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Computer vision is a highly booming technology where a lot of data are handled. As the data usage is too much there is a lack of data annotation/training tools. Our aim is to develop an opensource tool which monitors the

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Seyali is 4X Faster Image annotaion tool

Critical of Data Annotation:

  • Data is the backbone of AI and ML algorithms.

  • Data annotation facilitates a deeper understanding of the meanings of the objects, thereby allowing algorithms to perform better.

  • Computers can’t process visual information the way human brains do.

  • If data labelling is not done, ML algorithms cannot compute the essential attributes with ease.

Advantages of Seyali:

  • Easy creation of labelled datasets.

  • Fast track model training.

  • An important step in the machine learning dataset-building process.

  • Seyali has a user-friendly interface that allows users to upload and annotate images for training their computer vision models.

  • Seyali integrates with other popular computer vision platforms such as TensorFlow and PyTorch, making importing and exporting models easily.

Future plan of Seyali annotation tool:

  • Smart labelling tools will dominate the future AI and ML landscape.

  • Data annotation capabilities will be fully automatic, detecting labels without any manual intervention.

  • As machine learning algorithms become more advanced, we may see more automation in the annotation process. For example, tools that can automatically identify and label objects in an image, or that can suggest annotations based on user input.

  • Annotation types such as bounding boxes, polygons, and semantic segmentation, we may see more advanced types of annotations in the future. For example, tools that can annotate 3D objects, or that can annotate multiple objects at once.

Parameswaran P
Balaji Madhesh
Parthiban Marimuthu

Project created by Gokulnath

March 2, 2023