SenseCraft AI Wiki Center
Overview
The Overview section provides a high-level introduction to SenseCraft AI, explaining its purpose, key features, and benefits. It serves as a starting point for users to understand the platform and its capabilities. The overview also includes links to Getting Started guides and FAQs to help users quickly get up and running with SenseCraft AI.
Pretrained Models
The Pretrained Models section contains information about the readily available models that can be deployed on various devices supported by SenseCraft AI. These models are optimized for specific hardware and can be used for different applications without the need for custom training. The section is further divided into subsections based on the supported devices:
- for XIAO ESP32S3 Sense: This subsection lists the pretrained models compatible with the XIAO ESP32S3 Sense board, along with their descriptions and use cases.
- for Grove Vision AI V2: Here, you can find the pretrained models specifically designed for the Grove Vision AI V2 device.
- for SenseCAP Watcher: This subsection provides information about the pretrained models that can be used with the SenseCAP Watcher device, enabling various monitoring and detection functionalities.
- for reComputer Jetson: The reComputer Jetson subsection contains pretrained models optimized for the powerful reComputer Jetson platform, suitable for more demanding AI applications.
Training
The Training section is dedicated to guiding users through the process of creating custom models using SenseCraft AI. It is divided into two main subsections:
- Classification: This subsection provides step-by-step tutorials and best practices for training image classification models using SenseCraft AI.
- Object Detection: Here, you can find detailed guides on training object detection models using SenseCraft AI.
Models Output
The Models Output section focuses on how to configure and utilize the output of trained models on different devices supported by SenseCraft AI. It is organized into the following subsections:
- Grove Vision AI V2 Model Output: This subsection explains how to configure and access the output of models deployed on the Grove Vision AI V2 device. It covers topics such as setting up triggers, integrating with external systems, and visualizing the model's predictions.
XIAO ESP32S3 Sense Model Output: Here, you can find information on how to work with model outputs on the XIAO ESP32S3 Sense board. The subsection is further divided into:
- via GPIO: This part provides guides on how to map model outputs to the GPIO pins of the XIAO ESP32S3 Sense, enabling control of external hardware based on the model's predictions.
- via MQTT: Here, you can learn how to send model outputs from the XIAO ESP32S3 Sense to other devices or systems using the MQTT protocol, facilitating seamless integration and communication.
- As a Sensor: This part will explain how to use XIAO, which has already uploaded a model, as a sensor. It may require you to use an additional XIAO or Arduino device.
- Use SSCMACore library output model info: If you don't want to use an additional XIAO to receive data output from your model, then the tutorial here may be for you.
reComputer Jetson Workspace: This subsection provides information on how to set up and utilize the reComputer Jetson Workspace for working with model outputs. It covers topics such as configuring the workspace, visualizing model predictions, and integrating with other software.
Application
The Application section showcases real-world examples and case studies demonstrating how SenseCraft AI can be used to solve various problems across different domains. It includes detailed project write-ups, code samples, and best practices to inspire and guide users in developing their own AI applications using SenseCraft AI.
Tech Support & Product Discussion
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