Data Annotation Case Study — Object (Vehicles) Detection in a High-definition Map
What Is Object Detection？
Object detection is to find all the objects of interest in the image and determine their categories and positions. Normally, in an image, we can detect the object's position by returning a coordinate from the top left to the bottom right corner and the category tag.
In short, object detection mainly includes two tasks: object position detection and object category.
Application Fields
Most of the research on target detection is in such fields as digital recognition, fingerprint recognition, face recognition, license plate recognition, agricultural pest recognition, defect detection, and pathological detection.
- Face Recognition
The face recognition system mainly includes four parts: face image collection and detection, face image preprocessing, and face image feature extraction, matching, and recognition. In face image collection and detection, we need to use the object detection algorithm to only extract a small part of the face area from the whole image, leading to a more accurate and faster prediction of the recognition model later.
- Industrial Quality Inspection
Defect detection technology, like steel defect detection, is widely used in industrial scenarios, which includes car body and surface defect detection, parts appearance defect detection, and workpiece crack detection. In particular, metal surface defect detection technology plays an important role in quality control in the production and manufacturing stages.
- Automatic Driving
The vision-related algorithms of automatic driving mainly include the detection of roads, vehicles, and pedestrians, and the detection and recognition of traffic markers and roadside objects. At present, autonomous driving under restricted road conditions has been preliminarily realized, but there is still a long way to go for realizing autonomous driving(L4-level) that is not affected by road conditions, weather, and other factors.
Let’s take a look at an object detection project.
- Project description: data annotation project of vehicles in HD maps
- Quantity: Hundreds of objects (cars) in a single image
- Output format: txt (contain one class, with x y coordinates as well as length and width of the bounding box)
- Annotation method: 2D bounding box
- Requirement: errors no more than 2 pixels
- Output:
End
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