The ssd_mobilenet_v1_coco
model is a Single-Shot multibox Detection (SSD) network intended to perform object detection. The difference bewteen this model and the mobilenet-ssd
is that there the mobilenet-ssd
can only detect face, the ssd_mobilenet_v1_coco
model can detect objects.
Metric | Value |
---|---|
Type | Detection |
GFLOPs | 2.494 |
MParams | 6.807 |
Source framework | TensorFlow* |
Metric | Value |
---|---|
coco_precision | 23.3212% |
Image, name - image_tensor
, shape - [1x300x300x3], format [BxHxWxC],
where:
- B - batch size
- H - image height
- W - image width
- C - number of channels
Expected color order - RGB.
Image, name - image_tensor
, shape - [1x3x300x300], format [BxCxHxW],
where:
- B - batch size
- C - number of channels
- H - image height
- W - image width
Expected color order: BGR.
- Classifier, name -
detection_classes
, contains predicted bounding boxes classes in range [1, 91]. The model was trained on Microsoft* COCO dataset version with 90 categories of object. - Probability, name -
detection_scores
, contains probability of detected bounding boxes. - Detection box, name -
detection_boxes
, contains detection boxes coordinates in format[y_min, x_min, y_max, x_max]
, where (x_min
,y_min
) are coordinates top left corner, (x_max
,y_max
) are coordinates right bottom corner. Coordinates are rescaled to input image size. - Detections number, name -
num_detections
, contains the number of predicted detection boxes.
The array of summary detection information, name - DetectionOutput
, shape - [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
- `conf` - confidence for the predicted class
- (`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])
The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in APACHE-2.0-TensorFlow.txt.