ultra-lightweight-face-detection-slim-320#

Use Case and High-Level Description#

Ultra-lightweight Face Detection slim 320 is a version of the lightweight face detection model with network backbone simplification. The model designed for edge computing devices and pre-trained on the WIDER FACE dataset with 320x240 input resolutions.

For details see repository.

Specification#

Metric

Value

Type

Object detection

GFLOPs

0.1724

MParams

0.2844

Source framework

PyTorch*

Accuracy#

Metric

Value

mAP

83.32%

Input#

Original model#

Image, name - input, shape - 1, 3, 240, 320, format B, C, H, W, where:

  • B - batch size

  • C - number of channels

  • H - image height

  • W - image width

Expected color order is RGB.

Mean values - [127.0, 127.0, 127.0]. Scale values - [128.0, 128.0, 128.0].

Converted model#

Image, name - input, shape - 1, 3, 240, 320, format B, C, H, W, where:

  • B - batch size

  • C - number of channels

  • H - image height

  • W - image width

Expected color order is BGR.

Output#

Original model#

  1. Bounding boxes, name: boxes, shape - 1, 4420, 4. Presented in format B, A, 4, where:

    • B - batch size

    • A - number of detected anchors

    For each detection, the description has the format: [x_min, y_min, x_max, y_max], where:

    • (x_min, y_min) - coordinates of the top left bounding box corner (coordinates are in normalized format, in range [0, 1])

    • (x_max, y_max) - coordinates of the bottom right bounding box corner (coordinates are in normalized format, in range [0, 1])

  2. Scores, name: scores, shape - 1, 4420, 2. Contains scores for 2 classes - the first is background, the second is face.

Converted model#

  1. Bounding boxes, name: boxes, shape - 1, 4420, 4. Presented in format B, A, 4, where:

    • B - batch size

    • A - number of detected anchors

    For each detection, the description has the format: [x_min, y_min, x_max, y_max], where:

    • (x_min, y_min) - coordinates of the top left bounding box corner (coordinates are in normalized format, in range [0, 1])

    • (x_max, y_max) - coordinates of the bottom right bounding box corner (coordinates are in normalized format, in range [0, 1])

  2. Scores, name: scores, shape - 1, 4420, 2. Contains scores for 2 classes - the first is background, the second is face.

Download a Model and Convert it into OpenVINO™ IR Format#

You can download models and if necessary convert them into OpenVINO™ IR format using the Model Downloader and other automation tools as shown in the examples below.

An example of using the Model Downloader:

omz_downloader --name <model_name>

An example of using the Model Converter:

omz_converter --name <model_name>

Demo usage#

The model can be used in the following demos provided by the Open Model Zoo to show its capabilities: