Exciting news! We are thrilled to unveil the latest hardware benchmarks for the cutting-edge Raspberry Pi 5 featuring the Arm Cortex A76 processor @ 2.4GHz. Dive into the comparison between the Raspberry Pi 5 and 4 models, as well as other edge hardware platforms, using the powerful YOLOBench tool.
Discover YOLOBench, a latency-accuracy benchmark featuring over 900 YOLO-based object detectors tailored for embedded applications. The research presented at the ICCV 2023 RCV workshop serves as the foundation for this innovative benchmark.
Explore the interactive YOLOBench app on HuggingFace Spaces to pinpoint the perfect YOLO model for your edge device. Don't miss out on this opportunity to optimize your hardware performance!
YOLOBench is a comprehensive benchmark that evaluates over 900 YOLO-based object detection models on four different datasets (COCO, PASCAL VOC, WIDERFACE, and SKU-110K) on many embedded hardware platforms now including the Raspberry Pi 5.
YOLOBench provides a fair and controlled comparison of these models by using a fixed training environment (code and training hyperparameters). It also collects accuracy and latency numbers for each model and dataset combination. YOLOBench considers multiple dimensions of the model search space such as depth-width variations and different input resolutions. By analyzing these numbers, you can easily and quickly find the Pareto-optimal models that achieve the best trade-off between accuracy and speed for your edge device.
Based on your feedback, we have also enhanced the YOLOBench experience enabling you to compare benchmark results between different hardware platforms!
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Want to add your own hardware to YOLOBench?
Our initial set of benchmark hardware is just a start! Showcase your hardware with YOLOBench users by adding your benchmark data on your devices. If you’d like to have your hardware benchmarked on over 900 YOLO-based object detectors you can find the instructions on next steps here and we’ll get right back to you!
GET MY YOLOBENCH HARDWARE KIT!
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