We now have over 15 models covering more than 10 tasks in the zoo. Although most of the models are converted to ONNX straightly from its original format, such conversion may potentially lead to drop of accuracy, especially for FP16 and Int8-quantized models. To show the actual accuracy for our users, we now already have some evaluation scripts with the following conditions met in https://github.com/opencv/opencv_zoo/tree/master/tools/eval:

1. Reproduce the claimed accuracy with the converted FP32 ONNX model using OpenCV DNN as inference framework. The claimed accuracy is either from the source repository or paper on the same dataset, which needs to be specified in the first comment of the pull request.
2. Once it is reproduced, apply the same evaluation script on FP16 and Int8-quantized models.

Take a look at the task list below for current status. Feel free to leave a comment for application or discussion before you start to contribute.