visdrone / visdrone-dataset Goto Github PK

Dear VisDrone,
I'm working on visdrone task1, I really want to know the differences between 2018 and 2019 DET datasets.
Are they the same as each other?
If not, which aspects are they different in? Does they have overlaps with each other?
Thanks a lot :)

There should be 10 categories. Yet 0-11 all occurs, meaning that there could be 12 categories. What is category to id mapping?

I found that your dataset of cc only contains annotation of trainlist.

hey, How can I convert VisDrone Video Object Detection Dataset to yolov5 annotations and folders order.

thanks!

rt

I want to annotate my custom data to make a similar format to visdrone.
Are there any open source/free annotation tools?

Thanks

I have downloaded the dataset but the annotation data format is not mentioned and the class name too,]

How to identify data format inside the annotation file ? (Eg : xmin,ymin,xmax,ymax)

I want to ask you a question, are all videos in your dataset at the same frame rate? If the frame rate is the same, what is the frame rate? If the frame rate isn't the same, what are the kinds?

I notice that the annotation files looked like that

1,0,19,783,60,91,1,1,0,0
2,0,16,782,60,91,1,1,0,0
3,0,13,781,60,91,1,1,0,0
4,0,11,780,60,91,1,1,0,0

How should i understand the annotation?
Is it something like that?
<Target ID>, <frame number>, <bbox_left>,<bbox_top>,<bbox_width>,<bbox_height>,<score>,<object_category>,<truncation>,<occlusion>

How may i display the bounding boxes such that it look like that? I do not need the class, but i just need the ID and the bounding box.

Or something like that

请问这个数据集都是可见光的吗，还是有红外的图片？

I downloaded Task 2 dataset and unzipped it, then i got the annotation files and the format like below:

1,0,593,43,174,190,0,0,0,0
2,0,592,43,174,189,0,0,0,0
3,0,592,43,174,189,0,0,0,0
4,0,592,43,174,189,0,0,0,0
5,0,592,43,174,189,0,0,0,0
...

I found below description,

 <bbox_left>,<bbox_top>,<bbox_width>,<bbox_height>,<score>,<object_category>,<truncation>,<occlusion>


    Name                                                  Description
-------------------------------------------------------------------------------------------------------------------------------     
 <bbox_left>	     The x coordinate of the top-left corner of the predicted bounding box

 <bbox_top>	     The y coordinate of the top-left corner of the predicted object bounding box

 <bbox_width>	     The width in pixels of the predicted object bounding box

<bbox_height>	     The height in pixels of the predicted object bounding box

   <score>	     The score in the DETECTION file indicates the confidence of the predicted bounding box enclosing 
                     an object instance.
                     The score in GROUNDTRUTH file is set to 1 or 0. 1 indicates the bounding box is considered in evaluation, 
                     while 0 indicates the bounding box will be ignored.
                      
<object_category>    The object category indicates the type of annotated object, (i.e., ignored regions(0), pedestrian(1), 
                     people(2), bicycle(3), car(4), van(5), truck(6), tricycle(7), awning-tricycle(8), bus(9), motor(10), 
                     others(11))
                      
<truncation>	     The score in the DETECTION result file should be set to the constant -1.
                     The score in the GROUNDTRUTH file indicates the degree of object parts appears outside a frame 
                     (i.e., no truncation = 0 (truncation ratio 0%), and partial truncation = 1 (truncation ratio 1% ~ 50%)).
                      
<occlusion>	     The score in the DETECTION file should be set to the constant -1.
                     The score in the GROUNDTRUTH file indicates the fraction of objects being occluded (i.e., no occlusion = 0 
                     (occlusion ratio 0%), partial occlusion = 1 (occlusion ratio 1% ~ 50%), and heavy occlusion = 2 
                     (occlusion ratio 50% ~ 100%)).

But I think the description is quite different video annotation.
how to interprete this? thank you.

VisDrone2019-DET-test-challenge 里面只有图片

Hi how convert VisDrone annotations to yolo v7 format ?

Dear authors,
Thank you for sharing a good dataset for object detection as well as tracking.
I am trying to find Visdrone 2019 video (NOT sequential frames) with demo purpose.
Could you provide me Visdrone 2019 raw video?

Thank you

The PaddleDetection team provides an extremely high precision and speed VisDrone DET baseline PP-YOLOE, and also provides a link to download the converted COCO format dataset. Welcome to use it！

PaddleDetection团队提供了一个极高精度和速度的VisDrone DET数据集的baseline PP-YOLOE，还提供了转好COCO格式的数据集下载链接。欢迎使用！

ModelZoo：

Appreciating your work. However, will there be a toolkit in Python (most of trackers nowdays are written in Python, I suppose) ?
Thanks in advance.

I found this picture in the paper "Vision Meets Drones: Past, Present and Future", but no raw results. So where can I find the raw results of the Visdrone SOT test_dev ?

I found that the size of the bbox given in the mot dataset is much larger than the size of the actual object, is this normal? The bbox looks like this

Thank you very much if you can make some suggestions！

I'm appreciating your project, I would like to collect some datas myself and need to refer to your flight altitude, please help me, thank you

Hi, could you please provide the specific camera model information?

Hai is the dataset for VisDrone 2018 and VisDrone 2019 contain the same images and annotations?

1.The datasets are named as 2019 datasets, where are the 2020 datasets.
2.Are the annotations the same as mentioned in https://github.com/VisDrone/VisDrone2018-DET-toolkit

hello，The annotation file format : 684，8，273，116，0，0，0，0 ;

how to konw these number in someone format ? like this : x_min,y_min ,x_max,y_max or other detail

I want to train YOLO V3 for object detection on VisDrone dataset , for the YOLO V3 training I want to resize all the images to 416 x 416 and also change Annotations accordingly .

Is there any method or suggestions to do it ?

hello, your evaluation system maybe need fix bug.
when I submit my result to the evaluation system, I found my submission is in updated status over one hour, like the picture. I don't know the reason for this, maybe you can solve my problem.

Hi

Please add a license file, e.g. MIT.

Thanks.

Hi,

Could you please share the specific value or range of height/altitude at which the static images and videos have been captured and recorded respectively for the object detection. I would be grateful for your positive response.

Thanks,

您好！请问数据集中有附有采集数据时使用的摄像头的内参信息和拍摄角度吗？因为我想使用数据集检测的结果进行一个简单的位置估算，所以可能需要这些参数，不知道您是否方便提供？谢谢！

i have the result in test dataset,but the format is coco json.how can i change to the visdrone official format

I was trying to plot the ground truth labels on video dataset of visdrone. The annotation format is like -

Visdrones Video Detection dev- test set -
ann = 98 ,0 ,808 ,1 ,47 ,22 ,1 ,4 , 0, 0

I am aware of the DET format and in this VID format ann[2] to ann[5] is bbox, ann[6] is category.

1. Is ann[7] score?
2. ann[8] = truncation?
3. ann[9] = occlusion?
   I assumed ann[0] as index and ann[1] as frame. But when I plot the ground truth on the image I found ann[0] as frame and now I am not sure what ann[1] is.

Could you please clarify what annotations are? Thanks.

Hi,

I just want confirm that what is the frame rate of the frames in the MOT challenge? I believe it's not 30, maybe 15 or even less?

Thanks.

Does the VisDrone-Dataset correspond to the class[ 'pedestrian', 'people', 'bicycle', 'car', 'van', 'truck', 'tricycle', 'awning-tricycle', 'bus', 'motor']?

hello
could you please share the VisDrone 2019 dataset coco annotation format?

您好，请问红外图像的波段是在什么范围？

wait for it coming, hope the evaluation process of VisDrone and the leaderboard can be easy to use.

Hi, I'm not sure if this project is still being maintained. When I was studying on vehicle detection and tracking with VisDrone, there's seldom researches that I can compete with. I think the main reason is that there's no public annotations for test-challenge subset and most of the teams didn't report their local evaluation results on test-dev.

So, like COCO, maybe it's more preferable for organizers to recommend participates to report results of both test-dev and test-chanllege (of course only the latter one is taken in to consideration for competition).