can I compile it on windows system?

Hi, I want to convert your yolov2.weights to tensorflow .pb file, can you give me your .cfg file?

Thanks.

The function boxed_cam_to_velo in file "utils.py" projects the position of ground truth 3D bounding box to velo coordinate just with calibration matrix Tr_velo_to_cam. Does that mean the position is in camera 0 coordinate rather than rectified camera 0 coordinate? I have read some codes, such pointnet and frustum pointnets, which consider the position in rectified camera 0 coordinate.

In https://github.com/AI-liu/Complex-YOLO#result, predicted box and predicted class is drawn.
But, I think that eval.py draws only predicted box and target box. So, I want to know how to get predicted class from all_boxes.

There are 7 classes : https://github.com/AI-liu/Complex-YOLO/blob/master/utils.py#L11
But you have written code to accept 8 classes. With 7 classes the output tensor channels will be (6+1+7) x 5 = 70. In this implementation output tensor channels are 75 (https://github.com/AI-liu/Complex-YOLO/blob/master/complexYOLO.py#L74). Am I missing something or this is a mistake?

Thanks.

Hi Al-liu,
thank you for your implementation!
According to the cfg file in your repository the model should have 46935494 trainable parameters. However, your weight file contains only 46931945 weights. That is a difference of 3549.
It would be great if you could explain.
Many thanks!

The Complex-YOLO paper shows oriented bounding boxes in bird view images and the authors injects a predefined height for every object. Do you finish the orientation regression and injecting the predefined height?

KIndly mention how you designed anchors below

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Hi @AI-liu ,
Using the same hyperparameters from the repo, I trained it for 200 epochs on KITTI. It overfits to the train data. After training, I checked the first 100 images output using eval.py. It only gives outputs for train dataset and not for validatation dataset. Did you use same code and hyperparams for your results in the repo?

so i need to train the network but got confused to acquire labels , how did you get labels on Projection of LIDAR frame ?

Hello @AI-liu,

You have done wonderful work. The pretrained model you provided is based on DarkNet training. How about training with this repo pytorch code. Is is incomplete? I was training with your code, but couldn't get good results. Please share your results.

Thanks.

Hello everyone, in the middle of training i am facing the following issue. please help if anyone knows about this problem:
File "/media/imad/Windows/3d folder/Complex-YOLOv3/utils/utils.py", line 346, in build_targets
best_ious, best_n = ious.max(0)
RuntimeError: cannot perform reduction function max on tensor with no elements because the operation does not have an identity

Could you please share a direct link to the pre-trained model weights file (for your PyTorch implementation)?
Thanks!

The original paper can predict precise 3d box, does this 2d box can generat 3d box?

I am curious about how you process rotated rectangle iou in your code?

best.

Hello,
Thank you for sharing such a good implentation of Complex-YOLO :-)

after run python3 main.py, I got 20's of ComplexYOLO_epochxxx
and I ran python3 eval.py after modifying data path but Error occurred like below

Traceback (most recent call last):
  File "eval.py", line 93, in <module>
    target, target_num= get_target(label_file, calib['Tr_velo2cam'])
ValueError: too many values to unpack (expected 2)

any idea to resolve it?

hi @AI-liu thanks for the wonderful code . Just had a few queries

1. are there any steps how to augment the data(custom)
2. if i am using augmentation which feature of augmentation should i choose

Thanks in advance

Thank for your source code and can we use the network directly to deal with the single-line radar point cloud data?

Hi @AI-liu ,
Did you evaluate mAP on the KITTI? were you able to get the scores mentioned in the paper?

Hello everyone, can someone please suggest me point cloud annotation tool to label my lidar data with output similar to Kitti dateset format....
Thank you.

How to handle rotated objects using anchors?

Thanks for you share.however,I cann't load you pretrained weights.

Thank you very much for the code you provided, and I've been working on point cloud detection recently, so I sincerely hope to get the model files after your training. Thank you very much.

How do I train on own data, I already generated data/labels, but in my case I have 3 classes. So I decided to run and changed the

region_loss = RegionLoss(num_classes=8, num_anchors=5)
to
region_loss = RegionLoss(num_classes=3, num_anchors=5)
and got an error:
RuntimeError: shape '[12, 5, 10, 16, 16]' is invalid for input of size 230400

seems like second and third element of the output shape should be equal to 75 if multiplied together. But not sure what should I change to introduce different amount of classes.

It's a bit difficult to download weight using pan.baidu link for the foreigner

I publicly shared my NAS link to download this weight.
It'll be expired at 25/08/2019

https://gofile.me/3TjkG/u3XtTjGTe
(link is available by 2021.06)

楼主您好，我觉得这篇论文最大的创新就是在yolo上增加了角度预测，但是看您的结果预测框并没有角度

Hi,
Thanks for sharing this amazing work,
but it seems the pre-trained model share link expired and was cancelled，
Is it convenient to provide a link?
Thank you very much！