tflite_uint8

SSD MobileNet v1 UINT8

Description

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

Network Information

Network Information	Value
Framework	TensorFlow Lite
SHA-1 Hash	1f9c945db9e32c33e5b91539f756a8fbef636405
Size (Bytes)	6898880
Provenance	http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_quantized_300x300_coco14_sync_2018_07_18.tar.gz
Paper	https://arxiv.org/abs/1512.02325

Accuracy

Dataset: Coco Validation 2017

Metric	Value
mAP	0.180

Performance

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

Key

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

Optimizations

Optimization	Value
Quantization	UINT8

Network Inputs

Input Node Name	Shape	Description
normalized_input_image_tensor	(1, 300, 300, 3)	Input RGB images (a range of 0-255 per RGB channel).

Network Outputs

Output Node Name	Shape	Description
TFLite_Detection_PostProcess	()	The y1, x1, y2, x2 coordinates of the bounding boxes for each detection
TFLite_Detection_PostProcess:1	()	The class of each detection
TFLite_Detection_PostProcess:2	()	The probability score for each classification
TFLite_Detection_PostProcess:3	()	A vector containing a number corresponding to the number of detections