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How to train your own dataset #140
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I also want to train my own dataset, but it seems the situation is not very promising.If you find a solution, please share it. Thank you very much. |
Hi, there are roughly two steps:
you can refer to the code for coco or other datasets used in our training. |
"Okay, thank you very much for your patient explanation. I'll give it a try now." |
"I have another question. How can I construct JSON files like those in the image based on my annotated dataset?"
|
To construct JSON file please ask GPT4. Hhh |
@MaureenZOU @jwyang after running training command i am getting this error File "/home/hp-atc/labellerr/Segment-Everything-Everywhere-All-At-Once/modeling/interface/prototype/attention_data_struct_seemv1.py", line 290, in update_spatial_results although i am getting this key in log file when i print the result keys- 2024-10-13 15:29:34,730 - INFO - Input results keys: dict_keys(['aux_outputs', 'pred_logits', 'pred_masks', 'pred_gmasks', 'pred_smasks', 'pred_captions', 'pred_gtexts', 'pred_stexts', 'pred_smaskembs', 'pred_pspatials', 'pred_nspatials']) Input results keys: dict_keys(['prev_mask']) 2024-10-13 15:29:34,732 - INFO - Input results keys: dict_keys(['prev_mask']) i log this key one time it logs 4 times |
Hello, I currently have my own dataset labeled with labelme, which has been converted to Coco format. The list is as follows:
${DATASET_ROOT} # 数据集根目录,例如:/home/username/data/NWPU
├── annotations
│ ├── train.json
│ ├── val.json
│ └── test.json
└── images
├── train
├── val
└── test
Excuse me, can this be trained directly?
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