AI Object Detection Solution: YOLOv5 demo for real-time object detection | Deep Learning | Machine Learning
In the past few years, the rapid development of deep learning technologies has dramatically accelerated the momentum of object detection.?Object detection is at the core of most vision-based AI software and programs and plays a crucial role in scene understanding. Automatic?analysis of images and videos to detect, identify, and count different items, animals, and people is commonly used in security, traffic, medical, and military applications.
Despite significant advances in the field and the power of computer vision, detecting objects is a complex implementation that often faces quite a few challenges.?Challenges in object detection?include:
1. Objects may look completely different from different viewpoints
2. The darker the light, the lower the visibility of objects
3. Messy backgrounds affect recognition
4. Objects in motion require more precise algorithms
Popular algorithms used to perform object detection include R-CNN (Region-Based Convolutional Neural Networks), Fast R-CNN, and YOLO.?The R-CNN models may generally be more accurate, yet the YOLO family of models is fast, much faster than R-CNN, achieving object detection in real-time.
Referring to this benchmark?(YOLOv5 TensorRT Benchmark for NVIDIA? Jetson? AGX Xavier? and NVIDIA? Laptop?1),?we tested the very popular YOLOv5 with the Blade 3 board in hand to see how it works on the RK3588 chip and?show its performance.?https://community.mixtile.com/t/blade-3-yolov5-tensorrt-benchmark/607
Here, we show you a?detailed tutorial on changing the RK YOLOv5 demo to capture a real-time camera feed.?https://community.mixtile.com/t/how-to-change-the-rk-yolov5-demo-to-capture-real-time-camera-feeds/609
Additionally, we also made a detailed video for Blade 3 board to assess its performance and demonstrate its effectiveness. In this video, we'll show you how to use our product to do amazing AI YOLOv5 Object Detection.?
As the previous benchmark mentioned, Mixtile Blade 3 board is very beneficial for any cost-effective AIOT solution for its core functionalities of the accuracy of NPU, lower power consumption and reasonable cost.
At the heart of Mixtile Blade 3 is the RK3588 SoC, an 8nm-fabricated, low-power and high-performance processor with quad-core Cortex-A76 and quad-core Cortex-A55. There is also a powerful, quad-core Mali G610MC4 GPU and a 6-TOPS NPU,?enhancing AI workload performance and providing extensive machine learning support.?NPU is specifically designed to perform complex mathematical calculations that are required for deep learning algorithms. This makes it highly efficient for processing large amounts of data, which is essential for object detection tasks.
RK3588 NPU
The system-on-chip comes with a 48-megapixel image signal processor that can implement several algorithm accelerators such as HDR, 3A, 3DNR, sharpening, dehaze, fisheye correction, and gamma correction.
Thanks in part to a built-in HDMI interface and onboard support for the encoding and decoding of high-quality video formats, it is equally well suited to a broad range of other applications—from personal computing to video streaming.?The chip includes a powerful Arm Mali-G610 GPU, which can provide high-quality graphics processing and support for advanced graphics APIs, such as Vulkan and OpenGL ES 3.2. This is important for object detection applications that require advanced visualizations or user interfaces.
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Compared with Blade 3 board, Mixtile Edge 2 has 1Top NPU, but it also performs very well.?Features Quad-core ARM Cortex-A55 up to 2.0GHz and supports LPDDR4 up to 8GB. It adopts the SoC of RK3568 with integrated high-performance NPU, ideal for deep learning frameworks of TensorFlow, Caffe, Tflite, Pytorch, Onnx NN, Android NN, etc.
Advantages of Mixtile AI Object Detection Solution
Enables you to detect and classify objects in your images and videos in real-time to help you maximize your efficiency.
1. Visual AI acceleration, high efficiency and low power consumption, accurate recognition and wide recognition range
2.?Empower Diverse Industrials:
3.?Supports a wide range of connectivity options, including high-speed interfaces such as PCIe 3.0, USB 3.1, and HDMI 2.1. This means that it can easily interface with a wide range of sensors, cameras, and other peripherals that are commonly used in object detection applications.
4. Build specific businesses to provide the premium solution.?Our products could be scaled to meet the needs of a wide range of applications, from small-scale projects to large-scale deployments. It could be easily integrated with your cloud-based solutions or other distributed systems.
Why do you choose Mixtile?
Professional Support
Dedicated account manager;?Over 10 years of R&D technical innovation and more than 15 people professional support team
Complete Technical Resources
Include SDK,?Development Documents, Technical Documents and Tutorials
Mixtile Community: https://community.mixtile.com/
Full Product Build Services
Mixtile’s premium R&D, production and after-sales service will transform your design concept into a saleable product