Comments (2)
frabob2017
commented on July 1, 2024
1
I run DETR and compare YOLO to see how long it takes to train around 240 512*512 images. I found DETR training time for each epoch will almost double compared with YOLO. Is it expected?
Hope DETR team can be as supportive as YOLOv8 team. with this, I believe that more people will try DETR. I am also wondering there is no version update for DETR compared with frequent version update of YOLO.
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YejinHwang909
commented on July 1, 2024
me too!🥲
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Related Issues (20)
- using vit as image backbone HOT 1
- Keyerror: image_id (training detr on custom dataset
- How to train with a custom dataset on mac m2?
- continuously growing memory
- Question about object queries. HOT 4
- I want to train the DETR model on a CPU. How can I make it possible on a small computer, 8gb RAM HOT 3
- Why positional encoding is added to different role in encoder and decoder. HOT 1
- 🐛 Bug: Architecture diagram in README.md renders incorrectly when using dark mode
- continue training with chekckpoint
- How to finetune DETR for semantic segmentation task?
- I do not understand what the mask meaning in "samlpes"
- Process finished with exit code 137 (interrupted by signal 9: SIGKILL)Please read & provide the following
- Very low performance for segmentation task.
- box_cxcywh_to_xyxy
- ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: -9) local_rank: 6 (pid: 257736) of binary: /home/public/anaconda3/envs/DL/bin/python
- Average Precision of each class for best epoch and then it's mean HOT 1
- the mAP is chage
- I think there are some errors in the posted code HOT 6
- Queries for images with low number of objects HOT 2
- RuntimeError: Error(s) in loading state_dict for DETRsegm: HOT 2
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