Automatic Object Detection and Room Classification

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Automatic Object Detection and Room Classification

Mojo Case Study

Problem Statement

Customer has a specific requirement to Classify rooms based on objects within 70,000 unlabeled images (28 x 28 dimensions). The goal is to detect multiple objects in each image and classify the room type, such as the living room or bedroom, despite the lack of labeled data. Developing a solution to handle this large, unlabeled dataset and accurately identify and categorize room types is crucial.

Our solution

Object Detection and Room Classification: Utilize a pre-trained machine learning model to detect and identify multiple objects within images. Classify the room type (e.g., living room, bedroom) based on the detected objects.
Image Quality Assessment: Assess image quality and sharpness by analyzing image pixels to ensure clarity and detail for accurate detection and classification.
Automatic Object Blurring: Implement an automated system to detect and blur unnecessary objects or elements in the image, enhancing focus on relevant features and improving overall data quality.

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Benefits

Enhanced Detection and Categorization: The pre-trained model accurately identifies multiple objects in images and classifies the room type based on these objects, ensuring precise and reliable room categorization.
Enhanced Clarity and Relevance: By assessing image quality and automatically blurring unnecessary elements, the solution ensures that only relevant features are highlighted, leading to better data quality and more effective object detection.