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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog.

0.11.0

The following PRs have been merged since the last version.

ai-fast-track

fstroth

potipot

FraPochetti

jaeeolma

bogdan-evtushenko

drscotthawley

lgvaz

nicjac

Thank you to all contributers: @ai-fast-track, @fstroth, @potipot, @FraPochetti, @jaeeolma, @bogdan-evtushenko, @drscotthawley, @lgvaz, @nicjac

Unreleased - 0.10.0a1

Main dependencies updated

  • torch 1.9.0
  • tochvision 0.10
  • mmdet 2.16.0
  • mmcv 1.3.14
  • fastai 2.5.2
  • pytorch-lightning 1.4.8

Unreleased - 0.9.0a1

Added

  • Low level parsing workflow with RecordCollection
  • Semantic segmentation support with fastai

Changed

  • Breaking: Refactored mask components workflow
  • Breaking: Due to the new mask components refactor, autofix doesn't work for mask components anymore.

[0.8.1]

Added

  • end2end_detect(): Run Object Detection inference (only bboxes) on a single image, and return predicted boxes corresponding to original image size -Breaking: BaseLabelsRecordComponent as_dict() now returns both labels and labels_ids. labels are now strings instead of integers.

Changed

  • Breaking: On tfms.A.aug_tfms parameter size and presize changed from order (height, width) to (width, height)
  • Added RecordCollection
  • Breaking: Changed how the resnet (not-fpn) backbone cut is done for torchvision models. Previous resnet torchvision trained models will have trouble loading weights.

[0.8.0]

Supports pytorch 1.8

Added

  • iou_thresholds parameter to COCOMetric
  • SimpleConfusionMatrix Metric
  • Negative samples support for mmdetection object detection models

Changed

  • Breaking: Albumentations aug_tfms defaults.
    • rotate_limit changed from 45 to 15
    • rgb_shift_limit changed from 20 to 10
    • VOC parser uses image sizes from annotation file instead of image
    • bumps fastai to latest version (<2.4)

[0.7.0]

BREAKING: API Refactor

Added

  • Metrics for mmdetection models

Changed

  • Breaking: Renamed tasks default,detect,classif to common,detection,classification
  • Breaking: Renamed imageid to record_id
  • Breaking: Added parameter is_new to Parser.parse_fields
  • Removed all dependencies on cv2 for visualisation
  • Use new composite API for visualisation - covers user defined task names & multiple tasks
  • Added a ton of visualisation goodies to icevision.visualize.draw_data.draw_sample - user can now
    • use custom fonts
    • control mask thickness
    • control mask blending
    • prettify labels -- show confidence score & capitalise label
    • plot specific and/or exclude specific labels
    • pass in a dictionary mapping labels to specific colors
    • control label height & width padding from bbox edge
    • add border around label for legibility (color is a parameter)

Breaking:: Rename labels->label_ids, labels_names->labels in LabelsRecordComponent

  • Renamed torchvision resnet backbones:
    • resnet_fpn.resnet18 -> resnet18_fpn
    • resnest_fpn.resnest18 -> resnest18_fpn

Breaking: Added parameters sample and keep_image to convert_raw_prediction Breaking: Renamed VocXmlParser to VOCBBoxParser and VocMaskParser to VOCMaskParser Breaking: Renamed predict_dl to predict_from_dl

[0.6.0b1]

Added

  • mmdetection models

Changed

  • Breaking: All Parser subclasses need to call super.__init__
  • Breaking: LabelsMixin.labels now needs to return List[Hashable] instead of List[int] (labels names instead of label ids)
  • Breaking: Model namespace changes e.g. faster_rcnn -> models.torchvision.faster_rcnn, efficientdet -> models.ross.efficientdet
  • Breaking: Renamed ClassMap.get_name/get_id to ClassMap.get_by_name/get_by_id
  • Breaking: Removes idmap argument from Parser.parse. Instead pass idmap to the constructor (__init__).
  • ClassMap is not created inside of the parser, it's not required to instantiate it before
  • class_map labels get automatically filled while parsing
  • background for class_map is now always 0 (unless no background)
  • adds class_map to Record

Deleted

[0.5.2]

Added

  • aggregate_records_objects function

Changed

  • Added label_field to VIA parser to allow for alternate region_attribute names

[0.5.0]

Added

  • Keypoints full support: data API, model and training
  • VGG Image Annotator v2 JSON format parser for bboxes
  • figsize parameter to show_record and show_sample

Changed

  • improved visualisation for small bboxes
  • COCOMetric now returns all metrics from pycocotools
  • makes torchvision models torchscriptable

[0.4.0]

Added

  • retinanet: model, dataloaders, predict, ...

Changed

  • Breaking: models/rcnn renamed to models/torchvision_models
  • tests/models/rcnn renamed to tests/models/torchvision_models

[0.3.0]

Added

  • pytorch 1.7 support, all dependencies updated
  • tutorial with hard negative samples
  • ability to skip record while parsing

Changed

  • show_preds visual improvement

[0.2.2]

Added

  • Cache records after parsing with the new parameter cache_filepath added to Parser.parse (#504)
  • Added pretrained: bool = True argument to both faster_rcnn and mask_rcnn model() methods. (#516)
  • new class EncodedRLEs
  • all masks get converted to EncodedRLEs at parsing time

Changed

  • Removed warning on autofixing masks
  • RLE default counts is now COCO style
  • renamed Mask.to_erle to Mask.to_erles

[0.2.1]

Changed

  • updated matplotlib and ipykernel minimum version for colab compatibility

[0.2.0]

IMPORTANT

  • Switched from poetry to setuptools

Added

  • Function wandb_img_preds to help logging bboxes to wandb
  • wandb as a soft dependency
  • Template code for parsers.SizeMixin if parsers.FilepathMixin is used
  • Get image size without opening image with get_image_size
  • Ability to skip record while parsing with AbortParseRecord
  • Autofix for record: autofix_records function and autofix:bool parameter added to Parser.parse
  • Record class and mixins, create_mixed_record function to help creating Records
  • InvalidDataError for BBox
  • Catches InvalidDataError while parsing data

Changed

  • Breaking: Unified parsers.SizeMixin functions image_width and image_height into a single function image_width_height
  • Rename Parser SizeMixin fields from width height to image_width image_height

Deleted

  • Removed CombinedParser, all parsing can be done with the standard Parser

[0.1.6]

Added

  • Efficientdet now support empty annotations

Changed

  • Returns float instead of dict on FastaiMetricAdapter

[0.1.5]

Changed

  • Updates fastai2 to the final release version

[0.1.4]

Added

  • soft import icedata in icevision.all
  • show_pbar parameter to COCOMetric

Changed

Deleted

[0.1.3]

Changed

  • Effdet as direct dependency

[0.1.2]

Added

  • show_results function for each model

Changed

  • Default data_splitter for Parser changed to RandomSplitter
  • Renamed package from mantisshrimp to icevision

Deleted

  • Removed datasets module to instead use the new icedata package

[0.0.9]

Added

  • batch, samples = <model_name>.build_infer_batch(dataset)
  • preds = <model_name>.predict(model, batch)
  • infer_dl = <model_name>.infer_dataloader(dataset)
  • samples, preds = predict_dl(model, infer_dl)
  • Dataset.from_images Contructs a Dataset from a list of images (numpy arrays)
  • tfms.A.aug_tfms for easy access to common augmentation transforms with albumentations
  • tfms.A.resize_and_pad, useful as a validation transform
  • **predict_kwargs to predict_dl signature
  • from mantisshrimp.all import * to import internal modules and external imports
  • show parameter to show_img
  • download_gdrive and download_and_extract_gdrive
  • New datasets pennfundan and birds

Changed

  • Renames AlbuTransform to AlbumentationTransforms
  • All build_batch method now returns batch, samples, the batch is always a tuple of inputs to the model
  • batch_tfms moved to tfms.batch
  • AlbumentationTransforms moved to tfms.A.Adapter
  • All parsers function were moved to their own namespace parsers instead of being on the global namespace so, for example, instead of Parser now we have to do parsers.Parser
  • Removed Parser word from Mixins, e.g. ImageidParserMixin -> parsers.ImageidMixin
  • Removed Parser word from parser default bundle, e.g. FasterRCNNParser -> parsers.FasterRCNN
  • COCO and VOC parsers moved from datasets to parsers
  • DataSplitters moved from parsers/splits.py to utils/data_splitter.py
  • Renames *_dataloader to *_dl, e.g. mask_rcnn.train_dataloader to mask_rcnn.train_dl
  • Moves RecordType from parsers to core
  • Refactors IDMap, adds methods get_name and get_id
  • Moves IDMap from utils to data
  • DataSplitter.split now receives idmap instead of ids

[0.0.0-pre-release]

Added

  • CaptureStdout for capturing writes to stdout (print), e.g. from COCOMetric
  • mantisshrimp.models.<model_name>.convert_raw_predictions to convert raw preds (tensors output from the model) to library standard dict
  • COCOMetricType for selecting what metric type to use (bbox, mask, keypoints)
  • COCOMetric fixed
  • sort parameter for get_image_files
  • ClassMap: A class that handles the mapping between ids and names, with the optional insertion of the background class

Changed

  • All dataloaders now return the batch and the records, e.g. return (images, targets), records
  • Metric.accumulate signature changed to (records, preds), reflects in FastaiMetricAdapter and LightningModelAdapter
  • datasets.<name>.CLASSES substituted by a function datasets.<name>.class_map that returns a ClassMap
  • datasets.voc.VocXmlParser, show methods: parameter classes: Sequence[str] substituted by class_map: ClassMap
  • datasets.fridge.parser, datasets.pets.parser: additional required parameter class_map

Removed

  • MantisFasterRCNN, MantisMaskRCNN
  • MantisEfficientDet
  • CategoryMap, Category
  • MantisModule

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