Currently I work with a detection model. All COCO annotation files that I need does not contain "segmentation" field. Furthermore at the inference stage I generate a new COCO file with predictions. This new file needs to have all previous information about the dataset (images, categories) for the next stage of the pipeline. However I'd like to use tide to check the quality of my model by using evaluate_range with TIDE.BOX mode. To use TIDE in such conditions, some minor modifications of the dataset.py are needed. I believe that this feature may be interesting for the community and I'd like to share my code
Currently I work with a detection model. All COCO annotation files that I need does not contain "segmentation" field. Furthermore at the inference stage I generate a new COCO file with predictions. This new file needs to have all previous information about the dataset (images, categories) for the next stage of the pipeline. However I'd like to use tide to check the quality of my model by using evaluate_range with TIDE.BOX mode. To use TIDE in such conditions, some minor modifications of the dataset.py are needed. I believe that this feature may be interesting for the community and I'd like to share my code