Use Case and High-Level Description¶
Face detector based on MobileNetV2 as a backbone with a multiple SSD head for indoor and outdoor scenes shot by a front-facing camera. During the training of this model, training images were resized to 384x384.
AP ( WIDER )
Average Precision (AP) is defined as an area under the precision/recall curve. All numbers were evaluated by taking into account only faces bigger than 64 x 64 pixels.
1, 3, 384, 384 in the format
B, C, H, W, where:
B- batch size
C- number of channels
H- image height
W- image width
Expected color order:
The net outputs blob with shape:
1, 1, 200, 7 in the format
1, 1, N, 7, where
N is the number of detected bounding boxes. Each detection has the format [
image_id- ID of the image in the batch
label- predicted class ID (0 - face)
conf- confidence for the predicted class
y_min) - coordinates of the top left bounding box corner
y_max) - coordinates of the bottom right bounding box corner
The OpenVINO Training Extensions provide a training pipeline, allowing to fine-tune the model on custom dataset.
The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:
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