ssd_mobilenet_v1_fpn_coco¶
Use Case and High-Level Description¶
MobileNetV1 FPN is used for object detection. For details, see the paper.
Specification¶
Metric |
Value |
---|---|
Type |
Detection |
GFLOPs |
123.309 |
MParams |
36.188 |
Source framework |
TensorFlow* |
Accuracy¶
Metric |
Value |
---|---|
coco_precision |
35.5453% |
Input¶
Original Model¶
Image, name: image_tensor
, shape: 1, 640, 640, 3
, format: B, H, W, C
, where:
B
- batch sizeH
- image heightW
- image widthC
- number of channels
Expected color order: RGB
.
Converted Model¶
Image, name: image_tensor
, shape: 1, 3, 640, 640
, format: B, C, H, W
, where:
B
- batch sizeC
- number of channelsH
- image heightW
- image width
Expected color order: BGR
.
Output¶
Original Model¶
Classifier, name:
detection_classes
. Contains predicted bounding-boxes classes in range [1, 91]. The model was trained on Common Objects in Context (COCO) dataset version with 91 categories of object, 0 class is for background. Mapping to class names provided in<omz_dir>/data/dataset_classes/coco_91cl_bkgr.txt
file.Probability, name:
detection_scores
. Contains probability of detected bounding boxes.Detection box, name:
detection_boxes
. Contains detection-boxes coordinates in the following format:[y_min, x_min, y_max, x_max]
, where(x_min
,y_min
) are coordinates of the top left corner, (x_max
,y_max
) are coordinates of the right bottom corner.Coordinates are rescaled to an input image size.Detections number, name:
num_detections
. Contains the number of predicted detection boxes.
Converted Model¶
The array of summary detection information, name: DetectionOutput
, shape: 1, 1, 100, 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 batchlabel
- ID of the predicted classconf
- confidence for the predicted class in range [1, 91], mapping to class names provided in<omz_dir>/data/dataset_classes/coco_91cl.txt
file.(
x_min
,y_min
) - coordinates of the top left bounding box corner (coordinates stored in normalized format, in range [0, 1])(
x_max
,y_max
) - coordinates of the bottom right bounding box corner (coordinates stored in normalized format, in range [0, 1])
Download a Model and Convert it into Inference Engine Format¶
You can download models and if necessary convert them into Inference Engine format using the Model Downloader and other automation tools as shown in the examples below.
An example of using the Model Downloader:
python3 <omz_dir>/tools/downloader/downloader.py --name <model_name>
An example of using the Model Converter:
python3 <omz_dir>/tools/downloader/converter.py --name <model_name>
Legal Information¶
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-TF-Models.txt
.