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zhengthomastang / 2018AICity_TeamUW

The winning method in Track 1 and Track 3 at the 2nd AI City Challenge Workshop in CVPR 2018 - Official Implementation
http://openaccess.thecvf.com/content_cvpr_2018_workshops/w3/html/Tang_Single-Camera_and_Inter-Camera_CVPR_2018_paper.html
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How to run the yolo detection with the model provided? #24

Open estimate123 opened 3 years ago

estimate123 commented 3 years ago

Hi, I want to know how can I run yolo detection with your model provided? I don't understand the given examples in your bashfile track1.sh ./darknet procimgflr cfg/aicity.data cfg/yolo-voc.cfg yolo-voc_final.weights /home/ipl_gpu/Thomas/aicity18/Track1/Loc1_1/img1/ /home/ipl_gpu/Thomas/aicity18/Track1/Loc1_1/detimg1/ /home/ipl_gpu/Thomas/aicity18/Track1/Loc1_1/det.txt .1 .5 0 1799

What are the images in '/home/ipl_gpu/Thomas/aicity18/Track1/Loc1_1/detimg1/ ', what are they used for? Is /Loc1_1/det.txt the file that saves the result( in the format of MOTChanllenge)? And what is 'procimgflr' option? On my conputer I try to run this command but my computer gives me error（Not an option: procimgflr). Sorry, I'm really new to this, right now I want to try to use your given model to successfully detect and get the MOT format output, your help would means a lot to me, thanks : )

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zhengthomastang commented 3 years ago

Here is the definition of all the parameters: 

./darknet procimgflr <config file> <model weights> <input image folder> <output image folder> <output text file> <confidence threshold> <hierarchy threshold> <starting frame count> <ending frame count>

Here is the corresponding function to call for procimgflr (processing image folder): https://github.com/zhengthomastang/2018AICity_TeamUW/blob/master/Track1/3_YOLO_VEH/examples/detector.c#L699-L764