meta_trackers's People
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huaxinxiao codegank jiangfeng-xiong ouya-bytes abdelpakey mrdoer zhengzhenxian xhwxd remgao fengyen-chang dl-85 afcarl dreamyit 2017tjm yangkang779 jiaweihe1996 kriszhou1 ucasqcz seafishzha jacke121 fybaft2012 tobeagoodprogrammer yushenxiang mudiaoxu xuexia7023 iamweiweishi deepcharle gbzhucherish wpfhtl enqing626 sysu-shey meimeixu520 xieyunjiao lc790 huangjing0746 mjt1312 msathishkumar1990 edinesh90 ddoublesql yzlicloud minyuedayuanmeta_trackers's Issues
No such file or directory: '../../dataset/OTB/tb_100.txt'
Traceback (most recent call last):
File "run_tracker.py", line 405, in
with open(list_path) as f:
FileNotFoundError: [Errno 2] No such file or directory: '../../dataset/OTB/tb_100.txt'
Simple example
Can you add a simple example that can work on a custom sequence/video initialization?
Change the CNN Model
Dear @silverbottlep,
Thank you for your fantastic work.
I want to change the Base CNN model of your code via another one (e.g., ResNet18). Do you have any idea that how can I do that?
KeyError: 'conv1.weight'
when I run "run_tracker" in meta_crest, it doesn't work and tell me that KeyError: 'conv1.weight', and i am confused,can you tell me how to solve it.
My interpretation of this project?
As far as MetaSDNet is concerned, I think meta-learning plays a role in learning good initial parameters in order to adapt the network to the changes in future frames. In addition, since the parameters learned by the meta-learning are used, only the iteration is required once in the first frame and the required samples are reduced, which brings the advantage of speed increase(MDnet iterates 30 times in the first frame, positive sample 500, negative sample 5000). In the tracking of subsequent frames, the same settings as MDNet are used. The main purpose of the article is to use meta-learning to get a good initialization parameter. I don't know if my understanding is right?
Thank you for your contribution!
The doubt about random results
Hi, @silverbottlep , thaks for your excellent work. I just run your code (meta_sdnet/run_tracker.py) and find that you fix the seed in the experiment, like np.random.seed(1), torch.manual_seed(2) and torch.cuda.manual_seed(3). But i still find that the result is random, could you explain this ?
Hello, would you please share the otb results of the 30-15-pyMDNet ?
Hello, thanks for your contribution ๐
- Just as the title mentioned, would you please share the results of the 30-15-pyMDNet ?
Thanks in advance!
Best regards
could not find the definition of variable 'weights'
At line 52 in file 'meta_crest/model.py', there is a usage of variable 'weights', but I do not find where is the definition of 'weights'.
meta-learning on customized networks
Dear @silverbottlep ,
I am writing a meta-tracker on siamFC network, please give me some suggestions on the reproduce steps
Thank you so much,
I have solved many bugs in the code!
Great job!
1.the mat file is not imagenet-vgg-verydeep-16.mat but the imagenet-vgg-m.mat, you can download in
http://www.vlfeat.org/matconvnet/models/imagenet-vgg-m.mat
- The cpu version doesn't work, so GPU is necessary for you!
AttributeError: 'MetaSDNet' object has no attribute 'named_parameters'"
Hello, I wonder that in meta_model.py, there is not self.named_parameters(), could you please tell me the reason?
Hello, why are 'create_graph' arguments these places True?
inconsistent result with python 2.7
Someone tried meta_crest with pre-trained model with python 2.7, he reported it gave different result. When he changed to python 3.5, he could reproduce the result. At this point, I have no idea, hopefully have a chance to look at it later. FYI, my environment was python 3.6, pytorch 0.2.0+3f6fccd.
Can someone run through this tracking code?
The tracking code is missing images.txt and otb_100, and the VID dataset can't be done now.
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