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SSD MobileNet v1 FP32

Description

SSD MobileNet v1 is a object detection network, that localizes and identifies objects in an input image. This is a TF Lite floating point version that takes a 300x300 input image and outputs detections for this image. This model is trained by Google.

License

Apache-2.0

Related Materials

Class Labels

The class labels associated with this model can be downloaded by running the script get_class_labels.sh.

Model Recreation Code

Code to recreate this model can be found here.

How-To Guide

A guide on how to deploy this model using the Arm NN SDK can be found here.

Network Information

Network Information Value
Framework TensorFlow Lite
SHA-1 Hash 5bd511fc17ec7bfe9cd0f51bdec1537b874f52d2
Size (Bytes) 27286108
Provenance http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_coco_2018_01_28.tar.gz
Paper https://arxiv.org/abs/1512.02325

Accuracy

Dataset: Coco Validation 2017

Metric Value
mAP 0.210

Performance

Platform Optimized
Cortex-A ✔️
Cortex-M ✖️
Mali GPU ✔️
Ethos U ✖️

Key

  • ✔️ - Will run on this platform.
  • ✖️ - Will not run on this platform.

Network Inputs

Input Node Name Shape Description
normalized_input_image_tensor (1, 300, 300, 3) A float input image.

Network Outputs

Output Node Name Shape Description
TFLite_Detection_PostProcess () An array of num_detection box boundaries for each input in the format (y1, x1, y2, x2) scaled from 0 to 1.
TFLite_Detection_PostProcess:1 () COCO detection classes for each object. 1=person, 11=fire hydrant.
TFLite_Detection_PostProcess:2 () Detection scores for each object.
TFLite_Detection_PostProcess:3 () The number of objects detected in each image.