yu-wu / one-example-person-reid Goto Github PK

Hello author, how do you get 'market1501_init_-1.0.pickle','duke_init_-1.0.pickle' in file examples? Plase help me! Please! Thank you very much!

Hello,When i train the model ,i will always get this problem?Is anyone have solved it？

Traceback (most recent call last):
File "run.py", line 123, in
main(parser.parse_args())
File "run.py", line 87, in main
eug.train(new_train_data, unselected_data, step, loss=args.loss, epochs=args.epochs, step_size=args.step_size, init_lr=0.1) if step != resume_step else eug.resume(ckpt_file, step)
File "/home/xutian/One-Example-Person-ReID-master/reid/eug.py", line 92, in train
return self.softmax_train(train_data, unselected_data, step, epochs, step_size, init_lr, dropout, loss)
File "/home/xutian/One-Example-Person-ReID-master/reid/eug.py", line 135, in softmax_train
u_dataloader = self.get_dataloader(unselected_data, training=True, is_ulabeled=True)
File "/home/xutian/One-Example-Person-ReID-master/reid/eug.py", line 82, in get_dataloader
shuffle=training, pin_memory=True, drop_last=training)
File "/home/xutian/tools/anaconda3/envs/freedom/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 802, in init
sampler = RandomSampler(dataset)
File "/home/xutian/tools/anaconda3/envs/freedom/lib/python3.6/site-packages/torch/utils/data/sampler.py", line 64, in init
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integeral value, but got num_samples=0

for example：
dataset market1501：the fixed_layer = False
dataset MARS: the fixed_layer = True

Hello, thank you for sharing, but I run the error after following the readme file.
NotADirectoryError: [Errno 20] Not a directory: '/home/Ensoleille/One-Example-Person-ReID-master/data/market1501/train/0002_c1s1_000451_03.jpg'.I hope you can tell me how to reproduce smoothly.

Hi, Thanks for your awesome work. I read the paper and found baseline in market1501 is rank1=26.0, mAP=9.0. In my opinion, this is trained using 751 images with 751 ids. But I just try, and I cannot get the baseline result. My rank1=8.6, mAP=3.0. I want to know how to reproduce the baseline result using this code.

Hi,I want to replace the resnet50 with other networks,but every time I switch to the source code for another network, the program runs up a lot of memory after it shows" create dataloader for Training with batch_size 16", and then the code stops running with showing nothing.I don't know why and what should I do if I want to change the network?

Sorry for disturbing you. When I read the code about the Exclusive Loss, I found that Exclusive Loss in the “forward“ function uses targets labels. However, in the paper, the Exclusive Loss doesn't need labels to training.

Thanks for your many great works!
I have a question about how to get the static strategy work,such as the DGM+IDE ,which rank-1=36.8 and map=16.9 ?
Many thanks for you !

Thank you for your great work!But i found the exloss cannot converge when training, the optimizer is adam, lr=3e-4

Hi, I am trying your code on the duke dataset but I am getting the following error.

/usr/local/lib/python3.6/dist-packages/sklearn/externals/joblib/externals/cloudpickle/cloudpickle.py:47: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
  import imp
Files already downloaded and verified
Duke dataset loaded
  subset   | # ids | # tracklets
  ---------------------------
  train    |   702 |    16522
  query    |   702 |     2228
  gallery  |  1110 |    17661
  labeled    | N/A |      702
  unlabeled  | N/A |    15820

Create new one-shot split and save it to ./examples/duke_init_-1.pickle
Runing: EF=10%, step 0:	 Nums_to_be_select 1582 	 Ritio 	 Logs-dir 0.1
create dataloader for Training with batch_size 16
create dataloader for Training with batch_size 16
Traceback (most recent call last):
  File "run.py", line 124, in <module>
    main(parser.parse_args())
  File "run.py", line 88, in main
    eug.train(new_train_data, unselected_data, step, loss=args.loss, epochs=args.epochs, step_size=args.step_size, init_lr=0.1) if step != resume_step else eug.resume(ckpt_file, step)
  File "/home/zamra/PYreps/Person_ReId/One-Example-Person-ReID/my_reid/eug.py", line 92, in train
    return self.softmax_train(train_data, unselected_data, step, epochs, step_size, init_lr, dropout, loss)
  File "/home/zamra/PYreps/Person_ReId/One-Example-Person-ReID/my_reid/eug.py", line 142, in softmax_train
    trainer.train(epoch, s_dataloader, u_dataloader, optimizer, use_unselcted_data, print_freq=len(s_dataloader)//2)
  File "/home/zamra/PYreps/Person_ReId/One-Example-Person-ReID/my_reid/trainers.py", line 67, in train
    u_loss, u_prec1 = self._forward(u_inputs, u_targets, 'u')
  File "/home/zamra/PYreps/Person_ReId/One-Example-Person-ReID/my_reid/trainers.py", line 114, in _forward
    u_loss, outputs = self.u_criterion(u_feats, targets)
  File "/home/zamra/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/zamra/PYreps/Person_ReId/One-Example-Person-ReID/my_reid/exclusive_loss.py", line 36, in forward
    outputs = Exclusive(self.V)(inputs, targets) * self.t
  File "/home/zamra/PYreps/Person_ReId/One-Example-Person-ReID/my_reid/exclusive_loss.py", line 15, in forward
    outputs = inputs.mm(self.V.t())
RuntimeError: size mismatch, m1: [16 x 2048], m2: [1024 x 15820] at /pytorch/aten/src/THC/generic/THCTensorMathBlas.cu:266

I'm sorry to bother you.I have run your code several times, mAP only reaches 8%, and top-1 only reaches 20% at most. Otherwise,the results are different when each time I run the code. How can I achieve the effect in your paper and keep the results at the same?

Hellow!For video datasets, such as Mars, I would like to ask whether a tracklet is similar to a single frame image,? And whether all the frames in a tracklet are input into the network at the same time?

Hello author, I am recreating your paper. I want to ask how to use the Pycharm editor to run the run.sh file. I am a beginner. I want to adjust the parameters in the code because my GPU memory is not enough. What can I do? Thank you very much.