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OAK-D-Lite OpenCV AI Machine Vision Kit
Depth Measuring / Image Recognition & Location / Safety & Security Monitoring / Intelligent Driving / Robotics / Object Tracking
The OAK-D-Lite is the extremely cost effective solution of the OAK USB series, which provides similar performance as the OAK-D, except IMU, at a much lower price. It combines functions including depth perception, object detection (neural inference) and object tracking, together with easy-to-use Python API to help you use these functions. The OAK-D-Lite integrates three onboard cameras (1x 4K/30fps RGB camera, 2x mono binocular cameras) and USB3.0 Type-C port, it is accessible through USB connection on hosts like desktop computer, Raspberry Pi, and other popular embedded hosts.
Specifications
| DEPTH MEASURING RANGE | 0.2 ~ 9 m |
|---|---|
| DEPTH CAMERA | global shutter |
| RGB CAMERA | 13MP |
| MAX FRAMERATE | 60fps (RGB), 200fps (Depth) |
| AI CHIP | Intel Myriad X 4TOPS computing performance |
| VIDEO PLUG FLOW | 4K 30 fps H.265 plug flow |
| CONNECTOR | USB3.0 Type-C |
| NN PLATFORM SUPPORT | all platforms |
| POWER CONSUMPTION | avg 2.5W |
| DEVELOPMENT LANGUAGE | Python, C++ |
| ECLOSURE | aluminum enclosure |
| WEIGHT | 61g |
Powerful Computing Performance
The OAK Provides Up To 4TOPS Computing Performance,
10 Times Of OpenMV, 40 Times Of Raspberry Pi 4B
Camera Specifications
Use Free Neural Networks
Or Create Your Own
The OAK-D-Lite adopts Myriad X for binocular depth calculating as well as AI neural inference, then providing direct outputs like target coordinates, recognition results, and so on. More other functions can be achieved by calling the API, which allows you to build your own system easier.
Extensive Applications
The OAK Can Be Widely Used Thanks To Its Rich Functions And Technologies, It Will Upgrade Your Project To The Next Level By Enabling The Computer Vision Feature
Intelligent traffic |
Intelligent driving |
Intelligent safety & security |
Robotics |
Math contest |
|
Platform & Language Support
Framework & Neural Network Support
Outline Dimensions
Resources & Services
Wiki: OAK-D-Lite
How many cameras are included and what are their types?
The kit includes three onboard cameras: one 4K/30fps RGB camera and two mono binocular cameras for depth sensing.
What are the AI and depth features of this kit?
It uses the Intel Myriad X AI chip for up to 4 TOPS of computing, providing depth perception and neural inference with outputs such as coordinates and recognition results via the API.
What platforms and programming languages are supported?
Neural network platform support is all platforms. Development languages are Python and C++. It connects via USB3.0 Type C to desktop, Raspberry Pi, and other hosts.
What are the depth and video specifications?
Depth measuring range is 0.2 to 9 m. Depth camera uses global shutter. RGB camera is 13 MP up to 60 fps. Depth up to 200 fps. 4K 30 fps plug flow with H.265 support.
What are common use cases and applications?
Ideal for intelligent traffic detection, intelligent driving, safety and security monitoring, robotics, and education in OpenCV and AI projects using the Python API.
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Description
Ask AI about this product
OAK-D-Lite OpenCV AI Machine Vision Kit
Depth Measuring / Image Recognition & Location / Safety & Security Monitoring / Intelligent Driving / Robotics / Object Tracking
The OAK-D-Lite is the extremely cost effective solution of the OAK USB series, which provides similar performance as the OAK-D, except IMU, at a much lower price. It combines functions including depth perception, object detection (neural inference) and object tracking, together with easy-to-use Python API to help you use these functions. The OAK-D-Lite integrates three onboard cameras (1x 4K/30fps RGB camera, 2x mono binocular cameras) and USB3.0 Type-C port, it is accessible through USB connection on hosts like desktop computer, Raspberry Pi, and other popular embedded hosts.
Specifications
| DEPTH MEASURING RANGE | 0.2 ~ 9 m |
|---|---|
| DEPTH CAMERA | global shutter |
| RGB CAMERA | 13MP |
| MAX FRAMERATE | 60fps (RGB), 200fps (Depth) |
| AI CHIP | Intel Myriad X 4TOPS computing performance |
| VIDEO PLUG FLOW | 4K 30 fps H.265 plug flow |
| CONNECTOR | USB3.0 Type-C |
| NN PLATFORM SUPPORT | all platforms |
| POWER CONSUMPTION | avg 2.5W |
| DEVELOPMENT LANGUAGE | Python, C++ |
| ECLOSURE | aluminum enclosure |
| WEIGHT | 61g |
Powerful Computing Performance
The OAK Provides Up To 4TOPS Computing Performance,
10 Times Of OpenMV, 40 Times Of Raspberry Pi 4B
Camera Specifications
Use Free Neural Networks
Or Create Your Own
The OAK-D-Lite adopts Myriad X for binocular depth calculating as well as AI neural inference, then providing direct outputs like target coordinates, recognition results, and so on. More other functions can be achieved by calling the API, which allows you to build your own system easier.
Extensive Applications
The OAK Can Be Widely Used Thanks To Its Rich Functions And Technologies, It Will Upgrade Your Project To The Next Level By Enabling The Computer Vision Feature
|
Intelligent traffic |
Intelligent driving |
|
Intelligent safety & security |
Robotics |
|
Math contest |
|
Platform & Language Support
Framework & Neural Network Support
Outline Dimensions
Resources & Services
Wiki: OAK-D-Lite
FAQ
How many cameras are included and what are their types?
The kit includes three onboard cameras: one 4K/30fps RGB camera and two mono binocular cameras for depth sensing.
What are the AI and depth features of this kit?
It uses the Intel Myriad X AI chip for up to 4 TOPS of computing, providing depth perception and neural inference with outputs such as coordinates and recognition results via the API.
What platforms and programming languages are supported?
Neural network platform support is all platforms. Development languages are Python and C++. It connects via USB3.0 Type C to desktop, Raspberry Pi, and other hosts.
What are the depth and video specifications?
Depth measuring range is 0.2 to 9 m. Depth camera uses global shutter. RGB camera is 13 MP up to 60 fps. Depth up to 200 fps. 4K 30 fps plug flow with H.265 support.
What are common use cases and applications?
Ideal for intelligent traffic detection, intelligent driving, safety and security monitoring, robotics, and education in OpenCV and AI projects using the Python API.
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