sabarim / 3dc-seg Goto Github PK

where can i download WEIGHTS: "saved_models/csn/irCSN_152_ft_kinetics_from_ig65m_f126851907.pth"?

how can i change train epoch?

Can any friends tell me the problem with the title above, thank you again

How to understand your code:

flatten = lambda lst: [lst] if type(lst) is torch.Tensor else reduce(torch.add, [flatten(ele) for ele in lst])

x =   [[torch.tensor([5.0]), torch.tensor([6.0])], [torch.tensor([7.0]), torch.tensor([8.0])]]
flatten(x)

TypeError                                 Traceback (most recent call last)
<ipython-input-47-2a14fe8cc003> in <module>
----> 1 flatten(x)

<ipython-input-44-7c292cd8c3bd> in <lambda>(lst)
----> 1 flatten = lambda lst: [lst] if type(lst) is torch.Tensor else reduce(torch.add, [flatten(ele) for ele in lst])

<ipython-input-44-7c292cd8c3bd> in <listcomp>(.0)
----> 1 flatten = lambda lst: [lst] if type(lst) is torch.Tensor else reduce(torch.add, [flatten(ele) for ele in lst])

<ipython-input-44-7c292cd8c3bd> in <lambda>(lst)
----> 1 flatten = lambda lst: [lst] if type(lst) is torch.Tensor else reduce(torch.add, [flatten(ele) for ele in lst])

TypeError: add(): argument 'input' (position 1) must be Tensor, not list

In my opion, you should want to get x = [[torch.tensor([5.0]), torch.tensor([6.0])], [torch.tensor([7.0]), torch.tensor([8.0])]]-->[torch.tensor(12.0), torch.tensor(14.0)].

Or where am I wrong?

Thank you.

Hello, I want to train a model myself. I noticed that the final model was trained with datasets "COCO, YouTubeVOS, DAVIS'17", however I can only find the config with single dataset. Could you offer a config for training with parameter? And does the datasets need to do some preprocessing before train together?

Hello, I now have the FBMS results (.png) predicted by my network, can you tell me how to calculate Fmean? I cannot find or use the Ground-Truth. Thank you very much and look forward to your reply.

Hi, @sabarim

1. this paper is published at BMVC, rather than ECCV conference.

2. the indentation fashion of partition of codes is not a multiple of four, but some of the codes follow this way. Is there any difference between them?

Best regards

Hi, the file "saved_models/csn/irCSN_152_ft_kinetics_from_ig65m_f126851907.pth" is not provided, where can I download it? Thanks!

Is the output layer is softmax layer?

Hello, thanks your great work~
I trained the model and got the 10000.pth and the model_best_train.pth for example, when I tried to test I used command 'python main.py -c run_configs/bmvc_final.yaml --task infer --wts saved_models/model_best_train.pth', I changed the path in bmvc_final.yaml to my pth's path, but:
RuntimeError: Error(s) in loading state_dict for ResNet:
Missing key(s) in state_dict: "conv1.weight", "bn1.weight", "bn1.bias", "bn1.running_mean", "bn1.running_var", "layer1.0.conv1.weight", "layer1.0.bn1.weight", "layer1.0.bn1.bias", "layer1.0.bn1.running_mean", "layer1.0.bn1.running_var", "layer1.0.conv2.weight", "layer1.0.bn2.weight", "layer1.0.bn2.bias", "layer1.0.bn2.running_mean", "layer1.0.bn2.running_var", "layer1.0.conv3.weight", "layer1.0.bn3.weight", "layer1.0.bn3.bias", "layer1.0.bn3.running_mean", "layer1.0.bn3.running_var", "layer1.0.downsample.0.weight", "layer1.0.downsample.1.weight", "layer1.0.downsample.1.bias", "layer1.0.downsample.1.running_mean", "layer1.0.downsample.1.running_var", "layer1.1.conv1.weight", "layer1.1.bn1.weight", "layer1.1.bn1.bias", "layer1.1.bn1.running_mean", "layer1.1.bn1.running_var", "layer1.1.conv2.weight", "layer1.1.bn2.weight", "layer1.1.bn2.bias", "layer1.1.bn2.running_mean", "layer1.1.bn2.running_var", "layer1.1.conv3.weight", "layer1.1.bn3.weight", "layer1.1.bn3.bias", 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Unexpected key(s) in state_dict: "epoch", "model", "optimizer", "iter".

Could you tell me how to load the model correctly?
and how to generate the visualization results as a mask for each image when I test?
Thank you very much~

Hello, thank you for your code.

I want to ask how to do multi category training? It seems that this part is missing from the code (dataset, train, loss, val, infer...), and only single category training can be performed. As stated in issue #17 :

Dataset parameters 'num_classes' are missing in the config file.

Sorry to bother you.As shown in the topic.All my installation packages are strickly followed requires.txt.When I input "python main.py -c run_configs/bmvc_final.yaml --task infer --wts bmvc_final.pth" and I've got this problem.The full error message is shown below:

Microsoft Windows [版本 10.0.17763.1518]
(c) 2018 Microsoft Corporation。保留所有权利。

(3Denv) F:\pycharm projects2\3DC-Seg-master>python main.py -c run_configs/bmvc_final.yaml --task infer --wts bmvc_final.pth
Traceback (most recent call last):
File "main.py", line 15, in
from inference_handlers.infer_utils.util import get_inference_engine
File "F:\pycharm projects2\3DC-Seg-master\inference_handlers_init_.py", line 1, in
from .Engine import *
File "F:\pycharm projects2\3DC-Seg-master\inference_handlers\Engine.py", line 15, in
from util import color_map
File "F:\pycharm projects2\3DC-Seg-master\util.py", line 7, in
from utils.util import get_iou
File "F:\pycharm projects2\3DC-Seg-master\utils\util.py", line 9, in
from torch.distributed import all_reduce
ImportError: cannot import name 'all_reduce' from 'torch.distributed' (D:\anaconda3\envs\3Denv\lib\site-packages\torch\distributed_init_.py)

@sabarim
Looking forward to your answer,thank you!

Could you please specify the license of your code? Preferably MIT

Hi,

If in case, anyone of you are planning to perform just the inference without the target annotation on a video, then do visit the repository: https://github.com/pratikk-bulani/3DC-Seg-Inference

Thanks

I download davis 2017 dataset from the website https://davischallenge.org/davis2017/code.html , but in this code "2016/val.txt" is used. Where can I get this file? Thanks!

Hi, thanks for your code. I want to use the resnet50_csn_ir model and I wonder where I can download pretained model of it? Thank you very much!

Hi, in Datasets Required for Training, what is YouTubeVOS refered to? Video Object Segmentation or Video Instance Segmentation?