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hou-yz / MVDet

[ECCV 2020] Codes and MultiviewX dataset for "Multiview Detection with Feature Perspective Transformation".
https://hou-yz.github.io/publication/2020-eccv2020-mvdet
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Lightweight MVDet. #14

Closed zhangky666 closed 5 months ago

zhangky666 commented 1 year ago

Thank you for this article, I have a great reference! Now I want to apply it to the project, using the Jetson SUB DEVELOPER KIT. Its CPU and GPU have a combined memory of 16GB, which is obviously not compatible with MVDET's requirement for two graphics cards with more than 11GB of memory. So I would like to ask if there is a MVDET lightweight approach, or is there a lightweight approach to optimize it? Hope to hear from you soon.Best wishes.

hou-yz commented 1 year ago

thank you for your interest!

please check out our other repo MVDeTr and specify to use the conv architecture python main.py -d wildtrack --world_feat conv. this should return similar results to the vanilla MVDet and only takes one RTX 2080TI to run.

hope this helps.

best, Yunzhong

zhangky666 commented 1 year ago

Thanks for your reply. When I type "python main.py -d wildtrack --world_feat conv" in the terminal, it returns ”main.py: error: unrecognized arguments: --world_feat conv“. Is there anything I missed?

usage: main.py [-h] [--reID] [--cls_thres CLS_THRES] [--alpha ALPHA] [--variant {default,img_proj,res_proj,no_joint_conv}] [--arch {vgg11,resnet18}] [-d {wildtrack,multiviewx}] [-j NUM_WORKERS] [-b N] [--epochs N] [--lr LR] [--weight_decay WEIGHT_DECAY] [--momentum M] [--log_interval N] [--resume RESUME] [--visualize] [--seed SEED]

hou-yz commented 1 year ago

please use the MVDeTr repo instead of this one. this line python main.py -d wildtrack --world_feat conv refers to the main.py file in that repo.