A detailed look at how our team expertly managed a vast image sourcing project to boost a tech giant’s machine learning project.
Project Overview
A prominent multinational technology corporation faced the challenge of acquiring 10,000 images of various brands within a stringent deadline to bolster an AI machine learning project. The client required these images categorized into three distinct groups: “Simple,” “2D,” and “In the Wild,” with each brand needing at least 200 high-quality images.
Client Requirement
The project’s scope was expansive, necessitating a detailed and efficient approach to source images that could serve as foundational data for AI training. The images needed not only to fulfill quantity but also to meet high standards of clarity and relevance to the specified categories.
Our Solution
To meet these requirements, Tyrian Purple devised a comprehensive image sourcing strategy. We assembled a team of experts skilled in digital image curation and trained them specifically in the client’s classification criteria. Our team meticulously sourced 15 images per brand in the ‘Simple’ category, 45 in the ‘2D’ category, and 150 in the ‘In the Wild’ category, ensuring each image was precisely aligned with the client’s specifications. A dual-layer quality control process was implemented to ensure all images met the exacting standards before final submission.
Outcome
The project was a resounding success, with Tyrian Purple delivering all 10,000 images ahead of schedule. The client expressed high satisfaction with the quality and precision of the sourced images, which not only met but exceeded their expectations. This achievement underscores Tyrian Purple’s capability to handle large-scale, high-stakes projects efficiently and effectively.
