sess.get_outputs()[0].name, sess.get_outputs()[0].shape)