The OpenMV Cam RT1062 is a programmable camera board for building embedded-vision projects—not a generic USB webcam. It pairs an NXP i.MX RT1062 Cortex-M7 processor with a 5 MP OV5640 image sensor and runs Python-style scripts through OpenMV’s MicroPython workflow. That makes it a fit for projects such as reading QR codes, tracking colored objects or using visual tags to guide a robot, provided you plan around its 3.3 V I/O and the limits of the workload you want to run.
What the OpenMV Cam RT1062 is—and what it is not
The RT1062 is a self-contained camera and microcontroller platform. You write a script in OpenMV IDE, load it onto the board and use the camera’s image-processing features in an embedded project. It is different from a USB webcam, which generally supplies video to a separate computer for processing.
OpenMV’s official documentation describes programming the board with high-level Python scripts using MicroPython. Its documentation landing page, built October 2, 2026, identifies firmware v5.0.1 based on MicroPython v1.28; software versions can change. OpenMV’s documentation headline is “Machine vision, made simple,” a description of its intended workflow rather than an independent performance assessment. OpenMV MicroPython documentation
What hardware does the RT1062 provide?
OpenMV’s current quick reference lists the following specifications for the board. They are manufacturer-published figures, not independent measurements. OpenMV Cam RT1062 quick reference
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- High-Speed Processor: Features a 600 MHz ARM Cortex-M7 with 32MB SDRAM and 16MB flash for fast, reliable machine vision applications, running up to 40 FPS at QVGA resolutions.
- Versatile Connectivity: Includes USB-C, WiFi (802.11 a/b/g/n), Bluetooth v5.1, and Ethernet with PoE, offering seamless communication for diverse projects.
- Customizable Camera Module: Comes with a 5MP OV5640 sensor and M12 lens mount, supporting 2592x1944 resolution and optional modules for global shutter or thermal imaging.
- Advanced I/O and Low Power: 14 I/O pins with SPI, I2C, UART, ADC, and deep sleep mode consuming only 30µA for efficient, power-sensitive operations.
- Feature-Packed Design: Includes a secure cryptographic element, accelerometer, LiPo battery charging, RGB LEDs, and professional module support for advanced use cases.
| Component or feature | OpenMV-published specification |
|---|---|
| Processor | NXP i.MX RT1062, 600 MHz Cortex-M7 |
| Memory | 32 MB external SDRAM; 1 MB SRAM |
| Program storage | 16 MB QSPI flash |
| Camera | OV5640, 5 MP rolling-shutter sensor |
| Connections and interfaces | USB-C, Wi-Fi/Bluetooth, 10/100 Ethernet, microSD socket and 14 3.3 V I/O pins |
| Other listed hardware | Onboard accelerometer |
| Deep-sleep consumption | About 30 µA from a LiPo battery, according to OpenMV |
Those interfaces and component specifications do not mean every connection or workload can be used simultaneously at maximum performance. The product page says most simple algorithms run at about 40 FPS at QVGA (320 × 240) and below. Treat that as OpenMV’s claim: frame rate depends on image resolution and algorithm, and the figure is not an independent benchmark or a guarantee for a particular project. OpenMV Cam RT1062 product page
DIY projects the board can support
OpenMV’s documentation and product materials demonstrate several machine-vision tasks. They are useful starting points for ideas, but a demonstrated task does not guarantee a particular speed or accuracy in a different scene or build.
Robot localization or interaction with AprilTags
Use a camera to detect AprilTags placed around a work area, then make a robot react to the tag it sees. The documented example gives makers a software starting point for tag-based localization or interaction; the rest of the behavior depends on the robot, tag layout and control code.
Rank #2
- Powerful Vision Processor: Features a 480 MHz ARM Cortex-M7 processor with 32MB SDRAM and 32MB flash, perfect for high-speed machine vision tasks.
- Versatile Camera: Comes with a 5MP OV5640 sensor supporting resolutions up to 2592x1944 with an M12 lens mount for customization.
- Easy Python Programming: Program with MicroPython for simple integration of complex machine vision algorithms.
- Rich I/O Interfaces: Includes USB, SPI, I2C, CAN, UART, ADC, DAC, PWM, and servo control pins for versatile connectivity.
- Compact and Efficient: Lightweight design (17g) with low power consumption, ideal for robotics and IoT.
QR-code and barcode reading
A reader could scan a label to trigger a sorting action, select a robot behavior or identify a bin. Plan the optics, lighting, label size and working distance around the actual setup rather than assuming every code will be readable from any angle.
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Color tracking can help a robot follow a brightly colored object or let a small installation react when an object enters view. Lighting and background colors affect how easy it is to distinguish the target.
Face detection and person tracking
OpenMV includes face-detection and YOLO person-tracking examples. These are options for experiments such as a camera-driven display or a device that responds to a person’s presence. The examples should not be read as a promise that arbitrary models or more demanding workloads will run at a specified frame rate.
Rank #3
- Efficient Vision Processor: Powered by a 480 MHz ARM Cortex-M7 with 1MB SRAM and 2MB flash, perfect for running machine vision applications at up to 80 FPS on QVGA resolutions.
- Versatile Camera Module: Includes a MT9M114 image sensor with 640x480 resolution and an M12 lens mount, supporting upgrades for specialized lenses or thermal and global shutter modules.
- Comprehensive Connectivity: Features USB, SPI (80Mbps), I2C, CAN, and UART interfaces, with 10 I/O pins for PWM, ADC, DAC, and servo control, supporting diverse project needs.
- Python-Friendly Programming: Leverage MicroPython to easily execute complex vision algorithms and manage I/O pins, simplifying real-world vision integration.
- Compact and Low Power: Lightweight 16g design with power consumption as low as 110mA, ideal for robotics, IoT, and portable applications.
How to get started
OpenMV’s quick-start workflow has three steps:
- Install OpenMV IDE. Use the official OpenMV documentation for the current getting-started instructions.
- Connect the camera to your computer by USB. The board has a USB-C connector.
- Connect to the camera in the IDE and run a script. Start with an official example that matches the task you want to try, then adapt it to your sensor, scene and project.
Electrical and power decisions to get right
Protect the 3.3 V I/O
The RT1062’s I/O is 3.3 V tolerant, not 5 V tolerant. Do not connect its pins directly to a 5 V MCU or peripheral; use an appropriate level shifter where needed and follow the board’s pin and power guidance. OpenMV explicitly warns against a direct connection to a 5 V MCU such as an Arduino Mega. OpenMV product page
Power the board through the specified input
OpenMV specifies VIN at 4.7–5.7 V for the product page’s power guidance and says the 3.3 V pins are outputs only. Do not try to power the board through its 3.3 V rail. Check the pinout and power instructions for the exact board revision and attached hardware before wiring a build. OpenMV product page
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Check the revision for battery-charging details
OpenMV’s current materials list R4, R5 and R6 revisions. The published charging guidance differs: R4/R5 battery guidance states 100 mA, while the R6 product information describes a 500 mA charging update. If charging current matters to your battery choice or design, verify the documentation for the revision you have rather than applying one figure to every RT1062 board. OpenMV quick reference · OpenMV product page
Rank #4
- 【Compatibility】This 6 pin rear camera is only suitable for AZDOME M550 & M550 Max dash cam
- 【HD 1080P Recording】The rear car camera has excellent image output and amazing performance in both bright and dim light, ensuring your safety and peace of mind on the road
- 【IP68 Waterproof】The camera will be protected from powerful jets of water from any direction, such as rain and a car wash, comprehensively protecting the electronic components inside the camera
- 【Easy to Install】Simply connect the rear camera to the M550, M550 Max front view camera via the included extended cable
- 【6m/20ft Extension Cable】The rear camera is designed for most of the vehicles, such as cars, pickup trucks, SUVs, vans, RVs, etc
Choose the camera, connectivity and accessories around the build
Sensor module and lens
The OV5640 is on a removable camera carrier. OpenMV lists other sensor modules and an M12 lens interface, so a project may have options beyond the included camera configuration. Compare field of view, shutter type, resolution and lighting needs before choosing a module or lens; the right choice depends on what must fit in the frame and how objects move.
Storage, mounting and enclosure
The board has a microSD socket. OpenMV also links printable cases and tripod- or GoPro-style mounts. These can help with logging, positioning or protecting a particular installation, but they are project-specific accessories rather than requirements for every build. Check revision compatibility when choosing a case.
Wireless, Ethernet and PoE
OpenMV lists Wi-Fi/Bluetooth and 10/100 Ethernet. Its materials describe Power over Ethernet through an external shield; PoE is not built into the base board. Account for the extra hardware and power path if you plan to use that option.
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- C55-R 3GP Camera Module: Compact surveillance camera with 352x288 resolution at 15 fps and ultra-small 5x5mm lens for discreet recording applications
- Plug and Play Operation: No configuration required, simply insert micro SD card and start recording with a single button press for immediate use
- Ultra Low Power Consumption: Operates at only 95mA working current with 3.7V power supply, ensuring efficient energy usage during extended recording sessions
- Long Recording Time: Supports up to 256GB micro SD card with capability to record up to 1000 hours of video footage in 3GP format
- One Button Control System: Easy operation with single button for starting and stopping recordings, plus web camera function accessible via USB connection
How to decide whether it fits your project
The RT1062 is worth considering when the goal is to run documented vision tasks on a programmable camera board and connect the result to an embedded build. Before choosing it, check these project-specific trade-offs:
- Vision task: Confirm that the documented examples or supported software approach match the detection or tracking problem you need to solve.
- Compute and memory: Match the intended image resolution and algorithm to the board. Do not assume that the product page’s simple-algorithm frame-rate claim applies to a different model or workload.
- Optics: Decide whether the OV5640, an alternate module or an M12 lens best suits the scene and motion.
- Workflow: The board is programmed through OpenMV IDE and MicroPython; it is not simply a camera that streams video to a host for all processing.
- Connections and power: Check whether Wi-Fi/Bluetooth or Ethernet, battery operation, microSD and mounting options meet the project’s needs.
- Electrical compatibility: Ensure connected devices work with 3.3 V I/O, and design power and charging around the exact revision.
OpenMV’s board catalog also lists N6, AE3, H7 Plus and H7 platforms. The available RT1062 information does not establish a performance comparison among those boards, so compare their official specifications against your own requirements rather than assuming one is universally better. OpenMV board catalog
Quick Recap
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