Appendix: Training Format
Introduction
The VisionAI format is known for its comprehensive structure, accommodating a wide range of data types and annotations for AI model training. However, to facilitate a more user-friendly experience, we have developed a simplified version of this format for the training process.
Key Features
The simplified training format retains critical components such as image paths, annotations, and class labels, while omitting optional fields that are not directly involved in the training process.
Streamlined Structure: Focuses on essential elements required for training, reducing complexity.
Ease of Use: Designed for quick setup and integration with training pipelines.
Compatibility: Maintains compatibility with standard VisionAI format while simplifying the process.
Folder structure
Contents for annotations.jsonl
Image Classification
filename
string
The image file name under images folder
true
width
int
Image width
true
height
int
Image height
true
label
int
The index for the label category
true
Example
Box2D object detection
filename
string
The image file name under images folder
true
width
int
Image width
true
height
int
Image height
true
objects
dict
Contains the detection objects with the key below *label: list of the assigned object category-index *bbox: list of object info which contain x-center, y-center, bbox-width, bbox-height
true
Example
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