Concepts
Understanding the core components and terminologies of HubAI is essential for effective utilization. This page introduces several key concepts you'll encounter as you navigate through the documentation.Model
Model is a basic entity of HubAI. It consists of a Model File(s) and a Model Card. Models can be public (accessible to all HubAI users) or private (team-owned).Model File(s)
Model file(s) (also referred to as model executable(s)) come standalone or packed into a NN Archive. The model file(s) must be either in ONNX (.onnx), OpenVINO IR (.xml and .bin), or TensorFlow Lite (.tflite) or one of the RVC compiled formats.Model Card
Model Card is a collection of information about the model. You can choose your own structure for private models. For public models, we suggest the following structure:Markdown
1# Model Details
2
3## Model Description
4... Description of the model functionality.
5
6- Developed By - Name of the model developer(s).
7- Shared By - Source of the model file/weights.
8- Model Type - General model type (e.g. computer vision).
9- License - Link to the license that governs the use/distribution of the model.
10- Resources - Link(s) to the model resouces (e.g. paper, sourecode, etc.)
11
12# Training Details
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14## Training Data
15... Describe and link to the data used to train the model.
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17# Testing Details
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19## Metrics
20... Describe and report the metrics used to validate the model.
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22# Technical Specifications
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24## Input/Output Details
25... Name, shape and a short description for each input/output tensor.
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27## Model Architecture
28... Describe the model architecture (e.g. backbone, head, etc.).
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30## Throughput
31... Report model throughput on RVC platform(s) for which the model is converted.
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33## Quantization
34... Describe quantization data if quantization is used during conversion.
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36# Utilization
37... Explain how to utilize the model in a DepthAI pipeline.