Template: OAK-D Spec

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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
Shutter Rolling Globar
Sensor IMX378 OV9282
Max framerate 60fps 120fps
H.265 framerate 30fps /
Resolution 12MP (4056×3040 px/ 1.55um) 1MP (1280×800 px/3um)
FoV 81° DFoV – 68.8° HFoV 81° DFoV – 71.8° HFoV
Lens size 1/2.3 Inch 1/2.3 Inch
Focus 8cm – ∞ (AutoFocus) 19.6cm – ∞ (FixedFocus)
D-number 2.0 2.0

Camera Specifications

OAK-D-Lite
Camera Color camera Monochrome camera
Shutter Rolling Globar
Sensor IMX214 OV7251
Max framerate 60fps 200fps
H.265 framerate 30fps /
Resolution 48MP (4208×3120 px) 0.3MP (640×480 px/3um)
FoV 81.3° DFoV 85.6° DFoV
Lens size 1/3.1 Inch 1/7.5 Inch
Focus 8cm 6.5cm
D-number 2.2 2.2

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