v0.30.5

See https://github.com/quic/ai-hub-models/releases/v0.30.5 for changelog.

README.md

@@ -11,13 +11,9 @@ pipeline_tag: object-detection
 ![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/face_det_lite/web-assets/model_demo.png)
 
 # Lightweight-Face-Detection: Optimized for Mobile Deployment
-## face_det_lite is a face detection model
-
-
-face_det_lite is a machine learning model that detect face in the images
-
-This model is an implementation of Lightweight-Face-Detection found [here](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/face_det_lite/model.py).
+## Lightweight and efficient face detector
 
+A small and accurate model for detecting bounding boxes for faces in images. This model's architecture was developed by Qualcomm. The model was trained by Qualcomm on a proprietary dataset of faces, but can be used on any image.
 
 This repository provides scripts to run Lightweight-Face-Detection on Qualcomm® devices.
 More details on model performance across various devices, can be found
@@ -237,13 +233,13 @@ AI Hub. [Sign up for access](https://myaccount.qualcomm.com/signup).
 You can also run the demo on-device.
 
 ```bash
-python -m qai_hub_models.models.face_det_lite.demo --on-device
+python -m qai_hub_models.models.face_det_lite.demo --eval-mode on-device
 ```
 
 **NOTE**: If you want running in a Jupyter Notebook or Google Colab like
 environment, please add the following to your cell (instead of the above).
 ```
-%run -m qai_hub_models.models.face_det_lite.demo -- --on-device
+%run -m qai_hub_models.models.face_det_lite.demo -- --eval-mode on-device
 ```
 
 
@@ -273,10 +269,6 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
 
 
 
-## References
-* [Source Model Implementation](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/face_det_lite/model.py)
-
-
 
 ## Community
 * Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.