Claire, the Quality Assurance Coordinator at MDFT Pro, is evaluating computer vision solutions to automatically assess training materials and equipment condition from inspection photographs. MDFT Pro, a well-known training agency, needs to process images that may contain multiple damaged items in a single photo, such as several broken chairs in a classroom or multiple damaged textbooks on a shelf. Claire is comparing different AI approaches to understand which technology can identify and count individual instances of damaged equipment versus simply categorizing the overall image content. She needs a solution that can handle scenarios where multiple damaged items appear in the same photograph.
Can object classification technology identify and count multiple instances of damaged equipment within a single image?
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