Overview of target detection tasks and download of commonly used data sets

Target detection task purpose

In the field of computer vision, target detection refers to detecting and locating multiple target objects of interest in images or videos, and assigning corresponding category labels to each target object.

Target detection task data set

Datasets for object detection tasks play an important role in the training and evaluation of algorithms. The following are some commonly used target detection data sets:

• COCO (Common Objects in Context): The COCO dataset is a widely used object detection and segmentation dataset, containing more than 80 categories of objects. The data set provides rich annotation information and is suitable for a variety of tasks. link

• Pascal VOC: The Pascal VOC data set is a classic target detection data set, containing 20 categories of target objects. It provides a rich set of training and test images and is widely used for algorithm evaluation. link

• KITTI: The KITTI data set is mainly used for target detection and positioning tasks in autonomous driving scenarios. It contains images, point clouds and annotation information in urban driving scenes. link
  For details on how to divide the data set after obtaining it, see yolo format data set filtering

Target detection model

The current models are mainly rcnn and yolo. The more classic models include Fast RCNNPaper address, yolov5, etc., based on transformer The model structure includes DETRpaper addressetc.

Target detection application scenarios

Object detection has a wide range of applications in various fields, including but not limited to:

• Autonomous driving: Used to identify vehicles, pedestrians, traffic signs, etc. on the road to help autonomous vehicles make decisions.

• Security monitoring: Used to monitor abnormal events, people, vehicles, etc. in surveillance videos to improve security.

• Object counting: used to count the number of specific objects in an image, such as people counting in a shopping mall.

How to train a model and deploy it

Since target detection involves a lot of content, I would like to explain it in detail in multiple blogs. In the next blog, I will describe in detail the preprocessing of data, model selection, training and deployment. If you are interested in my content, If you are interested, please like and collect.