Comments (10)
Thank you. I have run through the code. I hope it can be helpful to the follow-up work, and I look forward to your excellent work in the future.
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"Wider-Attribute dataset your not doing Detection + attribute classification but only attribute classification because the crop of the person is done offline . right ??"
yes
This is a common fashion in multi-label benchmark.
from csra.
Hi,
Thanks for reading.
We provide validation code of various pretrained models on VOC and COCO, which could print out the mAP of each model (in ''val.py''). Do you mean ''prediction'' by saying that the pretrained models could output a label set of each test image? Say,
image1: dog, person, cat.
image2: person, bicycle.
If it was that case, you could use 0.5 as threshold to discriminate the positive and negative labels by (see line 45 in val.py):
result = nn.Sigmoid()(logit)
result[result >= 0.5] = 1
result[result < 0.5] = 0
Best,
Ke Zhu
from csra.
Thank you for your reply。
By the way, it is estimated when the code of Vit and the code trained in the wide attribute dataset will be released, because my work is similar to that of the wide attribute dataset。
Thank you!
from csra.
@2717117077
Hi, actually I am a little busy these days.
Hopefully we are about to release them in the middle or late of September.
from csra.
Thank you and hope to see your excellent work as soon as possible!
from csra.
Hi,
code concerned with wider attribute has been released @2717117077
and the prediction model demo has also been added @sure7018
Best
from csra.
@Kevinz-code thanks for sharing the code base one query is for the WIDER attribute dataset will the output be person and its attributes or only person ??
from csra.
Hi, @abhigoku10
For Wider-Attribute dataset, every input image to the network is a person cropped from the original dataset. So the output will be the attributes (14 categories of attributes) of the certain person.
Best,
from csra.
@Kevinz-code thanks for the response so just to clarify for Wider-Attribute dataset your not doing Detection + attribute classification but only attribute classification because the crop of the person is done offline . right ?? because you mentioned in the readme
utils/demo_images/000001.jpg prediction: dog,person,
utils/demo_images/000004.jpg prediction: car,
utils/demo_images/000002.jpg prediction: train,
...
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Related Issues (20)
- Is the code consistent with the description in the paper? HOT 4
- MobileNet; input size HOT 2
- Transformer on WiderAttribute predicition HOT 1
- Is 'normalized' classifier necessary? HOT 3
- some questions about val.py HOT 1
- The problems of val.py? HOT 1
- Partial-label HOT 1
- About the pretrained vit. HOT 2
- Question about Attention Image or Heatmap Generation HOT 1
- Specific improvements to vit HOT 3
- Some problems about vision transformer HOT 1
- Details about baseline resnet-101 in paper HOT 1
- Load Model İssue? HOT 1
- Cross Validation HOT 2
- MobileNet implementation of CSRA HOT 4
- About wider_attribute is Cropping individual person attributes ?
- How to use VIT-224 pretrain weight with 448 input size
- Use CSRA module in the ResNet50 model
- visualize function
- Global feature vector
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