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Use Active Learning to diversely sample the dataset and generate new labels to train a classifier to predict whether the microscopy image contains a linear arrangement of 53BP1 accumulation on chromatin surrounding DNA damage, or irradiation induced foci.
A desktop graphical tool for labelling image training data for object detection and other machine learning uses. Bounding boxes can be saved in ImageNet Pascal VOC (XML), JSON and CSV formats. Scripts are provided to convert the output to TensorFlow TFRecords for use with the object detection API.
datalabel is a UI-based data editing tool that makes it easy to create labeled text data in a dataframe. With datalabel, you can quickly and effortlessly edit your data without having to write any code. Its intuitive interface makes it ideal for both experienced data professionals and those new to data editing.
This streamlines the process of annotating data for machine learning tasks, making it easier and more efficient for teams to create labeled datasets by leveraging Label Studio and Bulk
A dashboard for Label Studio Free, allowing you to check for your team progress even on Free plan of Label Studio. It utilizes the Label Studio API and providing basic insights about your team progress.
This small module connects Label Studio with Fonduer by creating a fonduer labeling function for gold labels from a label studio export. Documentation: https://irgroup.github.io/labelstudio-to-fonduer/