YOLO-NAS-Pose-JetPack5

pesi/YOLO-NAS-Pose-JetPack5

YOLO-NAS-Pose-JetPack5 is a object detection model from pesi. Use it when you need objects located in an image.

Downloads · 30 days

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Public

Updated Feb 27, 2024

Repo size

4.6 GB

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Public

Hugging Face

Repo makeup

Click a slice to open those files.

.onnx1.2 GB · 100%

At a glance

Task: Object Detection
Access: Public
Created: Dec 29, 2023
Updated: Feb 27, 2024
SHA: b8d8df3d

Datasets

Mai0313/coco-pose-2017

Model card

From the Hugging Face model README

We offer a TensorRT model in various precisions including int8, fp16, fp32, and mixed, converted from Deci-AI's YOLO-NAS-Pose pre-trained weights (which is only allowed for non-commerical use) in PyTorch. This (TensorRT) model is compatible with JetPack 5.1.1, benchmarked and tested on Jetson Orin Nano Deveoper Kit.

~~Note that all quantization that has been introduced in the conversion is purely static, meaning that the corresponding model has potentillay bad accuracy compared to the original one.~~

Todo: ~~use cppe-5 dataset to calibrate int8 model~~

More information on calibration for post-training quantization, check this slide

Large

Model Name	ONNX Precision	TensorRT Preicion	Throughput (TensorRT)
yolo_nas_pose_l_fp16.onnx.best.engine	FP16	FP32+FP16+INT8	46.7231 qps
yolo_nas_pose_l_fp16.onnx.fp16.engine	FP16	FP32+FP16	29.6093 qps
yolo_nas_pose_l_fp32.onnx.best.engine	FP32	FP32+FP16+INT8	47.4032 qps
yolo_nas_pose_l_fp32.onnx.engine	FP32	FP32	15.0654 qps
yolo_nas_pose_l_fp32.onnx.fp16.engine	FP32	FP32+FP16	29.0005 qps
yolo_nas_pose_l_fp32.onnx.int8.engine	FP32	FP32+INT8	47.9071 qps
yolo_nas_pose_l_int8.onnx.best.engine	INT8	FP32+FP16+INT8	36.9695 qps
yolo_nas_pose_l_int8.onnx.int8.engine	INT8	FP32+INT8	30.9676 qps

Medium

Model Name	ONNX Precision	TensorRT Preicion	Throughput (TensorRT)
yolo_nas_pose_m_fp16.onnx.best.engine	FP16	FP32+FP16+INT8	58.254 qps
yolo_nas_pose_m_fp16.onnx.fp16.engine	FP16	FP32+FP16	37.8547 qps
yolo_nas_pose_m_fp32.onnx.best.engine	FP32	FP32+FP16+INT8	58.0306 qps
yolo_nas_pose_m_fp32.onnx.engine	FP32	FP32	18.9603 qps
yolo_nas_pose_m_fp32.onnx.fp16.engine	FP32	FP32+FP16	37.193 qps
yolo_nas_pose_m_fp32.onnx.int8.engine	FP32	FP32+INT8	59.9746 qps
yolo_nas_pose_m_int8.onnx.best.engine	INT8	FP32+FP16+INT8	44.8046 qps
yolo_nas_pose_m_int8.onnx.int8.engine	INT8	FP32+INT8	38.6757 qps

Small

Model Name	ONNX Precision	TensorRT Preicion	Throughput (TensorRT)
yolo_nas_pose_s_fp16.onnx.best.engine	FP16	FP32+FP16+INT8	84.7072 qps
yolo_nas_pose_s_fp16.onnx.fp16.engine	FP16	FP32+FP16	66.0151 qps
yolo_nas_pose_s_fp32.onnx.best.engine	FP32	FP32+FP16+INT8	85.5718 qps
yolo_nas_pose_s_fp32.onnx.engine	FP32	FP32	33.5963 qps
yolo_nas_pose_s_fp32.onnx.fp16.engine	FP32	FP32+FP16	65.4357 qps
yolo_nas_pose_s_fp32.onnx.int8.engine	FP32	FP32+INT8	86.3202 qps
yolo_nas_pose_s_int8.onnx.best.engine	INT8	FP32+FP16+INT8	74.2494 qps
yolo_nas_pose_s_int8.onnx.int8.engine	INT8	FP32+INT8	63.7546 qps

Nano

Model Name	ONNX Precision	TensorRT Preicion	Throughput (TensorRT)
yolo_nas_pose_n_fp16.onnx.best.engine	FP16	FP32+FP16+INT8	91.8287 qps
yolo_nas_pose_n_fp16.onnx.fp16.engine	FP16	FP32+FP16	85.4187 qps
yolo_nas_pose_n_fp32.onnx.best.engine	FP32	FP32+FP16+INT8	105.519 qps
yolo_nas_pose_n_fp32.onnx.engine	FP32	FP32	47.8265 qps
yolo_nas_pose_n_fp32.onnx.fp16.engine	FP32	FP32+FP16	82.3834 qps
yolo_nas_pose_n_fp32.onnx.int8.engine	FP32	FP32+INT8	88.0719 qps
yolo_nas_pose_n_int8.onnx.best.engine	INT8	FP32+FP16+INT8	80.8271 qps
yolo_nas_pose_n_int8.onnx.int8.engine	INT8	FP32+INT8	74.2658 qps

alt text

Task: Object Detection
Created: Dec 29, 2023
Updated: Feb 27, 2024