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STMicroelectronics/
st_yolo_x

object-detection

1405.0312

other

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ST Yolo X quantized

Use case : `Object detection`

Model description

ST Yolo X is a real-time object detection model targeted for real-time processing implemented in Tensorflow. This is an optimized ST version of the well known yolo x, quantized in int8 format using tensorflow lite converter.

Network information

Network information	Value
Framework	TensorFlow Lite
Quantization	int8
Provenance
Paper

Network inputs / outputs

For an image resolution of NxM and NC classes

Input Shape	Description
(1, W, H, 3)	Single NxM RGB image with UINT8 values between 0 and 255

Output Shape	Description

Recommended Platforms

Platform	Supported	Recommended
STM32L0	[]	[]
STM32L4	[]	[]
STM32U5	[]	[]
STM32H7	[x]	[]
STM32MP1	[x]	[]
STM32MP2	[x]	[x]
STM32N6	[x]	[x]

Performances

Metrics

Measures are done with default STM32Cube.AI configuration with enabled input / output allocated option.

Reference NPU memory footprint based on COCO Person dataset (see Accuracy for details on dataset)

Model	Hyperparameters (depth_width)	Dataset	Format	Resolution	Series	Internal RAM (KiB)	Weights Flash (KiB)	STEdgeAI Core version
st_yoloxn	d033_w025	COCO-Person	Int8	192x192x3	STM32N6	333	877.66	3.0.0
st_yoloxn	d033_w025	COCO-Person	Int8	256x256x3	STM32N6	624	884.91	3.0.0
st_yoloxn	d033_w025	COCO-Person	Int8	320x320x3	STM32N6	1125	895.03	3.0.0
st_yoloxn	d033_w025	COCO-Person	Int8	416x416x3	STM32N6	2676.12	904.03	3.0.0
st_yoloxn	d050_w040	COCO-Person	Int8	256x256x3	STM32N6	833	2414.64	3.0.0
st_yoloxn	d100_w025	COCO-Person	Int8	480x480x3	STM32N6	2707.5	1173.25	3.0.0
st_yoloxn	d033_w025	ST-Person	Int8	416x416x3	STM32N6	2676.12	906.28	3.0.0
st_yoloxn	d067_w025	ST-Person	Int8	416x416x3	STM32N6	2681.41	1039.78	3.0.0
st_yoloxn	d100_w025	ST-Person	Int8	416x416x3	STM32N6	2676.12	1173.28	3.0.0
st_yoloxn	d100_w025	ST-Person	Int8	480x480x3	STM32N6	2707.5	1173.25	3.0.0
st_yoloxn	d100_w025	ST-Person	W4A8	480x480x3	STM32N6	2593	738.53	3.0.0
st_yoloxn	d100_w025	COCO-80-classes	W4A8	480x480x3	STM32N6	3491.48	1217.59	3.0.0
st_yoloxn	d033_w025	COCO-Person	W4A8	192x192x3	STM32N6	360	519.06	3.0.0
st_yoloxn	d033_w025	COCO-Person	W4A8	256x256x3	STM32N6	624	526.31	3.0.0
st_yoloxn	d033_w025	COCO-Person	W4A8	320x320x3	STM32N6	1125	638.67	3.0.0
st_yoloxn	d033_w025	COCO-Person	W4A8	416x416x3	STM32N6	2670.84	575.53	3.0.0
st_yoloxn	d050_w040	COCO-Person	W4A8	256x256x3	STM32N6	835	1671.08	3.0.0
st_yoloxn	d100_w025	COCO-Person	W4A8	480x480x3	STM32N6	2707.5	868.8	3.0.0

Reference NPU inference time based on COCO Person dataset (see Accuracy for details on dataset)

Model	Hyperparameters (depth_width)	Dataset	Format	Resolution	Board	Execution Engine	Inference time (ms)	Inf / sec	STEdgeAI Core version
st_yoloxn	d033_w025	COCO-Person	Int8	192x192x3	STM32N6570-DK	NPU/MCU	6.63	150.74	3.0.0
st_yoloxn	d033_w025	COCO-Person	Int8	256x256x3	STM32N6570-DK	NPU/MCU	9.42	106.17	3.0.0
st_yoloxn	d033_w025	COCO-Person	Int8	320x320x3	STM32N6570-DK	NPU/MCU	13.29	75.26	3.0.0
st_yoloxn	d033_w025	COCO-Person	Int8	416x416x3	STM32N6570-DK	NPU/MCU	21.3	46.95	3.0.0
st_yoloxn	d050_w040	COCO-Person	Int8	256x256x3	STM32N6570-DK	NPU/MCU	20.12	49.70	3.0.0
st_yoloxn	d100_w025	COCO-Person	Int8	480x480x3	STM32N6570-DK	NPU/MCU	35.8	27.93	3.0.0
st_yoloxn	d033_w025	ST-Person	Int8	416x416x3	STM32N6570-DK	NPU/MCU	21.66	46.16	3.0.0
st_yoloxn	d067_w025	ST-Person	Int8	416x416x3	STM32N6570-DK	NPU/MCU	24.37	41.02	3.0.0
st_yoloxn	d100_w025	ST-Person	Int8	416x416x3	STM32N6570-DK	NPU/MCU	27.02	36.99	3.0.0
st_yoloxn	d100_w025	ST-Person	Int8	480x480x3	STM32N6570-DK	NPU/MCU	35.8	27.93	3.0.0
st_yoloxn	d100_w025	ST-Person	W4A8	480x480x3	STM32N6570-DK	NPU/MCU	34.27	29.18	3.0.0
st_yoloxn	d100_w025	COCO-80-classes	W4A8	480x480x3	STM32N6570-DK	NPU/MCU	49.34	20.27	3.0.0
st_yoloxn	d033_w025	COCO-Person	W4A8	192x192x3	STM32N6570-DK	NPU/MCU	6.33	157.96	3.0.0
st_yoloxn	d033_w025	COCO-Person	W4A8	256x256x3	STM32N6570-DK	NPU/MCU	8.20	121.95	3.0.0
st_yoloxn	d033_w025	COCO-Person	W4A8	320x320x3	STM32N6570-DK	NPU/MCU	11.82	84.66	3.0.0
st_yoloxn	d033_w025	COCO-Person	W4A8	416x416x3	STM32N6570-DK	NPU/MCU	19.87	50.32	3.0.0
st_yoloxn	d050_w040	COCO-Person	W4A8	256x256x3	STM32N6570-DK	NPU/MCU	18.34	54.52	3.0.0
st_yoloxn	d100_w025	COCO-Person	W4A8	480x480x3	STM32N6570-DK	NPU/MCU	34.71	28.80	3.0.0

Reference MCU memory footprint based on COCO Person dataset (see Accuracy for details on dataset)

Model	Hyperparameters (depth_width)	Format	Resolution	Series	Activation RAM (KiB)	Runtime RAM (KiB)	Weights Flash (KiB)	Code Flash (KiB)	Total RAM	Total Flash	STEdgeAI Core version
st_yoloxn	d033_w025	Int8	192x192x3	STM32H7	184.92	12.54	891.18	108.38	197.46	999.56	3.0.0
st_yoloxn	d033_w025	Int8	256x256x3	STM32H7	324.92	12.54	891.18	108.38	337.46	999.84	3.0.0
st_yoloxn	d050_w040	Int8	256x256x3	STM32H7	451.4	15.63	2435.76	151.42	467.03	2587.18	3.0.0
st_yoloxn	d033_w025	Int8	320x320x3	STM32H7	504.92	12.54	891.18	108.38	517.46	1000.04	3.0.0
st_yoloxn	d033_w025	Int8	416x416x3	STM32H7	849.92	12.54	891.18	108.38	862.46	999.99	3.0.0

Reference MCU inference time based on COCO Person dataset (see Accuracy for details on dataset)

Model	Hyperparameters (depth_width)	Format	Resolution	Board	Execution Engine	Frequency	Inference time (ms)	STEdgeAI Core version
st_yoloxn	d033_w025	Int8	192x192x3	STM32H747I-DISCO	1 CPU	400 MHz	357.79	3.0.0
st_yoloxn	d033_w025	Int8	256x256x3	STM32H747I-DISCO	1 CPU	400 MHz	641.66	3.0.0
st_yoloxn	d050_w040	Int8	256x256x3	STM32H747I-DISCO	1 CPU	400 MHz	1698.36	3.0.0
st_yoloxn	d033_w025	Int8	320x320x3	STM32H747I-DISCO	1 CPU	400 MHz	1026.35	3.0.0
st_yoloxn	d033_w025	Int8	416x416x3	STM32H747I-DISCO	1 CPU	400 MHz	1797.73	3.0.0

AP on COCO Person dataset

Dataset details: link , License CC BY 4.0 , Quotation[1] , Number of classes: 80, Number of images: 118,287

Model	Hyperparameters (depth_width)	Format	Resolution	Depth Multiplier	Width Multiplier	Anchors	AP
st_yoloxn	d033_w025	Int8	192x192x3	0.33	0.25	1	38.16 %
st_yoloxn	d033_w025	Float	192x192x3	0.33	0.25	1	38.82 %
st_yoloxn	d033_w025	W4A8	192x192x3	0.33	0.25	1	37.34 %
st_yoloxn	d033_w025	Int8	256x256x3	0.33	0.25	1	44.85 %
st_yoloxn	d033_w025	Float	256x256x3	0.33	0.25	1	45.12 %
st_yoloxn	d033_w025	W4A8	192x192x3	0.33	0.25	1	44.43 %
st_yoloxn	d050_w040	Int8	256x256x3	0.5	0.4	1	50.05 %
st_yoloxn	d050_w040	Float	256x256x3	0.5	0.4	1	51.07 %
st_yoloxn	d050_w040	W4A8	256x256x3	0.33	0.25	1	49.2 %
st_yoloxn	d033_w025	Int8	320x320x3	0.33	0.25	1	51.17 %
st_yoloxn	d033_w025	Float	320x320x3	0.33	0.25	1	51.69 %
st_yoloxn	d033_w025	W4A8	320x320x3	0.33	0.25	1	50.61 %
st_yoloxn	d033_w025	Int8	416x416x3	0.33	0.25	1	54.8 %
st_yoloxn	d033_w025	Float	416x416x3	0.33	0.25	1	54.82 %
st_yoloxn	d033_w025	W4A8	416x416x3	0.33	0.25	1	53.97 %
st_yoloxn	d100_w025	Int8	480x480x3	1.0	0.25	3	61.1 %
st_yoloxn	d100_w025	Float	480x480x3	1.0	0.25	3	61.7 %
st_yoloxn	d100_w025	W4A8	480x480x3	0.33	0.25	1	59.9 %
st_yoloxn	d033_w025	Int8	416x416x3	0.33	0.25	1	42.58 %
st_yoloxn	d033_w025	Float	416x416x3	0.33	0.25	1	44.28 %
st_yoloxn	d067_w025	Int8	416x416x3	0.67	0.25	1	46.2 %
st_yoloxn	d067_w025	Float	416x416x3	0.67	0.25	1	46.7 %
st_yoloxn	d100_w025	Int8	416x416x3	1.0	0.25	1	47.27 %
st_yoloxn	d100_w025	Float	416x416x3	1.0	0.25	1	48.14 %
st_yoloxn	d100_w025	Int8	480x480x3	1.0	0.25	1	48.15 %
st_yoloxn	d100_w025	Float	480x480x3	1.0	0.25	1	48.68 %
st_yoloxn	d100_w025	W4A8	480x480x3	1.0	0.25	1	47.3 %
st_yoloxn	d100_w025	Int8	480x480x3	1.0	0.25	1	34.3 %
st_yoloxn	d100_w025	Float	480x480x3	1.0	0.25	1	35.7 %

* EVAL_IOU = 0.5, NMS_THRESH = 0.5, SCORE_THRESH = 0.001, MAX_DETECTIONS = 100

Retraining and Integration in a simple example:

Please refer to the stm32ai-modelzoo-services GitHub here

References

[1] “Microsoft COCO: Common Objects in Context”. [Online]. Available: https://cocodataset.org/#download. @article{DBLP:journals/corr/LinMBHPRDZ14, author = {Tsung{-}Yi Lin and Michael Maire and Serge J. Belongie and Lubomir D. Bourdev and Ross B. Girshick and James Hays and Pietro Perona and Deva Ramanan and Piotr Doll{'{a} }r and C. Lawrence Zitnick}, title = {Microsoft {COCO:} Common Objects in Context}, journal = {CoRR}, volume = {abs/1405.0312}, year = {2014}, url = {http://arxiv.org/abs/1405.0312}, archivePrefix = {arXiv}, eprint = {1405.0312}, timestamp = {Mon, 13 Aug 2018 16:48:13 +0200}, biburl = {https://dblp.org/rec/bib/journals/corr/LinMBHPRDZ14}, bibsource = {dblp computer science bibliography, https://dblp.org} }

STMicroelectronics/st_yolo_x