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apfnet's Issues
请问作者一共训练了多长时间呢?用的什么服务器呢?
模型测试问题(pytorch版本)
imagenet权重
您好,我看您的代码里面没有mdnet_imagenet_vid.pth权重,可以提供一下吗?谢谢
如何选择最终的模型权重呢
作者您好!请教问下您在最后一个阶段训练时,怎么选择最终的模型权重呢?我这边复现了您的实验,最后一阶段训练结束后,控制台输出的Mean Precision只有60%多,请问这个复现数据有问题吗?您当时达到多少了呢?
log文件问题
这个项目第二、三阶段的训练以及测试都需要log文件,请问项目中为什么没有log文件呀?
Challenge Tag
I'm trying to train APFNEt but I have a problem with creating .pkl files for different challenge types. There is no .tag file (for example fast_motion.tag) in RGBT-234 or GTOT datasets. Have you created these tag files on your own? Do you have end can you share them with me? If you don't have them, can you tell me how to create them? Thank you very much.
if challenge_type == 'FM': challenge_inf = 'fast_motion.tag' elif challenge_type == 'OCC': challenge_inf = 'occlusion.tag' elif challenge_type == 'SC': challenge_inf = 'size_change.tag' elif challenge_type == 'ILL': challenge_inf = 'illum_change.tag' elif challenge_type == 'TC': challenge_inf = 'thermal_crossover.tag' elif challenge_type == 'ALL': data[seqname] = {'images_v':img_list_v, 'images_i':img_list_i, 'gt':gt}
about CMPP results
hello!
Thank you very much for your contribution in the field of RGBT object tracking. I reproduced your code and got excellent results. I have a question, how did you obtain the results of CMPP and CAT during the evaluation, I did not find relevant data or codes. I would be very grateful if you could help me!
数据集的问题
您好,我想问一下您提供的RGBT234的数据集里面没有rgbt.txt文件,我在官方文件里面下载txt文件没问题吧?为什么一直提示我找不到文件呢?希望作者能解答一下,谢谢
Pretrained Model Link
Link of pretrained model is broken or I can't reach it because of Baidu's policies. Can you renew it or upload to another cloud platform except Baidu?
属性标签
作者您好,请问您知道lasher的数据集怎么生成或制作tag属性标签吗?我看GTOT和RGBT234数据集都有
下载的GTOT数据集里没有challenge tag
关于RGBT234数据集
您好!我非常喜欢您的工作,然而我也同样遇到了数据集的问题,带有init.txt标注文件的RGBT234数据集无法找到,项目中的百度云链接目前已经无法下载,请问能否发布新的下载链接?
关于预训练权重mdnet_imagenet_vid.pth的问题
作者你好,我在您的网络结构基础上更改了一些结构,这样就导致之前的mdnet_imagenet_vid.pth的初始化参数匹配不上,我想问如果我不采用mdnet_imagenet_vid.pth初始化权重直接手动初始化,会很难收敛吗
model_stage3代码问题
output = torch.bmm(affinity, w_v)
# output=output.permute(0,2,1)
# output=self.transformer1_FFN[1](nn.Dropout(0.2)(F.relu(((self.transformer1_FFN[0](output))))))
# output=output.permute(0,2,1)
output=output.reshape(batch,dim,w,h)
output=self.transformer1_encoder1[3](output)
x=x+output
return x
你好,我想问一下按照您论文里面figure3的encoder的部分是先进行了自注意力后再add再升通道的,但是按照您model_stage3.py里面就是上面的代码是进行了自注意力后先升通道再与原始值相加的,请问是我理解有问题吗?
About generating the LasHeR dataset five attribute branches
Hello, are you training the code on the LasHeR dataset again? How did you divide the dataset attribute branches? If possible, can you provide the partitioned dataset or code for partitioning? I will be very grateful!
关于评测工具的问题
作者你好,为什么我直接从GitHub上直接下载下来的RGBT234的数据结果,用MATLAB跑上面说Precision是0.815,Success是0.561啊?我都没有修改
复现结果
您好,我想问一下在RGBT234上论文里的结果是82.7%/57.9%,GTOT的结果是90.5%/73.7%,我复现的结果在RGBT234上是80.4%/55.5%,GTOT上是88.4%/71.8%。直接使用您的模型在GTOT上跑的结果是88.7%/72.2%。请问这样的结果是正常的吗?我要怎样才能达到论文的精度?
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