Package: polimorfo
polimòrfoPolimòrfo (πολύμορϕος, comp. di πολυ- «poli-» e μορϕή «forma») is a dataset loader and converter library for object detection segmentation and classification.
The goal of the project is to create a library able to process dataset in format:COCO: Common Objects in ContextPascal VOC: Visual Object Classes ChallengeGoogle Open Images: Object Detection and Segmentation dataset released by Googleand transform these dataset into a common format (COCO).Moreover, the library offers utilies to handle (load, convert, store and transform) the various type of annotations.
This is important when you need to:
- convert mask to polygons
- store mask in a efficient format
- convert mask/poygons into bounding boxesFree software: Apache Software License 2.0Documentation:https://polimorfo.readthedocs.io.FeaturesTODO[X] Coco dataset[X] download coco datasets for train and val[X] add annotations loader and converter[X] add the ability to create dataet from scratch[ ] add voc dataset format[ ]CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.2.0 (2020-02-18)Add support to process coco dataset0.2.1 (2020-02-28)add support to download files and archives from the web and google drive0.3.0 (2020-10-04)addedd support for removing categories and other utilities0.4.0 (2020-10-05)addedd support to create a dataset from scratch0.5.0 (2020-10-06)added support to visualize images and annotationsmake image removing optional during annotations and categories deletion0.6.0 (2020-10-12)added copy datasetadded split dataset0.6.1 (2020-10-12)fixed a bug in colors generation for show images0.6.2 (2020-10-12)update signature for functiondef update_images_path(self, func):0.7.0 (2020-10-19)add method to dump dataset in format segmentation map0.8.0 (2020-10-23)fixed bug in maskutils.mask_to_polygonsadd class to transform the predictions from instance and semantic segmentation in coco formatfixed bug in add_image, add_annotation, add_categorymake load_image and load_images load random images sampled from the dataset0.8.1 (2020-10-23)fixed bug for tqdm when removing a category and its annotations from the dataset0.8.2 (2020-10-23)removed the prefix jpg when saving masksupdate draw instance to draw only bounding boxes0.8.3 (2020-10-24)fixed bug in enum for draw instances0.8.4 (2020-10-24)add show bounding boxes0.8.5 (2020-10-24)changed representation for masks from [width, height, labels] to [labels, width, height]0.8.6 (2020-10-24)added method to crop imagesadded method to move annotations with respect a bounding box0.8.7 (2020-10-24)support fully creation o a new dataset0.8.8-11 (2020-10-26)fixed vairous bugs0.8.12 (2020-10-26)fixed bug when the size of the segments is equal to 40.8.13 (2020-10-26)fixed bug in json dump to serialize numpy array0.8.14 (2020-10-26)fixed bug in json dump to serialize numpy types0.9.1 (2020-10-28)fixed various bugsadd index for speedup lookup operations0.9.2 (2020-10-28)add new feature to compute mean average precision and recall per class and global0.9.3 (2020-10-28)add computation of mean average precision and mean average recall per image0.9.4 (2020-10-28)fixed bug in score computation0.9.36fixed bug in mask generationfeature that allows us to add a single mask per component when saving segmentation results0.9.38add min confidence when displaying prediction from a segmentation mask modelnow semantic coco accepts only logits to create annotations0.9.39add new method to remap category idxs0.9.48add new feature to save images and masks to a folder and filter out images and mask with less than k annotations0.9.52the methodget_segmentation_maskreturn also the avg score of the image annotationsthe methodsave_mask_imagessave also a weight files with the avg score for the image