Q: How to align the category IDs and Image IDs?
A:
For mmdetection config, you can organize the config as follows:
```python
test/val = dict(
classes=('bicycle', 'car', 'motorbike', 'bus',
'bottle', 'chair', 'diningtable', 'tvmonitor'),
type='CocoDataset',
ann_file='/dataset/LIS/lis_coco_png_raw_dark_valonly_challenge_noanno.json',
img_prefix='/dataset/LIS/RAW_Dark/val_challenge/',
pipeline=test_pipeline
)
```
The `lis_coco_png_raw_dark_valonly_challenge_noanno.json` can be accessed via the following link:
[Google Drive Link](https://drive.google.com/file/d/1fpDjUX4-vXuFgJMsLSFLRnnsc_QfZhHC/view?usp=drive_link
)
In this way, the category IDs and Image IDs are aligned.
Q: How to obtain a .json file for submission?
For mmdetection, you can obtain the JSON file for submission using:
```bash
python ~/code/mmdetection/tools/test.py \
config.py \
checkpoint.pth \
--options "jsonfile_prefix=./test_results" \
--format-only
```
Q: How can I obtain a robust baseline model for low-light instance segmentation?
A: You can find one at https://github.com/Linwei-Chen/LIS