honglinchu / siamtrackers Goto Github PK

(2020-2022)The PyTorch version of SiamFC，SiamRPN，DaSiamRPN, UpdateNet , SiamDW, SiamRPN++, SiamMask, SiamFC++, SiamCAR, SiamBAN, Ocean, LightTrack , TrTr, NanoTrack; Visual object tracking based on deep learning

License: Apache License 2.0

Python 90.88% C 6.93% Shell 0.23% Cython 1.97%

tracking deep-learning visual-tracking

siamtrackers's Introduction

SiamTrackers

NanoTrackV1

Experiment

NanoTrack is a lightweight and high speed tracking network which mainly referring to SiamBAN and LightTrack. It is suitable for deployment on embedded or mobile devices. In fact, V1 and V2 can run at > 200FPS on Apple M1 CPU.

Trackers	Backbone Size(*.onnx)	Head Size (*.onnx)	FLOPs	Parameters
NanoTrackV1	752K	384K	75.6M	287.9K
NanoTrackV2	1.0M	712K	84.6M	334.1K
NanoTrackV3	1.4M	1.1M	115.6M	541.4K

Experiments show that NanoTrack has good performance on tracking datasets.

Trackers	Backbone	Model Size(*.pth)	VOT2018 EAO	VOT2019 EAO	GOT-10k-Val AO	GOT-10k-Val SR	DTB70 Success	DTB70 Precision
NanoTrackV1	MobileNetV3	2.4MB	0.311	0.247	0.604	0.724	0.532	0.727
NanoTrackV2	MobileNetV3	2.0MB	0.352	0.270	0.680	0.817	0.584	0.753
NanoTrackV3	MobileNetV3	3.4MB	0.449	0.296	0.719	0.848	0.628	0.815
CVPR2021 LightTrack	MobileNetV3	7.7MB	0.418	0.328	0.75	0.877	0.591	0.766
WACV2022 SiamTPN	ShuffleNetV2	62.2MB	0.191	0.209	0.728	0.865	0.572	0.728
ICRA2021 SiamAPN	AlexNet	118.7MB	0.248	0.235	0.622	0.708	0.585	0.786
IROS2021 SiamAPN++	AlexNet	187MB	0.268	0.234	0.635	0.73	0.594	0.791

For NanoTrackV1, we provide Android demo and MacOS demo based on ncnn inference framework.
We also provide PyTorch code. It is friendly for training with much lower GPU memory cost than other models. NanoTrackV1 only uses GOT-10k dataset to train, which only takes two hours on RTX3090.

OpenCV API

https://docs.opencv.org/4.x/d8/d69/classcv_1_1TrackerNano.html

Dataset

All json files BaiduYun parrword: xm5w (The json files are provided by pysot)

Test

OTB2015 BaiduYun password: t5i1
VOT2016 BaiduYun password: v7vq
VOT2018 BaiduYun password: e5eh
VOT2019 BaiduYun password: p4fi
VOT2020 BaiduYun password: x93i
UAV123 BaiduYun password: 2iq4
DTB70 BaiduYun password: e7qm
UAVDT BaiduYun password: keva
VisDrone2019 BaiduYun password: yxb6
TColor128 BaiduYun password: 26d4
NFS BaiduYun password: vng1

Train

GOT10k BaiduYun password: uxds
LaSOT BaiduYun password: ygtx
ILSVRC2015 VID BaiDuYun password: uqzj
ILSVRC2015 DET BaiDuYun password: 6fu7
YTB-Crop511 BaiduYun password: ebq1
COCO BaiduYun password: ggya
TrackingNet BaiduYun password: nkb9 (Note that this link is provided by SiamFCpp author)

Mask

YTB-VOS BaiduYun password: sf1m
DAVIS2017 BaiduYun password: c9qp

Toolkit

Matlab version

OTB2013/2015 Github
UAVDT BaiduYun password: ehit
VOT2016-toolkit BaiduYun password: 272e
VOT2018-toolkit BaiduYun password: xpkb

Python version

pysot-toolkit： OTB, VOT, UAV, NfS, LaSOT are supported.BaiduYun password: 2t2q
got10k-toolkit：GOT-10k, OTB, VOT, UAV, TColor, DTB, NfS, LaSOT and TrackingNet are supported.BaiduYun password: vsar

Papers

BaiduYun password: fukj

Reference

[1] SiamFC

Bertinetto L, Valmadre J, Henriques J F, et al. Fully-convolutional siamese networks for object tracking.European conference on computer vision. Springer, Cham, 2016: 850-865.
   
[2] SiamRPN

Li B, Yan J, Wu W, et al. High performance visual tracking with siamese region proposal network.Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018: 8971-8980.

[3] DaSiamRPN

Zhu Z, Wang Q, Li B, et al. Distractor-aware siamese networks for visual object tracking.Proceedings of the European Conference on Computer Vision (ECCV). 2018: 101-117.

[4] UpdateNet

Zhang L, Gonzalez-Garcia A, Weijer J, et al. Learning the Model Update for Siamese Trackers. Proceedings of the IEEE International Conference on Computer Vision. 2019: 4010-4019.
   
[5] SiamDW

Zhang Z, Peng H. Deeper and wider siamese networks for real-time visual tracking. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019: 4591-4600.

[6] SiamRPNpp

Li B, Wu W, Wang Q, et al. SiamRPNpp: Evolution of siamese visual tracking with very deep networks.Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019: 4282-4291.

[7] SiamMask

Wang Q, Zhang L, Bertinetto L, et al. Fast online object tracking and segmentation: A unifying approach. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019: 1328-1338.
   
[8] SiamFCpp

Xu Y, Wang Z, Li Z, et al. SiamFCpp: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines. AAAI, 2020.

[9] SiamCAR
Guo D ,  Wang J ,  Cui Y , et al. SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2020.

[10] SiamBAN
Chen Z, Zhong B, Li G, et al. Siamese box adaptive network for visual tracking[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2020: 6668-6677.

[11] TrTr 
Zhao M, Okada K, Inaba M. TrTr: Visual Tracking with Transformer[J]. arXiv preprint arXiv:2105.03817, 2021.

[12] LightTrack 
Yan B, Peng H, Wu K, et al. Lighttrack: Finding lightweight neural networks for object tracking via one-shot architecture search[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021: 15180-15189.

siamtrackers's People

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wangaixue yangshuwen wangyangneu five-days wishgale dreadlord1984 manzhihuangnian benjamesbabala warmstoner lkw666 tangtangchx greengrass2015 mr-shang-del chuanfuye mammoth9 mc206 txtmiaopasi maklachur zhangqingsongha cb-jack-s buoucatlabuladuodog wind754203900 1522454735 mustansarfiaz taskkk wuxiaolianggit liu-longfei veryquant grapesonwang echanted-168 wavelet2008 sandy1230 janysunny ruhao-liu wyyhh kuailedagongzai lks-es wanetsui mc610 tonyhuang1998 killyseason suizhang96 sywdazlq wifispy zangqx zxf864823150 perhuaper shanjiayao bingxinyang totoro-wen happme zhuxiangbin wrxwd mmiaomei screw888 wangqiangjn xdfanfan ysd-980201 bamboopu zxs789 stiphyjay terry1iu zj717754140 scott-mao qinsiyuan1213 lingguomeng banben fanchao1 lewisli66 noticeable msathishkumar1990 zsl4399 ste7an-cs liweimcc andudu huchenjie339 whjzsy lvpengfeinj shjy11 dome2322 xurui-ryan intouchable-vs lijihw08 shipingsong superjeary eddieleng1997 ngsford daydayupdyp sylan2019 seamasz lxc19950825 zishuilian zezhangh gzc-tracking nwpu-hjs luunguyen97 ajinkyapuar lengyue310 zuzi2015 yangzhe596

siamtrackers's Issues

数据集迁移的问题

请问如何实现迁移到自己的数据集上呢？

SiamRPN++多卡训练问题，

我在训练时，发现单卡可以正常训练，两张卡时就报错了，请问是跟哪些变量有关啊？

报错如下，求问如何解决：

[2021-05-30 22:39:23,961-rk0-my_train_LT.py#293] init done
fatal: Not a git repository (or any parent up to mount point /media/hdc/data4)
Stopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set).
fatal: Not a git repository (or any parent up to mount point /media/hdc/data4)
Stopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set).
[2021-05-30 22:39:23,992-rk0-my_train_LT.py#308] Version Information:
commit :
log :

[2021-05-30 22:39:23,994-rk0-my_train_LT.py#309] config
{
"META_ARC": "siamrpn_r50_l234_dwxcorr_lt",
"CUDA": true,
"TRAIN": {
"THR_HIGH": 0.6,
"THR_LOW": 0.3,
"NEG_NUM": 16,
"POS_NUM": 16,
"TOTAL_NUM": 64,
"EXEMPLAR_SIZE": 127,
"SEARCH_SIZE": 255,
"BASE_SIZE": 8,
"OUTPUT_SIZE": 25,
"RESUME": "",
"LOG_DIR": "./models/siamrpn_lt/logs",
"SNAPSHOT_DIR": "./models/siamrpn_lt/snapshot",
"EPOCH": 20,
"START_EPOCH": 0,
"BATCH_SIZE": 8,
"NUM_WORKERS": 1,
"MOMENTUM": 0.9,
"WEIGHT_DECAY": 0.0001,
"CLS_WEIGHT": 1.0,
"LOC_WEIGHT": 1.2,
"MASK_WEIGHT": 1,
"PRINT_FREQ": 20,
"LOG_GRADS": false,
"GRAD_CLIP": 10.0,
"BASE_LR": 0.005,
"LR": {
"TYPE": "log",
"KWARGS": {
"start_lr": 0.005,
"end_lr": 0.0005
}
},
"LR_WARMUP": {
"WARMUP": true,
"TYPE": "step",
"EPOCH": 5,
"KWARGS": {
"start_lr": 0.001,
"end_lr": 0.005,
"step": 1
}
}
},
"DATASET": {
"TEMPLATE": {
"SHIFT": 4,
"SCALE": 0.05,
"BLUR": 0.0,
"FLIP": 0.0,
"COLOR": 1.0
},
"SEARCH": {
"SHIFT": 64,
"SCALE": 0.18,
"BLUR": 0.2,
"FLIP": 0.0,
"COLOR": 1.0
},
"NEG": 0.2,
"GRAY": 0.0,
"NAMES": [
"GOT"
],
"VID": {
"ROOT": "data/crop511",
"ANNO": "data/crop511/train/train.json",
"FRAME_RANGE": 100,
"NUM_USE": 100000
},
"GOT": {
"ROOT": "./data/crop511",
"ANNO": "./data/crop511/train/train.json",
"FRAME_RANGE": 100,
"NUM_USE": 64000
},
"YOUTUBEBB": {
"ROOT": "data/yt_bb/crop511",
"ANNO": "data/yt_bb/train.json",
"FRAME_RANGE": 3,
"NUM_USE": -1
},
"COCO": {
"ROOT": "data/coco/crop511",
"ANNO": "data/coco/train2017.json",
"FRAME_RANGE": 1,
"NUM_USE": -1
},
"DET": {
"ROOT": "data/det/crop511",
"ANNO": "data/det/train.json",
"FRAME_RANGE": 1,
"NUM_USE": -1
},
"VIDEOS_PER_EPOCH": 64000
},
"BACKBONE": {
"TYPE": "resnet50",
"KWARGS": {
"used_layers": [
2,
3,
4
]
},
"PRETRAINED": "",
"TRAIN_LAYERS": [
"layer2",
"layer3",
"layer4"
],
"LAYERS_LR": 0.1,
"TRAIN_EPOCH": 10
},
"ADJUST": {
"ADJUST": true,
"KWARGS": {
"in_channels": [
512,
1024,
2048
],
"out_channels": [
128,
256,
512
]
},
"TYPE": "AdjustAllLayer"
},
"RPN": {
"TYPE": "MultiRPN",
"KWARGS": {
"anchor_num": 5,
"in_channels": [
128,
256,
512
],
"weighted": true
}
},
"MASK": {
"MASK": false,
"TYPE": "MaskCorr",
"KWARGS": {}
},
"REFINE": {
"REFINE": false,
"TYPE": "Refine"
},
"ANCHOR": {
"STRIDE": 8,
"RATIOS": [
0.33,
0.5,
1,
2,
3
],
"SCALES": [
8
],
"ANCHOR_NUM": 5
},
"TRACK": {
"TYPE": "SiamRPNLTTracker",
"PENALTY_K": 0.05,
"WINDOW_INFLUENCE": 0.28,
"LR": 0.22,
"EXEMPLAR_SIZE": 127,
"INSTANCE_SIZE": 255,
"BASE_SIZE": 8,
"CONTEXT_AMOUNT": 0.5,
"LOST_INSTANCE_SIZE": 831,
"CONFIDENCE_LOW": 0.8,
"CONFIDENCE_HIGH": 0.998,
"MASK_THERSHOLD": 0.3,
"MASK_OUTPUT_SIZE": 127
}
}
[2021-05-30 22:39:27,745-rk0-my_train_LT.py# 75] build train dataset
[2021-05-30 22:39:27,747-rk0-dataset.py# 38] loading GOT
[2021-05-30 22:39:27,759-rk0-dataset.py# 63] GOT loaded
[2021-05-30 22:39:27,783-rk0-dataset.py# 92] GOT start-index 0 select [64000/4] path_format {}.{}.{}.bmp
[2021-05-30 22:39:27,832-rk0-dataset.py#202] shuffle done!
[2021-05-30 22:39:27,833-rk0-dataset.py#203] dataset length 1280000
[2021-05-30 22:39:27,841-rk0-my_train_LT.py# 78] build dataset done
/home/hdc/anaconda3/envs/SiamTrackers/lib/python3.7/site-packages/torch/optim/lr_scheduler.py:122: UserWarning: Detected call of lr_scheduler.step() before optimizer.step(). In PyTorch 1.1.0 and later, you should call them in the opposite order: optimizer.step() before lr_scheduler.step(). Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
"https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning)
[2021-05-30 22:39:27,844-rk0-my_train_LT.py#347] (WarmUPScheduler) lr spaces:
[0.001 0.00137973 0.00190365 0.00262653 0.0036239 0.005
0.00424171 0.00359843 0.0030527 0.00258974 0.00219699 0.0018638
0.00158114 0.00134135 0.00113792 0.00096535 0.00081895 0.00069475
0.00058938 0.0005 ]
[2021-05-30 22:39:27,852-rk0-my_train_LT.py#348] model prepare done
/home/hdc/anaconda3/envs/SiamTrackers/lib/python3.7/site-packages/torch/nn/parallel/_functions.py:61: UserWarning: Was asked to gather along dimension 0, but all input tensors were scalars; will instead unsqueeze and return a vector.
warnings.warn('Was asked to gather along dimension 0, but all '
[2021-05-30 22:39:34,181-rk0-my_train_LT.py#282] Epoch: [1][20/8000] lr: 0.001000
batch_time: 0.161238 (0.315044) data_time: 0.000092 (0.011209)
total_loss: 0.860676 (1.279064) cls_loss: 0.482578 (0.566196)
loc_loss: 0.315082 (0.594057)
[2021-05-30 22:39:34,182-rk0-log_helper.py#111] Progress:20/160000,[0%], Speed:0.315 s/iter,Epoch-period 42:0 (M:S),ETA 0:14:00(D:H:M)

[2021-05-30 22:39:37,413-rk0-my_train_LT.py#282] Epoch: [1][40/8000] lr: 0.001000
batch_time: 0.162611 (0.237624) data_time: 0.000102 (0.005661)
total_loss: 1.051070 (1.156314) cls_loss: 0.447658 (0.500955)
loc_loss: 0.502843 (0.546132)
[2021-05-30 22:39:37,413-rk0-log_helper.py#111] Progress:40/160000,[0%], Speed:0.238 s/iter,Epoch-period 31:40 (M:S),ETA 0:10:33(D:H:M)

Traceback (most recent call last):
File "/media/hdc/data4/wxl/SiamTrackers-master/7-SiamRPNpp/SiamRPNpp-DW/bin/my_train_LT.py", line 357, in
main()
File "/media/hdc/data4/wxl/SiamTrackers-master/7-SiamRPNpp/SiamRPNpp-DW/bin/my_train_LT.py", line 351, in main
train(train_loader, dist_model, optimizer, lr_scheduler, tb_writer)
File "/media/hdc/data4/wxl/SiamTrackers-master/7-SiamRPNpp/SiamRPNpp-DW/bin/my_train_LT.py", line 237, in train
outputs = model(data)
File "/home/hdc/anaconda3/envs/SiamTrackers/lib/python3.7/site-packages/torch/nn/modules/module.py", line 532, in call
result = self.forward(*input, **kwargs)
File "/home/hdc/anaconda3/envs/SiamTrackers/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 152, in forward
outputs = self.parallel_apply(replicas, inputs, kwargs)
File "/home/hdc/anaconda3/envs/SiamTrackers/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 162, in parallel_apply
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "/home/hdc/anaconda3/envs/SiamTrackers/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 85, in parallel_apply
output.reraise()
File "/home/hdc/anaconda3/envs/SiamTrackers/lib/python3.7/site-packages/torch/_utils.py", line 394, in reraise
raise self.exc_type(msg)
RuntimeError: Caught RuntimeError in replica 1 on device 1.
Original Traceback (most recent call last):
File "/home/hdc/anaconda3/envs/SiamTrackers/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 60, in _worker
output = module(*input, **kwargs)
File "/home/hdc/anaconda3/envs/SiamTrackers/lib/python3.7/site-packages/torch/nn/modules/module.py", line 532, in call
result = self.forward(*input, **kwargs)
File "/media/hdc/data4/wxl/SiamTrackers-master/7-SiamRPNpp/SiamRPNpp-DW/siamrpnpp/models/model_builder.py", line 112, in forward
cls_loss = select_cross_entropy_loss(cls, label_cls)
File "/media/hdc/data4/wxl/SiamTrackers-master/7-SiamRPNpp/SiamRPNpp-DW/siamrpnpp/models/loss.py", line 25, in select_cross_entropy_loss
loss_pos = get_cls_loss(pred, label, pos)
File "/media/hdc/data4/wxl/SiamTrackers-master/7-SiamRPNpp/SiamRPNpp-DW/siamrpnpp/models/loss.py", line 17, in get_cls_loss
return F.nll_loss(pred, label)
File "/home/hdc/anaconda3/envs/SiamTrackers/lib/python3.7/site-packages/torch/nn/functional.py", line 1838, in nll_loss
ret = torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
RuntimeError: invalid argument 2: non-empty vector or matrix expected at /pytorch/aten/src/THCUNN/generic/ClassNLLCriterion.cu:31

如何制作跟踪数据？

您好，感谢分享：）
想问一下，自己拍了自行车的几个小时的视频（假设用siamrpn++，只跟踪mobike类别），是不是先用labelimg之类的工具对该跟踪目标进行打标签，之后的步骤怎么处理呢？
多谢！

SiamFC运行my_test

出现ZeroDivisionError: division by zero，看了一下主要是在ious = np.nanmean(ious, axis=0)这句，并且查看了ious的值。

ious= [[nan nan nan ... array([0.02229282]) array([0.10334186])
array([0.13032249])]]
Traceback (most recent call last):
File "/home/ubuntu/code/SiamTrackers-master/2-SiamFC/SiamFC-GOT/bin/my_test.py", line 72, in
prec_score,succ_score,succ_rate=e.report([tracker.name])
File "/home/ubuntu/code/SiamTrackers-master/2-SiamFC/SiamFC-GOT/got10k/experiments/vot.py", line 417, in report
ious = np.nanmean(ious, axis=0)

vot评估画图问题

up主你好，pysot带的vot只能评测出eao的数据，不能画vot的评估图，对于vot评估图请问你有好的解决方法吗？

老哥稳的一皮！！

Many wrong annotated bbox in GOT10K dataset

Why there are too many wrong annotated bbox for GOT10K dataset? For example, GOT-10k_Train_009058 sequence.

siamFCpp got10k在训练之前需要先裁剪好吗？

师兄您好，在训练之前需要先裁剪好GOT10K数据集吗，如果直接用原始的数据集训练，是不是对cpu负担很大，导致最后GPU跑不起来

SiamFC-VID问题

您好，感谢您收集的代码，对我帮助很大。我运行了SiamFC-VID里面的代码，下面是一些问题，希望您能解答。

我从百度云盘上下载了您提供的siamfc_30.pth预训练模型，当我运行 my_test.py后，程序可以运行，但是和您README.md里面提供的accuracy和precision完全不同，性能非常差，只有0.1多。
当我运行可视化程序查看OTB100中每个视频的跟踪结果时，发现跟踪结果非常差，完全漂移了，并且bbox非常大。如下图所示：
我运行SiamFC-GOT时，效果挺好的，基本和您提供的README.md一样

Vrey good work!

Very good work!
how to add the wechat group?
Thank you!

关于数据预处理问题

https://github.com/HonglinChu/SiamTrackers/blob/master/7-SiamRPNpp/SiamRPNpp-DW/siamrpnpp/datasets/dataset.py
作者你好，这里的dataset文件似乎没有对输入的图片做从0-255到0-1的映射，按理说一般网络不应该会对输入的图像数据统一到0-1之间吗？

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Can you provide pretrained models for these trackers

I am unable to train these trackers due to hardware constraints. Can someone please provide pre-trained weights. I specifically need for SiamFC++.

DaSiamRPN测试效果问题

您好，我又发现一个问题。我用DaSiamRPN-GOT加载官方提供的SiamRPNBIG.model，测试OTB2015结果为：
prec_score:0.840 -succ_score:0.634 -succ_rate:0.824。用UpdateNet（选择的step=1）加载SiamRPNBIG.model测试OTB2015结果为：prec_score:0.853 -succ_score:0.641 -succ_rate:0.830。这两个结果不一样，而且低于SiamR-CNN论文中提供的DaSiamRPN评测结果（prec:0.878, succ:0.658）。请问您知道是怎么回事吗？在VOT2018上测试DaSiamRPN结果为acc: 0.586, eao:0.383这个结果还算正常。

transfer learning strategy

Hi.
Can you please share some transfer learning strategy to start with
without training from scratch?
thank you

在VOT2018是怎么复现到原文的？难道调不同阶段的学习率？？

关于UpdateNet训练连数据集问题

您好，我用您提供的程序在ubuntu16.04下面生成训练数据时出现MemoryError问题。当我按照网上的说明 cat /proc/sys/vm/overcommit_memory改为1时，又显示已杀死，没法生成训练数据。请问您是否遇到过同样的问题。或者您是否能够把训练数据分享一下，谢谢。

Dataloader加载数据太慢

感谢您的贡献！
我在使用过程中出现了一些问题。
我使用的是siamrpn，我在训练的时候出现了数据加载太慢的情况，我已经将batchsize改为1了，迟迟无法获得数据。

我在dataset下调用还是挺快的，train_dataset.getitem(1)，但是不知道为什么在Dataloader中无法输出数据。

你好，学长，微信群还能加入吗

SiamRPNpp训练过程中出现“已杀死”后训练结束的问题

您好，我在训练alexnet的SiamRPNpp时，加载模型和数据集正常，但训练两次都出现“已杀死”的打印信息后就结束了训练，一次到99%，一次到80%，请问是什么问题

关于TrackingNet数据集

您好，请问您这里的百度云网盘TrackingNet数据集和官方的TrackingNet数据集内容是一样的不

Baidu ISSUE

All the models are uploaded at the Baidu, Baidu is not accessible for us,

Can you upload the models and everything is necessary for running the codes on the Google Drive?

关于siamfcpp的训练速度

同学，你用siamfcpp官方代码训练过吗？我用一片V100在got10k上训练，速度感人，一个epoch要10个小时。你写的代码训练速度是怎样的？

关于DA

作者您好，我想问下DA是一种互相关操作吗？哪篇
论文中提出来的啊。

siamRPN 请问解压YTB&VID需要多大内存啊，我480g的硬盘不够正常吗？

有点意思

如题

ImportError: cannot import name 'region' from partially initialized module 'toolkit.utils' (most likely due to a circular import)

请问有人能帮忙解决一下这个问题吗

运行代码

请问是否有运行自己视频进行跟踪的代码，只有测试数据集的代码吗

SIAMFC算法浮现出现错误

attempted relative import with no known parent package

请问学长这个问题怎么解决啊
在siamfc程序里出现的

大佬，请问IOU<?合适呢

在生成训练样本时，请问大神，iou设置为小于多少合适呢

关于siamfc.training部分，缺少文件"meta_data.pkl"，

请问学长这个文件在哪里可以下载呢，或者应该如何生成呢，麻烦告知一二，谢谢了！！！

got10k测试结果无法在官网上评估

学长，我按照siamFCpp源码训练之后测试了一下，然后将测试得到的.zip文件放到got10官网上评测，却不出结果，格式完全跟他给的fc实例一样，这种情况你有了解，有什么解决办法吗？？

关于使用got10k工具评估VOT

作者您好，我想问下使用got10K工具评估VOT数据集会报错吗？
我是报了一个除零错，就是在对iou除去NaN数据后做平均的时候，请问这个您解决了吗？

关于siamfc

用alexnet训练后，在otb和vot2018上进行测试，然后改成resnet22训练，再在otb和vot2018上测试，得到的结果没有变，一个数字都没变，这是为什么。

UpdateNet训练效果问题。

您好，我又来问问题了，不好意思问题有点多。我按照您的README文件训练后发现越训练越差，不知道怎么回事。我在训练过程中，每个stage x-1学习率设置为lrs = np.array([[6,7],[7,8]])，每个stage x-2学习率设置为lrs = np.array([[8,9],[9,10]])。在进行下一阶段训练前都会加载上一阶段的最好模型生成新的训练数据，但是效果是越来越差，不知道怎么回事，感觉很迷惑。

updatenet在测试的时候遇到问题

ValueError: max() arg is an empty sequence
您好，我想问一下在测试的时候已经得到跟踪框的位置，但最后显示这个错误，没能得到eao

wechat QR code out of date

wechat QR code out of date，I want to join you !

GOT10k数据集中visible ratios的计算方式？

林林大佬您好，GOT10K数据集中提供了visible ratios，请教下您，这个visible ratios是怎么计算得到的？论文中只看到这句相关的The regions that are occluded or truncated by image boundary correspond to the invisible parts，麻烦您给指导下？不胜感激

数据集下载

学长，您好。readme里百度网盘的数据集，打不开，无法下载。可以重新分享下吗。UAV123 BaiduYun password: 2iq4

VOT2018 BaiduYun password: e5eh

十分感激，谢谢学长

学长，有没有训练好的SiameseFC模型呢

SiamFC++test问题，希望学长解答一下

Traceback (most recent call last):
File "./bin/my_test.py", line 66, in
tester.test()
File "/home/c506/lrh/SiamFC++/SiamFCpp-master/siamfcpp/engine/tester/tester_impl/vot.py", line 93, in test
self.run_tracker()
File "/home/c506/lrh/SiamFC++/SiamFCpp-master/siamfcpp/engine/tester/tester_impl/vot.py", line 121, in run_tracker
self.worker(keys, all_devs[0], result_queue, speed_queue)
File "/home/c506/lrh/SiamFC++/SiamFCpp-master/siamfcpp/engine/tester/tester_impl/vot.py", line 174, in worker
lost, speed = self.track_single_video(tracker, video, v_id=v_id)
File "/home/c506/lrh/SiamFC++/SiamFCpp-master/siamfcpp/engine/tester/tester_impl/vot.py", line 238, in track_single_video
package="vot_overlap").vot_overlap
File "/home/c506/anaconda3/envs/siamfc/lib/python3.6/importlib/init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 994, in _gcd_import
File "", line 971, in _find_and_load
File "", line 941, in _find_and_load_unlocked
File "", line 219, in _call_with_frames_removed
File "", line 994, in _gcd_import
File "", line 971, in _find_and_load
File "", line 955, in _find_and_load_unlocked
File "", line 665, in _load_unlocked
File "", line 678, in exec_module
File "", line 219, in _call_with_frames_removed
File "/home/c506/lrh/SiamFC++/SiamFCpp-master/siamfcpp/evaluation/vot_benchmark/pysot/utils/init.py", line 10, in
from . import region
ImportError: cannot import name 'region'
主要是不能加载SiamFC++/SiamFCpp-master/siamfcpp/evaluation/vot_benchmark/pysot/utils/init.py中的region模块
我用pycharm打开看了一下，好像是相对路径导入的问题，新手对这个问题不知道怎么解决，希望学长答复一下。谢谢

已经解决，谢谢大佬

关于参数调节

可以分享一下单目标跟踪里面关于参数调节的一些技巧吗

siamrpn 测试VOT2018 请问你解决了这个BUG了么

root_dir = os.path.abspath('/media/xiaofei/ECD67E80D67E4B3A/test_data/vot
2018') # VOT测试暂时遇到问题

关于youtubebb原始数据集下载链接

大佬您好，请问有没有Youtubebb原始数据集的百度云下载链接

SiamRPN++的复现结果

大佬您好，我看到你的rpn++复现的结果也不太好，您后面有没有尝试复现出原效果

GlobalTrack of AAAI-20

Thank you for sharing and i'd like to ask if 2020 AAAI's global track will be shared.
（GlobalTrack: A Simple and Strong Baseline for Long-Term Tracking）

SiamFC-GOT 训练出现

您好，我下载了部分GOT 数据，看能不能跑通代码，结果运行出来这样的结果，后面就结束了，没有报epoch loss 等，

请问这是哪里出现问题了，在代码里定位不到这一块

Windows下pycharm运行的，文件调用问题。

Traceback (most recent call last):
File "K:/SiamTrackers-master/2-SiamFC/SiamFC-GOT/bin/my_test.py", line 8, in
from got10k.experiments import *
File "K:\SiamTrackers-master\2-SiamFC\SiamFC-GOT\got10k\experiments\got10k.py", line 13, in
from ..datasets import GOT10k
ImportError: attempted relative import with no known parent package

我看前几天其实有人提问过这个问题，但是作者没有解答，我再提问一次。有人懂这个跨文件调用怎么出错了吗？应该1怎么改呀？

能否提供一个OTB的测试模型呢。

如何测试OTB该如何训练，您是否有OTB的测试模型。