Re: LDC 1.32.0-beta1
On Tuesday, 28 February 2023 at 06:01:51 UTC, newbie wrote: find one error for musl + aarch64: ```sh /ldc2/bin/../import/core/sys/posix/sys/stat.d(1659): Error: alias `core.sys.posix.sys.stat.__mode_t` conflicts with alias `core.sys.posix.sys.stat.__mode_t` at /ldc2/bin/../import/core/sys/posix/sys/stat.d(662) ``` This was fixed upstream, but didn't make it into v2.102 unfortunately: https://github.com/dlang/dmd/pull/14793
Re: D Language Foundation January 2023 Quarterly Meeting Summary
On Monday, 27 February 2023 at 23:00:41 UTC, Mike Parker wrote: On Monday, 27 February 2023 at 12:08:58 UTC, newbie wrote: betterC is much more important for some user, please don't phase out `-betterC`. BetterC isn’t going anywhere. Too many people use it. Using word "Too" is scary enough for me here :D
Re: Centroid tracking using DCV
On Tuesday, 28 February 2023 at 12:29:05 UTC, Sergey wrote: On Tuesday, 28 February 2023 at 12:08:14 UTC, Ferhat Kurtulmuş wrote: On Wednesday, 15 February 2023 at 17:32:33 UTC, Ferhat Kurtulmuş wrote: I heard you are not having fun enough with d today. Hello everyone, We have mir.ndslice and dcv, and then we should be able to run, for instance, tinyYOLOv3 with video streams. I believe that such applications will attract more people's attention to d. Here is how it looks like and the source code: https://www.youtube.com/watch?v=m3ex9lDELfQ https://github.com/aferust/dcv-tinyyolov3 Great job. Could we have any comparison in the performance/memory usage versus original solution in Python? I have not conducted any comparisons yet. There are a lot of factors affecting performance. My old laptop lacks good cuda support, so I disabled the CUDA acceleration. I cannot give you a strongly backed test result, but I can say that preprocessing is not so costly in my example. The FPS drop is primarily due to onnxruntime itself. The preprocessing step only takes 2 or 3 msecs. The newer versions of onnxruntime have various backend options for acceleration, such as CUDA, tensorrt, directML (uses directX).
Re: Centroid tracking using DCV
On Tuesday, 28 February 2023 at 12:08:14 UTC, Ferhat Kurtulmuş wrote: On Wednesday, 15 February 2023 at 17:32:33 UTC, Ferhat Kurtulmuş wrote: I heard you are not having fun enough with d today. Hello everyone, We have mir.ndslice and dcv, and then we should be able to run, for instance, tinyYOLOv3 with video streams. I believe that such applications will attract more people's attention to d. Here is how it looks like and the source code: https://www.youtube.com/watch?v=m3ex9lDELfQ https://github.com/aferust/dcv-tinyyolov3 Great job. Could we have any comparison in the performance/memory usage versus original solution in Python?
Re: Centroid tracking using DCV
On Wednesday, 15 February 2023 at 17:32:33 UTC, Ferhat Kurtulmuş wrote: I heard you are not having fun enough with d today. Hello everyone, I was looking for ways to run pre-trained DCNN models (inference) using D. I then ran across onnxruntime, which has a c API. Luckily, it has a bindbc binding readily available. Nowadays, to run inference routines of CNN models, we only need some basic image processing to satisfy the input shape requirements of those models. We have mir.ndslice and dcv, and then we should be able to run, for instance, tinyYOLOv3 with video streams. I believe that such applications will attract more people's attention to d. Here is how it looks like and the source code: https://www.youtube.com/watch?v=m3ex9lDELfQ https://github.com/aferust/dcv-tinyyolov3
Re: Centroid tracking using DCV
On Wednesday, 15 February 2023 at 17:32:33 UTC, Ferhat Kurtulmuş wrote: I heard you are not having fun enough with d today. Do you know you can do things like this with dlang now? After some fiddling with it, my last commits made this possible. how it looks like: https://www.youtube.com/watch?v=ACC_-TDAtqc source code: https://github.com/aferust/oclcv/tree/main/examples/centroidtracking DCV: https://github.com/libmir/dcv Sorry for the potato-quality video. My art director is on vacation. I am cheating a little with OpenCL since things are not fast enough at the moment. Hope you like it. Enjoy! Hello everyone, I was looking for ways to run pre-trained DCNN models (inference) using D. I then ran across onnxruntime, which has a c API. Luckily, it has a bindbc binding readily available. Nowadays, to run inference routines of CNN models, we only need some basic image processing to satisfy the input shape requirements of those models. We have mir.ndslice and dcv, and then we should be able to run, for instance, tinyYOLOv3 with video streams. I believe that such applications will attract more people's attention to d. Here is how it looks like and the source code: https://www.youtube.com/watch?v=m3ex9lDELfQ https://github.com/aferust/dcv-tinyyolov3
