Computer Vision Data Acceptability Scoring With IOU Feedback
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Solution Overview
Problem
Existing systems struggle to efficiently organize, filter, and sort unstructured data from computer vision models, leading to inefficiencies in analytical analysis.
Innovation Solution
A system utilizing processors, memory components, and machine-readable instructions to generate metrics, compare them to acceptability thresholds, and automatically generate feedback to improve the acceptability of computer vision data, including filtering and sorting based on intersection over union (IOU) metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If unstructured data from computer vision models is processed without systematic inspection, then processing speed is maintained, but data quality and acceptability deteriorate
Solution Approach 1:
The system performs preliminary inspection of computer vision data before final processing by generating metrics and comparing them against acceptability thresholds. This preliminary action identifies unacceptable data early, preventing wasted processing time on low-quality inputs and improving overall data reliability without significantly impacting productivity.
Solution Approach 2:
The system generates feedback based on the inspection results, providing information about data quality metrics and acceptability determinations. This feedback loop enables continuous improvement of data processing by identifying patterns in unacceptable data and adjusting processing parameters accordingly, thereby improving both reliability and long-term productivity.
2Measurement precision
If comprehensive metrics are generated for all computer vision data, then measurement precision is improved, but computational complexity increases
Solution Approach 1:
The system segments the data inspection process into distinct components: generating specific metrics (such as IOU metrics), comparing metrics against thresholds, and making acceptability determinations. This segmentation allows for precise measurement of individual data aspects while managing system complexity through modular processing steps that can be independently optimized.
3Ease of operation
If data filtering and sorting operations are implemented, then data organization is improved, but processing time increases
Solution Approach 1:
The system performs filtering and sorting operations as preliminary actions based on generated metrics and acceptability determinations. By organizing data early based on quality metrics, the system reduces the amount of data requiring detailed analysis later, thereby improving ease of operation while actually reducing total processing time through early elimination of unacceptable data.
Data Source
AI summary
A system for computer vision data acceptability analysis and methods of use to receive a plurality of computer vision data comprising data processed via a computer vision model with one or more rules, generate one or more metrics for each of the plurality of computer vision data based on the one or more rules, compare a compared metric of the one or more metrics for each of the plurality of computer vision data to an acceptability threshold, determine the computer vision data to be acceptable when the compared metric associated with the computer vision data is equal to or above the acceptability threshold, generate an overall acceptability score for the plurality of computer vision data, and automatically generate feedback for computer vision model processing based on the overall acceptability score to improve acceptability.