Difference between revisions of "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.<br /> | 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.<br /> | ||
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).<br /> | 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).<br /> | ||
− | 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. <br /> | + | 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 a 1000BASE-T ethernet connection. <br /> |
− | == | + | --> |
− | *Depth measuring range: 0.2 ~ | + | Onboard Intel® Movidius™ Myriad™ X |
− | *Depth camera: Global shutter 120fps / 200fps | + | vision processor, OAK-D is an AI vision intelligent kit designed and produced by the OpenCV team. Although it is tiny, it integrates a 4K RGB binocular depth camera, IMU, and a high-performance AI processing chip to realize the binocular depth visual computing and neural network reasoning. The inertial navigation sensor is integrated into a single camera, allowing users to obtain binocular vision measurement positioning, AI neural network acceleration, and 4K H.265 30-frame real-time streaming with a low power consumption of 2.5W. It meets the needs of users in intelligent driving, intelligent transportation, intelligent security, robots, teaching competitions, etc.<br/> |
+ | OAK-D-PoE is based on the OAK-D with a PoE power supply circuit that allows a single Cat5e (or higher) Ethernet cable (up to 100 meters (328 feet)) to power and provides a 1,000 Mbps (1 Gbps) full-duplex connection to devices. With the IP67 protection grade shell, it is suitable for users to use in environments that have requirements.<br/> | ||
+ | OAK-D-Lite is the most cost-effective product in the OAK USB series. Except for no IMU, the performance is comparable to OAK-D, but the price is lower. It combines depth perception, object detection (neural reasoning), and object tracking, and helps you achieve these functions with a simple and easy-to-use Python API. This OAK-D-Lite includes three onboard cameras (a 4K/30fps RGB camera, two monochrome binocular cameras) and a USB3.0 Type-C interface, you can use it on an ordinary computer, Raspberry Pi, or other popular embedded host to access the OAK through the USB interface.<br/> | ||
+ | OAK-D-Pro is an upgraded version of the OAK-D with structured light ranging, featuring an IR laser dot matrix emitter (active depth vision), and IR illuminated LEDs (for "night vision"). It is also smaller, lighter, and more precise than the OAK-D. With built-in high-performance Myriad X VPU, it adopts the active binocular vision technology and structured light, which improves the positioning accuracy to the sub-millimeter level, meeting the needs of close-range high-precision positioning and identification, such as automatic welding robots, the positioning, identification, and calibration of surface defects of parts, etc. and enhancing the robot's perception capabilities.<br/> | ||
+ | OAK-D-S2 is more compact than ODK-D. Its functions, performance, and lenses are the same as OAK-D, but smaller in size and lighter in weight, and can be used in scenes where space is limited and quality is required. In addition, compared with OAK-D, OAK-D-S2 removes the 5V power port in the structure and has a larger depth measurement range than OAK-D in performance. | ||
+ | ==Parameters== | ||
+ | *Depth measuring range: 0.2 ~ 35m | ||
+ | *Depth camera: Global shutter 120fps / 3MP 200fps | ||
+ | *RGB camera: 12MP 60fps / 13MP 60fps | ||
*AI chip: Intel Myriad X 4TOPS computing performance | *AI chip: Intel Myriad X 4TOPS computing performance | ||
*Video plug flow: 4K 30 fps H.265 plug flow | *Video plug flow: 4K 30 fps H.265 plug flow | ||
− | * | + | *Interface: USB3.0 Type-C (OAK-D/OAK-D-Lite/OAK-D-Pro) / PoE (OAK-D-PoE) |
*Expansion interfaces: GPIO, SPI, UART | *Expansion interfaces: GPIO, SPI, UART | ||
*NN platform support: all platforms | *NN platform support: all platforms | ||
− | * | + | *Average power consumption: 2.5W (average) |
*Development language: Python, C++ | *Development language: Python, C++ | ||
− | * | + | *Enclosure: Metal enclosure |
− | + | ||
− | ==Camera Specifications== | + | ===Camera Specifications=== |
{|class="wikitable" | {|class="wikitable" | ||
− | |+OAK-D/OAK-D-PoE | + | |+OAK-D/OAK-D-PoE/OAK-D-S2 |
!Camera !! Color camera !! Monochrome camera | !Camera !! Color camera !! Monochrome camera | ||
|- | |- | ||
!Shutter | !Shutter | ||
|Rolling | |Rolling | ||
− | | | + | |Global |
|- | |- | ||
!Sensor | !Sensor | ||
Line 28: | Line 37: | ||
|OV9282 | |OV9282 | ||
|- | |- | ||
− | !Max | + | !Max Framerate |
|60fps | |60fps | ||
|120fps | |120fps | ||
|- | |- | ||
− | !H.265 | + | !H.265 Framerate |
|30fps | |30fps | ||
|/ | |/ | ||
|- | |- | ||
!Resolution | !Resolution | ||
− | |12MP ( | + | |12MP (4056 × 3040 px/1.55um) |
− | |1MP ( | + | |1MP (1280 × 800 px/3um) |
|- | |- | ||
!FoV | !FoV | ||
Line 46: | Line 55: | ||
!Lens size | !Lens size | ||
|1/2.3 Inch | |1/2.3 Inch | ||
− | |1/ | + | |1/4 Inch |
|- | |- | ||
!Focus | !Focus | ||
Line 56: | Line 65: | ||
|2.0 | |2.0 | ||
|} | |} | ||
− | |||
− | |||
{|class="wikitable" | {|class="wikitable" | ||
− | |+OAK-D-Lite | + | |+OAK-D-Lite |
− | !Camera !! Color | + | !Camera !! Color Camera !! Monochrome Camera |
|- | |- | ||
!Shutter | !Shutter | ||
|Rolling | |Rolling | ||
− | | | + | |Global |
|- | |- | ||
!Sensor | !Sensor | ||
|IMX214 | |IMX214 | ||
− | | | + | |OV7215 |
|- | |- | ||
− | !Max | + | !Max Framerate |
|60fps | |60fps | ||
|200fps | |200fps | ||
|- | |- | ||
− | !H.265 | + | !H.265 Framerate |
|30fps | |30fps | ||
|/ | |/ | ||
|- | |- | ||
!Resolution | !Resolution | ||
− | | | + | |13MP (4208 × 3120 px) |
− | |0.3MP ( | + | |0.3MP (640 × 480 px) |
|- | |- | ||
!FoV | !FoV | ||
− | |81.3° DFoV | + | |81.3° DFoV |
− | |85.6° DFoV | + | |85.6° DFoV |
|- | |- | ||
− | !Lens | + | !Lens Size |
− | |1/3 | + | |1/2.3 Inch |
− | |1/ | + | |1/2.3 Inch |
|- | |- | ||
!Focus | !Focus | ||
− | |8cm | + | |8cm – ∞ (FixedFocus) |
− | |6.5cm | + | |6.5cm – ∞ (FixedFocus) |
|- | |- | ||
!D-number | !D-number | ||
Line 98: | Line 105: | ||
|2.2 | |2.2 | ||
|} | |} | ||
+ | |||
+ | {|class="wikitable" | ||
+ | |+ OAK-D-Pro | ||
+ | ! Camera !! Color Camera !! Monochrome Camera | ||
+ | |- | ||
+ | ! Shutter | ||
+ | |Rolling | ||
+ | |Global | ||
+ | |- | ||
+ | !Sensor | ||
+ | |IMX378 | ||
+ | |OV9282 | ||
+ | |- | ||
+ | !Max Framerate | ||
+ | |60fps | ||
+ | |120fps | ||
+ | |- | ||
+ | !H.265 Framerate | ||
+ | |30fps | ||
+ | |/ | ||
+ | |- | ||
+ | !Resolution | ||
+ | |12MP (4032 × 3040px) | ||
+ | |1MP (1280 × 4800px) | ||
+ | |- | ||
+ | !FoV | ||
+ | |81°DFoV / 69°HFoV / 55°VFoV | ||
+ | |81°DFoV / 72°HFoV / 49°VFoV | ||
+ | |- | ||
+ | !Lens Size | ||
+ | |1/2.3 Inch | ||
+ | |1/4 Inch | ||
+ | |- | ||
+ | !Focus Range | ||
+ | |8cm – ∞ (AutoFocus) | ||
+ | |19.6cm – ∞ (FixedFocus) | ||
+ | |- | ||
+ | !D-number | ||
+ | |2.0 | ||
+ | |2.2 | ||
+ | |- | ||
+ | !colspan="3" | Laser Transmitter Specifications | ||
+ | |- | ||
+ | !Laser Transmitter | ||
+ | !colspan="2" | Specification | ||
+ | |- | ||
+ | !Model | ||
+ | |colspan="2"| Belago1.1 Dot-Pattern | ||
+ | |- | ||
+ | !Number of dots | ||
+ | |colspan="2"| 4700 | ||
+ | |- | ||
+ | !HFOI*50% | ||
+ | |colspan="2"|78±7% | ||
+ | |- | ||
+ | !VFOI*50% | ||
+ | |colspan="2"|61°±7% | ||
+ | |- | ||
+ | !VSCEL Wavelength | ||
+ | |colspan="2"| 940nm | ||
+ | |- | ||
+ | !Operating Temperature | ||
+ | |colspan="2"| 10°C ~ 60°C | ||
+ | |- | ||
+ | !Storage Temperature | ||
+ | |colspan="2"|0°C ~ 80°C | ||
+ | |- | ||
+ | !Laser Safety Standards | ||
+ | |colspan="2"|EN/IEC 60825-1 3rd Edition (2014) Class 1 Laser Products | ||
+ | |} | ||
+ | |||
==Supported NN== | ==Supported NN== | ||
;Caffe* | ;Caffe* |
Latest revision as of 06:31, 26 July 2023
Overview
Onboard Intel® Movidius™ Myriad™ X
vision processor, OAK-D is an AI vision intelligent kit designed and produced by the OpenCV team. Although it is tiny, it integrates a 4K RGB binocular depth camera, IMU, and a high-performance AI processing chip to realize the binocular depth visual computing and neural network reasoning. The inertial navigation sensor is integrated into a single camera, allowing users to obtain binocular vision measurement positioning, AI neural network acceleration, and 4K H.265 30-frame real-time streaming with a low power consumption of 2.5W. It meets the needs of users in intelligent driving, intelligent transportation, intelligent security, robots, teaching competitions, etc.
OAK-D-PoE is based on the OAK-D with a PoE power supply circuit that allows a single Cat5e (or higher) Ethernet cable (up to 100 meters (328 feet)) to power and provides a 1,000 Mbps (1 Gbps) full-duplex connection to devices. With the IP67 protection grade shell, it is suitable for users to use in environments that have requirements.
OAK-D-Lite is the most cost-effective product in the OAK USB series. Except for no IMU, the performance is comparable to OAK-D, but the price is lower. It combines depth perception, object detection (neural reasoning), and object tracking, and helps you achieve these functions with a simple and easy-to-use Python API. This OAK-D-Lite includes three onboard cameras (a 4K/30fps RGB camera, two monochrome binocular cameras) and a USB3.0 Type-C interface, you can use it on an ordinary computer, Raspberry Pi, or other popular embedded host to access the OAK through the USB interface.
OAK-D-Pro is an upgraded version of the OAK-D with structured light ranging, featuring an IR laser dot matrix emitter (active depth vision), and IR illuminated LEDs (for "night vision"). It is also smaller, lighter, and more precise than the OAK-D. With built-in high-performance Myriad X VPU, it adopts the active binocular vision technology and structured light, which improves the positioning accuracy to the sub-millimeter level, meeting the needs of close-range high-precision positioning and identification, such as automatic welding robots, the positioning, identification, and calibration of surface defects of parts, etc. and enhancing the robot's perception capabilities.
OAK-D-S2 is more compact than ODK-D. Its functions, performance, and lenses are the same as OAK-D, but smaller in size and lighter in weight, and can be used in scenes where space is limited and quality is required. In addition, compared with OAK-D, OAK-D-S2 removes the 5V power port in the structure and has a larger depth measurement range than OAK-D in performance.
Parameters
- Depth measuring range: 0.2 ~ 35m
- Depth camera: Global shutter 120fps / 3MP 200fps
- RGB camera: 12MP 60fps / 13MP 60fps
- AI chip: Intel Myriad X 4TOPS computing performance
- Video plug flow: 4K 30 fps H.265 plug flow
- Interface: USB3.0 Type-C (OAK-D/OAK-D-Lite/OAK-D-Pro) / PoE (OAK-D-PoE)
- Expansion interfaces: GPIO, SPI, UART
- NN platform support: all platforms
- Average power consumption: 2.5W (average)
- Development language: Python, C++
- Enclosure: Metal enclosure
Camera Specifications
Camera | Color camera | Monochrome camera |
---|---|---|
Shutter | Rolling | Global |
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 | 1/4 Inch |
Focus | 8cm – ∞ (AutoFocus) | 19.6cm – ∞ (FixedFocus) |
D-number | 2.0 | 2.0 |
Camera | Color Camera | Monochrome Camera |
---|---|---|
Shutter | Rolling | Global |
Sensor | IMX214 | OV7215 |
Max Framerate | 60fps | 200fps |
H.265 Framerate | 30fps | / |
Resolution | 13MP (4208 × 3120 px) | 0.3MP (640 × 480 px) |
FoV | 81.3° DFoV | 85.6° DFoV |
Lens Size | 1/2.3 Inch | 1/2.3 Inch |
Focus | 8cm – ∞ (FixedFocus) | 6.5cm – ∞ (FixedFocus) |
D-number | 2.2 | 2.2 |
Camera | Color Camera | Monochrome Camera |
---|---|---|
Shutter | Rolling | Global |
Sensor | IMX378 | OV9282 |
Max Framerate | 60fps | 120fps |
H.265 Framerate | 30fps | / |
Resolution | 12MP (4032 × 3040px) | 1MP (1280 × 4800px) |
FoV | 81°DFoV / 69°HFoV / 55°VFoV | 81°DFoV / 72°HFoV / 49°VFoV |
Lens Size | 1/2.3 Inch | 1/4 Inch |
Focus Range | 8cm – ∞ (AutoFocus) | 19.6cm – ∞ (FixedFocus) |
D-number | 2.0 | 2.2 |
Laser Transmitter Specifications | ||
Laser Transmitter | Specification | |
Model | Belago1.1 Dot-Pattern | |
Number of dots | 4700 | |
HFOI*50% | 78±7% | |
VFOI*50% | 61°±7% | |
VSCEL Wavelength | 940nm | |
Operating Temperature | 10°C ~ 60°C | |
Storage Temperature | 0°C ~ 80°C | |
Laser Safety Standards | EN/IEC 60825-1 3rd Edition (2014) Class 1 Laser Products |
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