The nanodet-m-1.5x-416 model is one from NanoDet models family, which is a FCOS-style one-stage anchor-free object detection model which using Generalized Focal Loss as classification and regression loss. The model is a super-fast and high accuracy lightweight model with ShuffleNetV2 1.5x backbone. This model was pre-trained on Common Objects in Context (COCO) dataset.
More details provided in the repository.
| Metric | Value |
|---|---|
| Type | Object detection |
| GFLOPs | 2.3895 |
| MParams | 2.0534 |
| Source framework | PyTorch* |
Accuracy metrics obtained on Common Objects in Context (COCO) validation dataset for converted model. Label map with 80 public available object categories are used.
| Metric | Value |
|---|---|
| coco_orig_precision | 27.38% |
| coco_precision | 26.63% |
Image, name - data, shape - 1, 3, 416, 416, format B, C, H, W, where:
B- batch sizeC- number of channelsH- image heightW- image width
Expected color order is BGR.
Mean values - [103.53, 116.28, 123.675]. Scale values - [57.375, 57.12, 58.395].
Image, name - data, shape - 1, 3, 416, 416, format B, C, H, W, where:
B- batch sizeC- number of channelsH- image heightW- image width
Expected color order is BGR.
The array of detection summary info, name - output, shape - 1, 3549, 112, format is B, N, 112, where:
B- batch sizeN- number of detection boxes
Detection box has the following format:
- 80 probability distribution over the classes in logits format for 80 public available Common Objects in Context (COCO) object classes, listed in file
<omz_dir>/data/dataset_classes/coco_80cl.txt. - 8 * 4 raw coordinates in format
A* 4, whereA- max value of integral set.
The array of detection summary info, name - output, shape - 1, 3549, 112, format is B, N, 112, where:
B- batch sizeN- number of detection boxes
Detection box has the following format:
- 80 probability distribution over the classes in logits format for 80 public available Common Objects in Context (COCO) object classes, listed in file
<omz_dir>/data/dataset_classes/coco_80cl.txt. - 8 * 4 raw coordinates in format
A* 4, whereA- max value of integral set.
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>
The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:
The original model is distributed under the
Apache License, Version 2.0.
A copy of the license is provided in <omz_dir>/models/public/licenses/APACHE-2.0-PyTorch-NanoDet.txt.