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CHANGELOG.md

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Version 0.17.0

  • New evaluation metrics;
  • New evaluation on test set;
  • New inference service with image upload;
  • Bug fixes;

Version 0.16.4

  • sahi version bump;
  • Bug fix with parameter grid on image callbacks and mod polymapper.

Version 0.16.3

  • Bug fixes on ModPolymapper training when some parts are frozen.

Version 0.16.2

  • Bug fix on ModPolyMapper when choosing not to evaluate while training.
  • Added the option of freezing some parts of ModPolyMapper.

Version 0.16.1

  • Dependencies fix.

Version 0.16.0

  • New Mod PolyMapper model;
  • Matching methods added;
  • Evaluation methods added;

Veresion 0.15.0

  • New Naive Mod PolyMapper model (Object Detection + PolygonRNN);
  • New Naive Mod Polymapper dataset;
  • New callback: Frame Field Only Crossfield Warmup Callback;
  • New inference processors for Object Detection and PolygonRNN;
  • Bug fix on object detection model;
  • Bug fix on bounding box mask building;
  • Bug fix on polygon iou with invalid geometries;
  • Minor code refactor;

Veresion 0.14.2

  • Bug fix on PolygonRNN polygon tokenizer.

Veresion 0.14.1

  • Bug fix on convert dataset;
  • Bug fix on PolygonRNNDataset;
  • Bug fix on PolygonRNNResultCallback when using gpu;
  • Bug fix on PolygonRNNPLModel;

Version 0.14.0

  • Vector IOU;
  • Polis metric added;
  • IoU added to PolygonRNN training loop;
  • Object detection visualization callback added;
  • PolygonRNN visualization callback added;
  • Bug fix on polygon building on build mask geometry handling;

Version 0.13.1

  • Bug fixes on SegLoss parameters;

Version 0.13.0

  • Dataset conversion added. It is possible to convert between some formats of dataset;
  • Tversky Loss and Focal Tversky Loss added;
  • LabelSmoothingLoss added;
  • MixUpAugmentationLoss added;
  • KnowledgeDistillationLoss added;
  • Mixup augmentation added to Frame Field Model;

Version 0.12.1

  • Bug fixes on mask building;
  • Bug fixes on detection model training.
  • New mode on build masks;

Version 0.12.0

  • Minor improvements on polygonization methods;
  • Inference server added;

Version 0.11.0

  • Gradient Centralization added;

Version 0.10.0

  • Object Detection added;
  • Instance Segmentation added;

Version 0.9.0

  • PolygonRNN model added;
  • Added the option of choosing the number of images on ImageCallback;
  • Added the option of adding created masks to existing csv;
  • Added the option of generating bounding boxes in create masks;
  • Added the option of converting csv dataset to coco dataset;

Version 0.8.2

  • Fixes on requirements;

Version 0.8.1

  • Minor improvements and bug fixes on polygon building inference;
  • Bug fixes on mask builder;
  • Performance improvement on mask builder using coco format;

Version 0.8.0

  • Added inference features;
  • Improved polygon inference;

Version 0.7.2

  • Changed the versions of pytorch and torchvision.

Version 0.7.1

  • Added MANIFEST.in to include missing yml on pypi packaging.

Version 0.7.0

  • Bug fix on loss sync;
  • Custom models from Frame Field implementation (to compare training results);
  • New HRNet-OCR-W48 backbone;
  • Fixed bugs on new versions of pytorch-lightning;
  • Build mask from COCO dataset format;

Version 0.6.0

  • Polygon inference
  • Unittests to Polygon inference;
  • Bug fixes warmup callback (invalid signature on method);
  • FrameFieldResultCallback renamed to FrameFieldOverlayedResultCallback;
  • New implementation of FrameFieldResultCallback;
  • Invalid mask handling (frame field training mask with only polygon mask and empty vertex and boundary masks);
  • Added multiple schedulers option;
  • Added IoU 10, 25, 50, 75 and 90;
  • Added GPU augmentation using kornia;

Version 0.5.1

  • Bug fixes when inputs are RGBA images;
  • Bug fixes on frame field model with models other than U-Net;
  • Bug fixes on FrameFieldResultCallback (all black image fixed).

Version 0.5.0

  • Added frame field training image visualization callback.

Version 0.4.1

Bug fixes on missing entrypoints and mask process execution.

Version 0.4

Polygoniztion by Frame Field Learning features

  • FrameField dataset
  • FrameField Learning
  • Polygonization

Version 0.3.2

Bug fixes on image callback when Pytorch Lightning DDP is used.

Version 0.3.1

Bug fixes when Pytorch Lightning DDP is used.

Version 0.3.0

  • Custom metric option in the model config;
  • pytorch_toolbelt added as required package. This enables usage of the models, losses and metrics in the training;
  • Added the option of setting a limit of rows to be read in the csv dataset;
  • Added the option of setting a root_dir to the dataset. This root_dir will be concatenated to the entry in the csv dataset before loading the image;
  • Bug fixes on image_callback;

Version 0.2.1

Fixes relative path bug on dataset

Version 0.2.0

New custom callbacks:

  • ImageSegmentationResultCallback: Callback that logs the results of the training on TensorBoard and on saved files; and
  • WarmupCallback: Applies freeze weight on encoder during callback epochs and then unfreezes the weights after the warmup epochs.

Metrics added to Segmentation Model:

  • Accuracy;
  • Precision;
  • Recall; and
  • Jaccard Index (IoU).

Version 0.1.4

First version of metrics added.

Bug fixes on dataset reading with prefix path.

Version 0.1.3

Bug fix on entry points and --config-dir syntax.

Version 0.1.2

Bug fix on Python's version.

Minor bug fix

Bug fix.

First Release

Framework based on Pytorch, Pytorch Lightning, segmentation_models.pytorch and hydra to train semantic segmentation models using yaml config files.