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Overview
OAK-D and the OAK-D-PoE is an MIT-licensed open-source software and Myriad X-based hardware solution for computer vision at any scale. which is made by the OpenCV team.
The OAK-D baseboard has three onboard cameras which implement stereo and RGB vision, piped directly into the DepthAI SoM for depth and AI processing. The data is then output to a host via USB 3.1 Gen1 (Type-C).
The OAK-D-PoE baseboard offers full 802.3af, Class 3 PoE compliance with 1000BASE-T speeds. The OAK-D-POE baseboard has three onboard cameras which implement stereo and RGB vision, piped directly into the DepthAI SoM for depth and AI processing. The data is then output to a host via 1000BASE-T ethernet connection.
Features
- Depth measuring range: 0.2 ~ 9m
- Depth camera: Global shutter 120fps / 200fps
- AI chip: Intel Myriad X 4TOPS computing performance
- Video plug flow: 4K 30 fps H.265 plug flow
- Connector: Gigabit Ethernet, with 802.3af-compliant PoE circuit
- Expansion interfaces: GPIO, SPI, UART
- NN platform support: all platforms
- Power consumption: 2W ~ 5.5W
- Development language: Python, C++
- Eclosure: Aluminum enclosure
- Weight: 361g
Camera Specifications
OAK-D/OAK-D-PoE
Camera |
Color camera |
Monochrome camera
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Shutter
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Rolling
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Globar
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Sensor
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IMX378
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OV9282
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Max framerate
|
60fps
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120fps
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H.265 framerate
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30fps
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/
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Resolution
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12MP (4056×3040 px/ 1.55um)
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1MP (1280×800 px/3um)
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FoV
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81° DFoV – 68.8° HFoV
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81° DFoV – 71.8° HFoV
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Lens size
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1/2.3 Inch
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1/2.3 Inch
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Focus
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8cm – ∞ (AutoFocus)
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19.6cm – ∞ (FixedFocus)
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D-number
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2.0
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2.0
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Camera Specifications
OAK-D-Lite
Camera |
Color camera |
Monochrome camera
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Shutter
|
Rolling
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Globar
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Sensor
|
IMX214
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OV7251
|
Max framerate
|
60fps
|
200fps
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H.265 framerate
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30fps
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/
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Resolution
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48MP (4208×3120 px)
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0.3MP (640×480 px/3um)
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FoV
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81.3° DFoV
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85.6° DFoV
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Lens size
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1/3.1 Inch
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1/7.5 Inch
|
Focus
|
8cm
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6.5cm
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D-number
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2.2
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2.2
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Supported NN
- Caffe*
- AlexNet
- CaffeNet
- GoogleNet (Inception) v1, v2, v4
- VGG family (VGG16, VGG19)
- SqueezeNet v1.0, v1.1
- ResNet v1 family (18***, 50, 101, 152)
- MobileNet (mobilenet-v1-1.0-224, mobilenet-v2)
- Inception ResNet v2
- DenseNet family (121,161,169,201)
- SSD-300, SSD-512, SSD-MobileNet, SSD-GoogleNet, SSD-SqueezeNet
- TensorFlow*
- AlexNet
- Inception v1, v2, v3, v4
- Inception ResNet v2
- MobileNet v1, v2
- ResNet v1 family (50, 101, 152)
- ResNet v2 family (50, 101, 152)
- SqueezeNet v1.0, v1.1
- VGG family (VGG16, VGG19)
- Yolo family (yolo-v2, yolo-v3, tiny-yolo-v1, tiny-yolo-v2, tiny-yolo-v3)
- faster_rcnn_inception_v2, faster_rcnn_resnet101
- ssd_mobilenet_v1
- DeepLab-v3+
- MXNet*
- AlexNet and CaffeNet
- DenseNet family (121,161,169,201)
- SqueezeNet v1.1
- MobileNet v1, v2
- NiN
- ResNet v1 (101, 152)
- ResNet v2 (101)
- SqueezeNet v1.1
- VGG family (VGG16, VGG19)
- SSD-Inception-v3, SSD-MobileNet, SSD-ResNet-50, SSD-300