Comments (6)
Hi @XiaominLi1997
The config is here https://github.com/NVlabs/GroupViT/blob/main/configs/default.yml#L90
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I also want to know the evaluation part.
Does the cls part only include the ImageNet?
And the seg part includes Pascal VOC, Pascal Context and COCO?
Thank you very much.
config file:
evaluate:
eval_only: false
eval_freq: 1
task:
- cls
- seg
cls:
save_best: true
template: subset
seg:
save_best: true
cfg: segmentation/configs/base/datasets/pascal_voc12.py
template: simple
opts: []
from groupvit.
I also want to know the evaluation part.
Does the cls part only include the ImageNet?
And the seg part includes Pascal VOC, Pascal Context and COCO?
Thank you very much.
config file:
evaluate:
eval_only: false
eval_freq: 1
task:
- cls
- seg
cls:
save_best: true
template: subset
seg:
save_best: true
cfg: segmentation/configs/base/datasets/pascal_voc12.py
template: simple
opts: []
from groupvit.
Hi @XiaominLi1997 The config is here https://github.com/NVlabs/GroupViT/blob/main/configs/default.yml#L90
Thanks. And I have another question, in the reference phase, can GroupViT only group the objects appearring in the training samples? If GroupViT can group objects unseen in the training phase.
Thank you again for your patient reply.
from groupvit.
Hi @XiaominLi1997
Since the training samples are noisy, it may cover a wide range of concepts. Some of them may overlap with our evaluation dataset, e.g. Pascal VOC. But we didn't explicitly evaluate the out of distribution grouping since it's hard to exclude some objects from noisy training set.
from groupvit.
I also want to know the evaluation part. Does the cls part only include the ImageNet? And the seg part includes Pascal VOC, Pascal Context and COCO? Thank you very much.
config file: evaluate: eval_only: false eval_freq: 1 task: - cls - seg cls: save_best: true template: subset seg: save_best: true cfg: segmentation/configs/base/datasets/pascal_voc12.py template: simple opts: []
The cls
part is referring to the ImageNet zero-shot classification.
You may change the evaluation dataset following instructions here. By default, we are using Pascal VOC dataset.
from groupvit.
Related Issues (20)
- Inconsistent Results from the paper
- Parallel training hangs in reduce_tensor method HOT 1
- Learnable group tokens fine-tuning on out-of-domain datasets HOT 1
- Checkpoint for the model trained just with 1 grouping stage HOT 1
- Inquiry about the Grouping Blocks HOT 2
- error when use single node and multi gpu for training HOT 5
- background threshold issues HOT 1
- How fast can this model run?
- YFCC subset taking very long to process HOT 1
- Visualization of Concepts Learnt by Group Tokens
- output masks consistently showing the same structure HOT 5
- How to generate the mask in Figure 1 in Appendix?
- Questions about input pred label file HOT 3
- question about training setup [#GPUs].
- use gumbel softmax only for training
- How to generate image-text pairs when i want to use other datasets such as ADE20K or medical segmentation dataset? HOT 1
- Command 'apex' not found HOT 1
- AttributeError: module 'torch.nn' has no attribute 'backends'
- Open-vocabulary semantic segmentation HOT 1
- Are there any plans to retrain a version with larger data and parameter scale?
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