This project focuses on the development of an AI-powered software tailored for event photos. The software enables photographers to upload event pictures and employs advanced AI algorithms to segregate low-quality photographs based on specific criteria, such as blurriness, duplication, closed eyes, optimal face angle, and head tilt detection.
The system utilizes AI algorithms to identify and segregate low-quality photos based on the following criteria:
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Blurriness Detection: Implement an algorithm to detect blurry images and separate them from clear, high-quality photos.
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Duplicate Image Identification: Identify and remove duplicate images to maintain a clean and organized photo collection.
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Closed Eyes Detection: Utilize facial recognition and eye detection to identify photos where subjects have closed eyes and flag them for review.
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Best Face Angle Detection: Task focused on finding the optimal angle of a face in an image to enhance photo quality.
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Head Tilt Detection: Measure the angle of the head in an image or video to ensure an optimal perspective.
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Emotion Detection: The system shall be equipped to detect and categorize photos based on the emotions displayed by subjects.
This software aims to streamline the photo curation process, providing photographers with a tool to manage their event photo collections efficiently.