ssd512¶

Use Case and High-Level Description¶

The ssd512 model is the Caffe* framework implementation of Single-Shot multibox Detection (SSD) algorithm with 512x512 input resolution and VGG-16 backbone. The network intended to perform visual object detection. This model is pretrained on VOC2007 + VOC2012 + COCO dataset and is able to detect 20 PASCAL VOC2007 object classes:

Person: person
Animal: bird, cat, cow, dog, horse, sheep
Vehicle: aeroplane, bicycle, boat, bus, car, motorbike, train
Indoor: bottle, chair, dining table, potted plant, sofa, tv/monitor

Mapping model labels to class names provided in <omz_dir>/data/dataset_classes/voc_20cl_bkgr.txt file.

For details about this model, check out the repository.

Example¶

See here.

Specification¶

Metric	Value
Type	Detection
GFLOPs	180.611
MParams	27.189
Source framework	Caffe*

Accuracy¶

The accuracy results were obtained on test data from VOC2007 dataset.

Metric	Value
mAP	91.07%

Input¶

Original model¶

Image, name - data, shape - 1, 3, 512, 512, format is B, C, H, W, where:

B - batch size
C - channel
H - height
W - width

Channel order is BGR. Mean values - [104.0, 117.0, 123.0]

Converted model¶

Image, name - data, shape - 1, 3, 512, 512, format is B, C, H, W, where:

B - batch size
C - channel
H - height
W - width

Channel order is BGR.

Output¶

Original model¶

The array of detection summary info, name - detection_out, shape - 1, 1, 200, 7 in the format 1, 1, N, 7, where N is the number of detected bounding boxes. For each detection, the description has the format: [image_id, label, conf, x_min, y_min, x_max, y_max], where:

image_id - ID of the image in the batch
label - predicted class ID (1..20 - PASCAL VOC defined class ids). Mapping to class names provided by <omz_dir>/data/dataset_classes/voc_20cl_bkgr.txt file.
conf - confidence for the predicted class, in [0, 1] range
(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])

Converted model¶

image_id - ID of the image in the batch
label - predicted class ID (1..20 - PASCAL VOC defined class ids). Mapping to class names provided by <omz_dir>/data/dataset_classes/voc_20cl_bkgr.txt file.
conf - confidence for the predicted class, in [0, 1] range
(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])

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:

Legal Information¶

The original model is distributed under the following license:

COPYRIGHT

All new contributions compared to the original branch:
Copyright (c) 2015, 2016 Wei Liu (UNC Chapel Hill), Dragomir Anguelov (Zoox),
Dumitru Erhan (Google), Christian Szegedy (Google), Scott Reed (UMich Ann Arbor),
Cheng-Yang Fu (UNC Chapel Hill), Alexander C. Berg (UNC Chapel Hill).
All rights reserved.

All contributions by the University of California:
Copyright (c) 2014, 2015, The Regents of the University of California (Regents)
All rights reserved.

All other contributions:
Copyright (c) 2014, 2015, the respective contributors
All rights reserved.

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their contributions to Caffe. The project versioning records all such
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their copyright solely in the commit message of the change when it is
committed.

LICENSE

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