CIDACC: Chlorella vulgaris Image Dataset for Automated Cell Counting

This CIDACC dataset was created to determine the cell population of Chlorella vulgaris microalga during cultivation. Chlorella vulgaris has diverse applications, including use as food supplement, biofuel production, and pollutant removal. High resolution images were collected using a microscope and annotated, focusing on computer vision and machine learning models creation for automatic Chlorella cell detection, counting, size and geometry estimation.

The dataset is organized hierarchically into multiple folders and subfolders, containing 628 images taken from a microscope and further processed by external tools. It consists of three root folders: “original_images”, “clusters”, and “distinct”. The “original_images” folder holds the raw microscope images with initial dimensions of 2592x1944 pixels. These images are further subdivided into “clusters” and “distinct” folders, indicating whether they contain single cells or cell clusters. The “clusters” and “distinct” root folders contain annotated images with reduced dimensions (640x640 pixels). The “clusters” folder includes images showing C. vulgaris cells forming clusters, where counting individual cells is not possible. The “distinct” folder contains images of cells that can be counted with high precision.