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RLX COMPONENTS s.r.o. , Electronic Components Distributor.
RLX COMPONENTS s.r.o. , Electronic Components Distributor.
OAK-D-S2-POE, 12MP, 4TOPS, OpenCV AI Machine Vision Kit, Depth Measuring, Image Recognition (WS-27827)
OAK-D-S2-POE, 12MP, 4TOPS, OpenCV AI Machine Vision Kit, Depth Measuring, Image Recognition
Depth Measuring / Image Recognition & Location / Safety & Security Monitoring
Intelligent Driving / Robotics / Gigabit Ethernet / PoE Support / Object Tracking / IP65
OAK is an embedded, high-performance, 3D AI+CV platform consisting of an open-source hardware, firmware, software ecosystem that provides complete and ready-to-use embedded 3D AI + hardware-accelerated computer vision.
The OAK-D-S2-POE combines depth perception, object detection (neural reasoning) and object tracking, and can help you achieve these functions with a simple and easy-to-use Python API. Onboard three cameras (a 4k/30fps RGB camera and two mono binocular cameras) and IMU. Features an IP65 industrial-grade waterproof rating, it can be used both indoors and outdoors, with onboard PoE port (for 802.3af-compliant PoE power supply and GigE connectivity), making it an intelligent Network IP camera with depth vision.
This product is the Series 2 version of the OAK-D-POE. The main difference is that this product is smaller and lighter.
Perceive The Real 3D World And Give Robots A Pair Of Eyes
Real-Time Data Processing On The Chip, Low Performance Requirements On The Host
Edge Detection
Feature Tracking
Run Neural Network Models Directly On The Device And Support Your Own Models To OAK
Object Detection
Semantic Segmentation
OCR
Attitude detection
Supports almost all common platforms, programming languages, and neural network frameworks
(The OpenCV AI Kit Official plans to support Java and in progress)
The core chip with 4 TOPS computing performance has built-in functions such as depth measurement, neural network inference acceleration, and OpenCV image processing acceleration. The development environment can be installed with one click, and it features open-source hardware similar to Raspberry Pi, massive application cases and free industrial-grade neural network pre-training models, so you can quickly design your own products.
Lightly Loaded CPU
The processing of artificial intelligence and depth vision on OAK can be completed on the chip without the involvement of the host.
Easy to Develop
It takes less than 30 seconds to run the 3D AI function of OAK.
Open Source Ecology
The hardware and software of OAK are open-source, allowing users to prototype and produce solutions with low risk.
The OAK Provides Up To 4TOPS Computing Performance
10 Times Of OpenMV, 40 Times Of Raspberry Pi 4B
PARAMETER | RGB Camera | Binocular Camera |
---|---|---|
SENSOR | IMX378 | OV9282 |
FOV | 81°D / 69°H / 55°V | 89°D / 80°H / 55°V |
RESOLUTION | 12MP (4032×3040) | 1MP (1280×800) |
MAX FPS | 60 FPS | 120 FPS |
FOCAL LENGTH | 4.81mm | 2.35mm |
APERTURE | 1.8 ±5% | 2.0 ±5% |
FOCUS RANGE | AF: 8cm ~ ∞ (the default shipping version) FF: 50cm ~ ∞ (you can contact our customer service if needed) |
FF: 19.6cm ~ ∞ |
LENS SIZE | 1/2.3″ | 1/4″ |
DISTORTION | < 1.0% | < 1.5% |
PIXEL SIZE | 1.55µm × 1.55µm | 3µm × 3µm |
SHUTTER | Rolling | Global |
WATERPROOF RATING | IP65 |
---|---|
DEPTH MEASURING RANGE | 0.7~12m (The theoretical measuring distance can reach 35m, with an actual measurement error of approx. 6% to 10% at 30m) Minimum depth: ~20 cm (400P and extended), ~35 cm (400P or 800P, extended), ~70cm (800P) |
DEPTH CAMERA | 1MP, global shutter |
REFERENCE ACCURACY | <2% error @below 4m <4% error @4m~7m <6% error @7m~10m |
RGB CAMERA | 12MP |
MAX FRAMERATE | 60fps (RGB), 120fps (Depth) |
AI CHIP | Intel Myriad X 4TOPS computing performance |
VIDEO PLUG FLOW | 4K 30 fps H.265 plug flow |
CONNECTOR | Gigabit Ethernet port with integrated 802.3af PoE circuit |
NN PLATFORM SUPPORT | All platforms |
POWER CONSUMPTION | 3W ~ 3.5W |
DEVELOPMENT LANGUAGE | Python, C++ |
ECLOSURE | Dull-polish metal case |
WEIGHT | 184g |
DIMENSIONS | 111 × 40 × 31.3 (mm) |
Balenie Obsahuje / Package Content