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Deliverables relating to the Group Project of Principles of Computer Vision for AI University Unit

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Principles of Computer Vision Group Project

Authors:

Matthias Bartolo ID: 0436103L
Luke Cardona ID: 0011803H
Jerome Agius ID: 0353803L
Isaac Muscat ID: 0265203L

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Description of Task:

This task explored a variety of data augmentation techniques in computer vision, covering both theoretical and practical aspects. The main objectives of the task were to investigate the concept of data augmentation in computer vision, conduct a thorough review of the existing literature on the topic, implement selected techniques using popular frameworks like TensorFlow and PyTorch, as well as develop custom implementations from scratch using OpenCV. Additionally, the task involved generating augmented images using the chosen techniques and evaluating their performance in comparison to other approaches and the original images. By accomplishing these objectives, this task aimed to contribute valuable insights into the field of data augmentation techniques in computer vision, showcasing their potential and effectiveness.

Deliverables:

The repository includes 2 directories one for each question of the assignment

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