hopefully this is the right forum where I post this question.
I need to detect some fast objects with YOLOv3 in real time and I need to decide between systems for running. Maybe someone could give me some advice which of the following two systems might work (better).
In the system there are some aquatic organism (e.g. fishs), semi-transparent, with length 15 mm and width 3 mm swimming through a transparent tube with a velocity of at least 0.2 m/s.
The tube is filmed by a camera and the picture is analyzed by YOLOv3. Right now YOLOv3 is running with 6 FPS (416 x 416 pixel) on Jetson Nano. The goal is to reach 25 FPS or higher with YOLOv3 (or another real time detection algorithm, but not Tiny-YOLO). Therefore I am thinking about two different systmes:
The first idea would be to use the AGX Jetson Xavier. It is unclear if it can reach more than 25 FPS, based on the information found online (see link 1, 2 and 3). I found that it might be an option to get up to 50 FPS by using a plugin called nvyolo (see link 4 and 5). The question is if there is an option that would lead to a running system within an acceptable amount of time. At the moment, I was unable to find a system with direct Nvidia support.
The second idea is to buy up a computer with a high-quality GPU. I was thinking of Pascal Titan X, because it is recommended in pjreddies hardware guide (see link 6) or Geforce RTX 2080 Ti because it seems to perform great in real time detection (see link 7).
Maybe anyone has an idea or an estimation, which system should be preferably used for 25 FPS. But it would also be interesting, if both of them could reach 25 FPS. Also if it would be possible to use a lower performance GPU, e.g. Geforce GTC 2070.
Thank you for your help!
1 - https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=8&cad=rja&uact=8&ved=2ahUKEwi5p7mk4InmAhUs4aYKHbqbBooQFjAHegQIBRAC&url=https%3A%2F%2Fwww.mdpi.com%2F1424-8220%2F19%2F15%2F3371%2Fpdf-vor&usg=AOvVaw3lDYhXKsMOIu_7pgZOWtGA
2 - https://devtalk.nvidia.com/default/topic/1048211/yolov3-on-jetson-agx-xavier-developer-kit-with-ros-on-a-mobile-robot/
3 - https://github.com/opendatacam/opendatacam/issues/45
4 - https://devtalk.nvidia.com/default/topic/1049402/deepstream-sdk/deepstream-yolo-app-performance-vs-tensor-core-optimized-yolo-darknet/
5 - https://devtalk.nvidia.com/default/topic/1058408/jetson-agx-xavier/yolov3-fps-on-xavier/
6 - https://pjreddie.com/darknet/hardware-guide/
7 - https://lambdalabs.com/blog/best-gpu-tensorflow-2080-ti-vs-v100-vs-titan-v-vs-1080-ti-benchmark/