Cankaya

GETTING STARTED, DATA AUGMENTATION, DETECTRON2, TUTORIALA step-by-step guide to implementing a new data augmentation method that needs image, mask, and bounding boxes at the same time such as Simple Copy PastePhoto by Sigmund on UnsplashTable of Contents— Introduction— How do data augmentations work in Detectron2?— Implementing Multimodal Augmentations— Usecase 1: Instance Color Jitter Augmentation— Usecase 2: Copy Paste AugmentationDetectron2 is one of the most powerful deep learning toolboxes for visual recognition…

Machine learning or specifically deep learning in essence is finding a function that describes the data best. This process depends on computing resources, algorithms, and data. In recent years, the deep learning era has developed quite fast in terms of the availability of computing resources, a wide range of machine learning models, and accessibility of datasets. However, annotation of data in the dataset is still a bottleneck because it needs heavy human-labeling efforts e.g. the COCO segmentation dataset required around…

GETTING STARTED, DETECTRON2, DEEP LEARNINGCommon steps to know to start a project on top of detectron2 the state-of-the-art detection and segmentation frameworkPhoto by geralt on PixabayDetectron2 is one of the most powerful deep learning toolboxes for visual recognition. It is designed as flexible as possible to easily switch between different tasks such as Object Detection, Instance Segmentation, Person Keypoint Detection, Panoptic Segmentation, etc. It has built-in support for popular datasets COCO, Cityscapes, LVIS,…