A General Toolbox for Identifying Object Detection Errors

An easy-to-use, general toolbox to compute and evaluate the effect of object detection and instance segmentation on overall performance. This is the code for our paper: TIDE: A General Toolbox for Identifying Object Detection Errors (ArXiv) [ECCV2020 Spotlight].

Check out our ECCV 2020 short video for an explanation of what TIDE can do:


TIDE is available as a python package for python 3.6+ as tidecv. To install, simply install it with pip:

pip3 install tidecv

The current version is v1.0.1 (changelog).


TIDE is meant as a drop-in replacement for the COCO Evaluation toolkit, and getting started is easy:

from tidecv import TIDE, datasets

tide = TIDE()
tide.evaluate(datasets.COCO(), datasets.COCOResult('path/to/your/results/file'), mode=TIDE.BOX) # Use TIDE.MASK for masks
tide.summarize()  # Summarize the results as tables in the console
tide.plot()       # Show a summary figure. Specify a folder and it'll output a png to that folder.

This prints evaluation summary tables to the console:

-- mask_rcnn_bbox --

bbox AP @ 50: 61.80

                         Main Errors
  Type      Cls      Loc     Both     Dupe      Bkg     Miss
   dAP     3.40     6.65     1.18     0.19     3.96     7.53

        Special Error
  Type   FalsePos   FalseNeg
   dAP      16.28      15.57

And a summary plot for your model’s errors:

A summary plot

Jupyter Notebook

Check out the example notebook for more details.


The currently supported datasets are COCO, LVIS, Pascal, and Cityscapes. More details and documentation on how to write your own database drivers coming soon!


If you use TIDE in your project, please cite

  author    = {Daniel Bolya and Sean Foley and James Hays and Judy Hoffman},
  title     = {TIDE: A General Toolbox for Identifying Object Detection Errors},
  booktitle = {ECCV},
  year      = {2020},


For questions about our paper or code, make an issue in this github or contact Daniel Bolya. Note that I may not respond to emails, so github issues are your best bet.