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v1.6.5

v1.6.4

  • fix windows mask api.
  • numpy>=2 support for py39+
  • update CI\CD for build macos & windows whl

v1.6.1 - v1.6.3

v1.6.0

  • Rework mask_api with pybind11 C++ .
  • Rework RLE support.
  • Create test files for all components.
  • The math_matches function has been reworked, with an emphasis on using C++ code.
  • Added more documentation of functions. Optimized existing ones.
  • Added rleToBoundary func with 2 backend ["mask_api", "opencv"]
  • IoU type boundary support (further testing is needed)
  • Create async rle and boundary comput discussion

v1.5.7

  • Compare COCOEval bug fix.

v1.5.6

  • Replace CED MSE curve with MAE (px) curve
  • Add CED examples
  • Display IoU and MAE for keypoints
  • Reworked eval._prepare to clear up the return flow
  • Reworked the C++ part of COCOevalEvaluateImages and COCOevalAccumulate
    • Add new COCOevalEvaluateAccumulate to combine these two calls. You can use old style separate_eval==True (default=False)
    • COCOevalAccumulate & COCOevalEvaluateAccumulate -> COCOeval_faster.eval is now correctly created as numpy arrays.
  • Append LVIS dataset support lvis_style=True in COCOeval_faster
cocoEval = COCOeval_faster(cocoGt, cocoDt, iouType, lvis_style=True, print_function=print)
cocoEval.params.maxDets = [300]

v1.5.5

  • Add CED MSE curve
  • Review tests
  • Review COCOeval_faster.math_matches function and COCOeval_faster.compute_mIoU function

v1.5.3 - v1.5.4

  • Worked out the ability to work with skeletons and various key points
  • eval.state_as_dict Now works for key points

v1.5.2

  • Change comparison to colab_example
  • append utils with opencv conver_mask_to_poly (extra)
  • append drop_cocodt_by_score for extra eval

v1.5.1

  • breaking change | new static function COCO.load_json
  • new curve f1_confidence with cur.plot_f1_confidence()
  • breaking change | replace display_matrix arg in_percent to normalize
  • breaking change | rework draw functions

v1.4.2

  • append Auto-formatters
  • append py36 support
  • append pandas to requirements for plotly[express]
  • update mask api with pycootools

v1.4.1

  • append Plotly fig return
  • append preview GT only func. Without eval.
cocoGt = COCO(...)
preview = PreviewResults(cocoGt, iouType='segm')
preview.display_tp_fp_fn(data_folder=..., image_ids=..., display_gt=True)

v1.4.0

  • fix issue #12
  • Updated pre-rec calculation method
  • Updated required libraries
  • Moved all matplotlib dependencies to plotly
  • Append new examples & mmeval test file

v1.3.3

v1.3.2

  • rework math_matches function. moved to faster_eval_api
  • Moved calculations from python to c++
  • Separated extra classes
  • Added new sample data
  • append mIoU based on TP pred.
  • append mAUC based on Coco pre/rec.

v1.3.1

v1.3.0

  • remove pycocotools dependencies
  • clean c/c++ code

v1.2.3

  • Implemented of mean IoU for TP
  • set FP-red FN-blue

v1.2.2

  • Removed own implementation of pre-rec
  • Switched to the implementation of pre-rec calculation from COCO eval
  • Lost backward compatibility
  • Implemented output fp/fn/tp + gt to pictures

v1.2.1

  • bug fix with pre-rec curve
  • rework error calc (tp/fp/fn)
  • change image plot to plotly
  • append docker auto builder
  • append native iou calc (slow but accurate)
  • rework auc calc with link

v1.1.3-v1.1.4

  • rebuild plotly backend
  • Segm bug-fix

v1.1.2

  • Append fp fn error analysis via curves
  • Append confusion matrix
  • Append plotly backend support for ROC / AUC

v1.1.1

  • Redesigned curves
  • Reworked data preload
  • Append csrc to setup
  • Build sdist Package

v1.1.0

  • Wrap c++ code
  • Get it to compile
  • Add COCOEval class wraper
  • Remove detectron2 dependencies
  • Remove torch dependencies
  • Append unittest
  • Append ROC / AUC curves
  • Check if it works on windows