The project aims to develop an AI/ML tool capable of extracting data from bar graphs, a common visualization format used in various industries. The tool will automate the process of data extraction, which is traditionally manual and time-consuming, thereby increasing efficiency and accuracy. Learners will apply their knowledge of machine learning algorithms, image processing, and data analysis to create a solution that can identify and interpret bar graph elements such as axes, bars, and labels. The project will involve training a model on a dataset of bar graph images, testing its accuracy, and refining it for optimal performance. This project provides an opportunity for learners to bridge theoretical knowledge with practical application in the field of AI and machine learning.

The project deliverables include a functional AI/ML tool that can accurately extract data from bar graphs, a comprehensive report detailing the development process, and a presentation demonstrating the tool's capabilities. Additionally, learners will provide documentation outlining the tool's usage instructions and potential areas for future improvement. These deliverables will showcase the learners' ability to apply machine learning techniques to solve real-world data extraction challenges.

GUI must be able to adjust the location of data points, add or subtract data points where the algorithm fails to detect the information. Algorithm should extract the X-Y axis labels and titles, and the legend data. Must be able to convert the bar back into its spreadsheet form.