Use Case and High-Level Description

MobileNetV1 FPN is used for object detection. For details, see the paper.



Metric Value
Type Detection
GFLOPs 123.309
MParams 36.188
Source framework TensorFlow*


Metric Value
coco_precision 35.5453%



Original Model

Image, name: image_tensor, shape: [1x640x640x3], format: [BxHxWxC], where:

Expected color order: RGB.

Converted Model

Image, name: image_tensor, shape: [1x3x640x640], format: [BxCxHxW], where:

Expected color order: BGR.


Original Model

  1. 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, 0 class is for background.
  2. Probability, name: detection_scores. Contains probability of detected bounding boxes.
  3. 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.
  4. 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, 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:

Legal Information

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.