Comments (2)
You missed some parameters. See #21
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You missed some parameters. See #21
I also using flip-eval while evaluation. Did you notice the network changing sometime, these two parts below often exchange :
(1): GlobalBranch(
(fc): Sequential(
(0): Linear(in_features=960, out_features=1024, bias=True)
(1): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(2): ReLU(inplace)
(3): Dropout(p=0.5)
)
(avgpool): AdaptiveAvgPool2d(output_size=1)
(classifier): Linear(in_features=1024, out_features=333, bias=True)
)
and
(sum_conv): Sequential(
(0): Dropout2d(p=0.1)
(1): Conv2d(1024, 1024, kernel_size=(1, 1), stride=(1, 1))
)
(avgpool): AdaptiveAvgPool2d(output_size=1)
(classifiers): ModuleList(
(0): Linear(in_features=1024, out_features=333, bias=True)
(1): Linear(in_features=1024, out_features=333, bias=True)
)
)
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Related Issues (20)
- Tried to fix pretrained weights but performance still lower than reported HOT 2
- run single method of " baseline (XE) + O.F. " HOT 1
- A bug which sometimes causes failure to resume training HOT 2
- python eval_acc.py error HOT 2
- Is baseline(XE) training also using two-step transfer learning? HOT 1
- Niubility in train.py #line330 HOT 1
- CUDA out of memory HOT 1
- Anyone who can share the model files? I can't access GoogleDrive ,thx! HOT 1
- How did you visualize the attention map in two branches model? HOT 3
- about gpu.devices
- Hello, friend!I used a pre-deployment term -- Visualize - ranks. Why did the test report a failure of query_flip and Gallery_flip HOT 2
- Hello, friend, test whether the picture matches with other pictures, can you visualize it?What code is required? HOT 1
- Reproduce results are so bad although I have used all default parameter for all datasets.
- Reproduce results are so bad although I have used all default parameter for all datasets.
- Attention map visualization
- 参数问题和感谢 HOT 2
- Can we use torchreid framework to visualize the output images?
- the deployment problem of O.W, O.F HOT 5
- val_acc error HOT 1
- Train in windows
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