Comments (4)
Thanks a lot for your enquiry. train_single.py
is to train the segmentation branch. During the joint training stage, you could load the trained weights of segmentation branch (pretrained on segmentation maps) and the classification branch (pretrained on image-level maps) separately, then conducting the joint training (finetuning).
from jcs.
Thank you for your response. I need assistance with two issues:
- How can I train a classification branch using techniques like image mixing and pixel-level supervision for activation mapping, as mentioned in the paper?
- Is the code for this specific part, especially for training a classification branch on a custom dataset, available in this GitHub repository?
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We have no plans to release the entire code of training the classification branch currently.
However, you can reimplement the training process as all details (process, hyper-params) have been explained clearly in our paper.
Thank you for your understanding.
from jcs.
Thanks for your clarification. I appreciate your great work. Have a nice day!
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Related Issues (9)
- Training process HOT 5
- How can I train the "Joint model of segmentation (cls + seg)" HOT 5
- Why do you perform both AM and Segmentation? HOT 1
- Where is 'dcm_png' folder in COVID-CS?? HOT 3
- How can i use the stage 1 feature in the code? thanks. HOT 3
- .
- 个人数据集训练的模型如何在该实验中进行测试分割? HOT 7
- Implementation detail of "Feature combination" module HOT 1
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