Blood Cell Detection and Localization

Objective

This project proceeded in a straightforward manner. The company I collaborated with provided a dataset comprising blood cell images, encompassing both red and white blood cells. The objective was to train an AI model, specifically an object detection model, to accurately detect and localize both red and white blood cells within the images. The workflow I followed was also straightforward.

1. I augmented the image dataset and divided it into three subsets: training, validation, and test datasets.
2. I explored and experimented with various existing object detection models, utilizing different backbone models, using the training and validation datasets.
3. Finally, I tested the trained models using the test dataset and evaluated the results obtained from each model.