Open funkydvd opened 3 years ago
Hi, have you find out the solution? I also want to use this project but I can not find a way to visualize the predicted trajectory.
Hi, unfortunately, we do not have a way to do proper visualization.
Do you know how I should use my own data set for trajectory prediction and evaluation, how can I find the data generated by the evaluation and use them to calculate relevant metrics?
您好,请问您找到解决方案了吗?我也想使用这个项目,但我找不到可视化预测轨迹的方法。
"Setup.py" resources download problem in TrackNPred I keep failing to download. Do you have any saved files? If so, can you share a copy of me
您好,请问您找到了解决方案吗?我也想使用这个项目,但我找不到可以预见的方案的。
TrackNPred 中的“Setup.py”资源下载问题>>resources/data/TRAF/TRAFx/densep.npy 我一直无法下载。你有保存的文件吗?如果是这样,你能分享一份我的副本吗
您好,请问您找到解决方案了吗?我也想使用这个项目,但我找不到可视化预测轨迹的方法。
"Setup.py" resources download problem in TrackNPred I keep failing to download. Do you have any saved files? If so, can you share a copy of me
Nah I haven't look at this project for a long time and I already forgot about that lol
您好,请问您找到解决方案了吗?我也想使用这个项目,但我找不到可视化预测轨迹的方法。
"Setup.py" resources download problem in TrackNPred I keep failing to download. Do you have any saved files? If so, can you share a copy of me
Have you found the new download link? Can you share it with me, thank you very much.
First of all, congrats for the strong work here. However, as far as I inspected the code, the prediction module offers only an evaluation function, which doesn't offer much information. Is there an easy way to modify the code in order to see for each frame the center of the predicted objects, for example, in order to compare it with the actual center of the object? Also, the prediction is done for 3 seconds in the future? I want to make some experiments regarding trajectory prediction and it would be nice if I could use your project, but I need to vary the prediction time and also to see for each frame the predicted objects/ the predicted center for the objects, in order to compute the difference between the predicted center and the ground truth. I am interested specifically in car prediction. I see that you use Mean Suared Error and that the magic happens in maskedMSETest, however I don't really know what is the link between frames, object coordinates and the tensors x, y, muX, muY. Any help in order to detect the predicted objects and to change the prediction time will be greatly appreciated.
L.E.: How is the MSE computed? It takes only the detected objects and their centers?