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.
The class labels associated with this model can be downloaded by running the script get_class_labels.sh
.
Code to recreate this model can be found here.
A guide on how to deploy this model using the Arm NN SDK can be found here.
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 |
Dataset: Coco Validation 2017
Metric | Value |
---|---|
mAP | 0.210 |
Platform | Optimized |
---|---|
Cortex-A | ✔️ |
Cortex-M | ✖️ |
Mali GPU | ✔️ |
Ethos U | ✖️ |
- ✔️ - Will run on this platform.
- ✖️ - Will not run on this platform.
Input Node Name | Shape | Description |
---|---|---|
normalized_input_image_tensor | (1, 300, 300, 3) | A float input image. |
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. |