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VS-DX5 EDGE AI DEVELOPMENT PLATFORM
Powered by the Sunrise 5 (X5) intelligent computing chip, the VS-DX5 is designed for algorithm uation, functional validation, and prototype development across edge AI, machine vision, robotics, and multimedia applications. It helps development teams quickly validate the complete workflow from image capture and model inference to display and network output.
CORE VALUE
The board integrates an 8-core Arm Cortex-A55 CPU with a Bayers-architecture BPU, along with multiple vision, display, network, and expansion interfaces. It is well suited for perception algorithm validation, robotic prototyping, and product feasibility uation based on the X5 chip.
The 8-core Cortex-A55 handles the operating system, device management, communications, and application logic, while the 10 TOPS BPU accelerates neural network inference for a balanced combination of general-purpose computing and real-time AI.
Three MIPI CSI interfaces provide one 4-lane and two 2-lane connections for validating monocular, multi-camera, multi-angle, and multi-sensor vision solutions.
Camera, HDMI, MIPI DSI, USB, and network interfaces support a complete workflow covering image capture, AI inference, result overlay, local display, and network transmission.
Available resources cover PTQ, QAT, model compilation, performance and accuracy analysis, and on-device Runtime deployment for uating classification, detection, segmentation, pose estimation, OCR, and multimodal models.
A 40-pin header, ADC, I2S/PDM, USB, TF card slot, Wi-Fi, Bluetooth, and Gigabit Ethernet make it easy to connect sensors, audio modules, controllers, and custom expansion boards.
Integrated networking, debugging, and storage resources shorten hardware integration, algorithm uation, and demonstration system development cycles while reducing early-stage product development risk.
END-TO-END PIPELINE
Validate the critical workflow from sensor input, image processing, and AI inference to result display and network output on a single development board.
MIPI CSI, I2S / PDM, and USB peripherals
Video frame processing, format conversion, and data preparation
Classification, detection, segmentation, pose estimation, OCR, and multimodal AI
HDMI 4K@30fps and MIPI DSI 2K@30fps
Gigabit Ethernet, dual-band Wi-Fi, and Bluetooth 5.1
PRODUCT FEATURES
Connect cameras according to interface bandwidth, driver compatibility, and sensor requirements to uate object recognition, pose estimation, environmental perception, multi-angle capture, and multi-sensor fusion.
Evaluate adaptation, calibration, quantization, compilation, and on-device deployment for models from PyTorch, ONNX, and other frameworks, with ongoing performance and accuracy optimization.
Choose from 2GB / 4GB LPDDR4 and 8GB / 16GB eMMC configurations to support uation workloads and concurrent applications with different levels of complexity.
The onboard CH340N supports serial debugging, while USB Device mode supports ADB, Fastboot, DFU, and USB networking. Gigabit Ethernet enables SSH remote access and file transfer.
Note: The number of cameras that can operate simultaneously, along with their resolution, frame rate, sensor model, and ISP configuration, depends on the hardware design, drivers, and software version. Refer to the compatibility list and test results for the applicable version.
AI DEPLOYMENT WORKFLOW
Adapt models from PyTorch, ONNX, and other frameworks
Balance model accuracy and computational efficiency
Model calibration, validation, and platform compilation
Evaluate latency, throughput, and resource utilization
Compare model results before and after quantization
Integrate real application data pipelines on the board
APPLICATIONS
Ideal for algorithm uation, functional validation, hardware interface testing, software architecture research, and demonstration prototype development.
Object detection and tracking, human or pet recognition, pose estimation, visual obstacle avoidance, and multi-camera capture.
Validate camera-based perception, motion recognition, visual interaction, voice input and output, and screen display capabilities.
Object detection, behavior recognition, video analytics, regional s, and overlaid visualization of algorithm results.
Proof-of-concept development for defect detection, object classification, counting, positioning, meter reading, and personal protective equipment detection.
Customer traffic analysis, product recognition, interactive displays, content triggering, and visual perception for self-service terminals.
Combine an audio daughterboard, microphones, speakers, and cameras to validate integrated visual and audio interaction.
Suitable for experiments in embedded AI, computer vision, robotics, model quantization, and on-device inference.
Evaluate chip capabilities, interfaces, model migration, performance, and software architecture before developing custom hardware.
FROM EVALUATION TO PRODUCT
Tell us about your algorithms, interface requirements, mechanical design, and product goals to receive solution recommendations for robotics, machine vision, and edge AI projects.
Discuss Your VS-DX5 ProjectSunrise 5 (X5) SoC
Octa-core Arm® Cortex®-A55 @ 1.5 GHz
Bayes Architecture BPU @ 1.0 GHz, up to 10 TOPS AI Computing Performance
2 GB / 4 GB LPDDR4 RAM, 8 GB / 16 GB eMMC Flash
3 × MIPI CSI interfaces (1 × 4-lane, 2 × 2-lane)
1 × HDMI output, up to 4K @ 30 fps; 1 × MIPI DSI output, up to 2K @ 30 fps
1 × USB Type-A 3.0, 1 × Micro USB 2.0
1 × Gigabit Ethernet (RJ45)
2.4 GHz / 5 GHz Wi-Fi (IEEE 802.11 b/g/n), Bluetooth® 5.1
1 × TF (microSD) card slot, 1 × 40-pin expansion header, 6 × ADC channels, 1 × I2S0/PDM interface
12 V DC power input (DC adapter)
Discuss your OEM/ODM requirements with our engineering team and get a customized AI solution.
Contact Expert
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