ivalab / AffKpNet

The implementation and supplementary material for our RA-L work "An Affordance Keypoint Detection Network for Robot Manipulation".
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Is anyone successful for configuring the environment? #5

Open ZiqiLoveSunshine opened 1 year ago

ZiqiLoveSunshine commented 1 year ago

First of all, I tried python==3.6 and follow the step of configuring the environment of maskrcnn-benchmark as mentioned, when I succeded with the environment of maskrcnn-benchmark, I returned to this project and tried to install

cd AffKpNet 
python setup.py install

however, it told me that python version must>=3.8

so then, I used python==3.8, torch==1.6.0, torchvision==0.7.0, cudatoolkit=10.1 and followed the steps of maskrcnn-benchmark as well. It compiles successful, However, when it comes to execute the code, there is always some errors subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1.

how should I do? I have no idea.

Knightbreeze commented 1 year ago

@GuoyuloveSunshine Hello, I recently are trying to configure the environment, met the same problem with you, you then have to solve the subprocess. CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1. this problem?

ZiqiLoveSunshine commented 1 year ago

No, I give up configuring this project, there are lots of compiling errors that I cannot solve, I probably use the dataset that they provide to train another network later.

Knightbreeze commented 1 year ago

@GuoyuloveSunshine Thanks for your reply. I failed after many attempts. May I ask if you have any new networks about the affordance detection and used for manipulator fetching? I want to learn and replicate related aspects recently, but there are few open source RGB-D image-based networks during the search on the Internet. So if there is a new network also hope to recommend some.

ZiqiLoveSunshine commented 1 year ago

I am sorry I cannot give you any useful advice about the network, as I begin to tacile with the manipulation trajectories and didn't insist on the grasping part, perheps you can try to search 'manipulation affordance' or 'grasping', There may be some repository that can help you.