[Jetson target detection SSD-MobileNet application example] (2) Make your own data set--collection, labeling, and preprocessing of the data set - 코드 세계

[Jetson target detection SSD-MobileNet application example] (2) Make your own data set--collection, labeling, and preprocessing of the data set

발 2023-06-05 11:00:59 독서 시간: null

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출처blog.csdn.net/weixin_47407066/article/details/126262866

[Jetson target detection SSD-MobileNet application example] (2) Make your own data set--collection, labeling, and preprocessing of the data set

[Jetson target detection SSD-MobileNet application example] (2) Make your own data set--collection, labeling, and preprocessing of the data set

[Jetson target detection SSD-MobileNet application example] (2) Make your own data set--collection, labeling, and preprocessing of the data set

[Jetson target detection SSD-MobileNet application example] (2) Make your own data set--collection, labeling, and preprocessing of the data set

[Jetson target detection SSD-MobileNet application example] (2) Make your own data set--collection, labeling, and preprocessing of the data set

[Target Detection] Visdrone data set and CARPK data set preprocessing

[Jetson target detection SSD-MobileNet application example] (3) Training your own detection model and reasoning test

Target detection data preprocessing - grid puzzles of various image sizes with labels

【Image captioning】File preprocessing of Meshed-memory transformer’s own data set

[yolov7 series 3] Build and train your own data set from 0 in actual combat

YOLO target detection - dim vehicle data set + annotated VOC format tag download and share

YOLO target detection - red fire ant recognition data set + labeled yolo format tag download and share

YOLO target detection - cotton pests and diseases data set + annotated txt format tag download and share

YOLO target detection - complex scene pedestrian data set + labeled voc format tag download and share

[Jetson target detection SSD-MobileNet application example] (4) Use the CSI camera on Jetson to perform video inference and output detection results

Target detection data preprocessing - component screenshots, external expansion according to random proportions

Get the number closest to the target value in a set of data based on the target value

KNN-Taking the iris data set as an example

How to use your own data set to quickly implement any semantic segmentation algorithm and algorithm improvement in the mmsegmentation algorithm library (1)

[Target Detection] YOLOv5: Modify your own network structure

Video and AI, interacting with the process (2) pytorch minimally trains its own data set and recognizes it

Use the pre-trained model of TensorFlow Object Detection API to train your own data

[Target Detection] Visdrone data set and CARPK data set preprocessing

[Target Detection] Visdrone data set and CARPK data set preprocessing

[Target Detection] Visdrone data set and CARPK data set preprocessing

[Target Detection] Visdrone data set and CARPK data set preprocessing

[Target Detection] Visdrone data set and CARPK data set preprocessing

[Target Detection] Visdrone data set and CARPK data set preprocessing

yolov3 trains its own data set (MMDetection)

nanodet-plus trains its own data set

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