Prompt-Based Yarn Spindle Detection for Trolley Positioning
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Solution Overview
Problem
Existing methods for locating yarn spindles in dyeing processes are inefficient and inaccurate, leading to low processing efficiency due to manual search and retrieval.
Innovation Solution
A detection method and apparatus utilizing a target prompt word and a target detection model to identify the position of a yarn spindle by processing multiple images of a trolley with two carrying areas, employing a segmentation network module, information mapping module, and identification module to automate the spindle location process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual search and retrieval method is used to locate yarn spindles, then the system complexity is low, but the productivity is low and the time consumption is high
Solution Approach 1:
The patent replaces the manual mechanical search process with an automated image-based detection system. A detection model processes images of the parking area to automatically identify and locate yarn spindles, substituting human visual search and physical retrieval with computational image analysis and automated positioning, thereby dramatically improving productivity without requiring complex mechanical retrieval devices
Solution Approach 2:
The patent uses image copies (photographs or digital images) of the parking area and yarn spindles to create a virtual representation of the physical space. The detection model analyzes these image copies to locate yarn spindles, eliminating the need for direct physical interaction or complex mechanical search systems while maintaining accurate localization capability
2Measurement precision
If manual search method is used to find yarn spindles, then the device complexity is low, but the measurement precision of yarn spindle position is low
Solution Approach 1:
The patent replaces manual visual search with an automated detection model that processes images to precisely identify yarn spindle positions. The model uses computer vision algorithms to detect and locate yarn spindles in images, providing accurate positional information without requiring complex mechanical measurement devices or manual searching
Solution Approach 2:
The patent introduces images as an intermediary medium between the yarn spindles and the detection system. Instead of directly detecting physical yarn spindles, the system captures images of the parking area and uses a detection model to analyze these images, creating an indirect but precise measurement pathway that improves location accuracy without requiring direct contact or complex physical sensors
Data Source
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AI summary
Provided is a detection method, including: obtaining (S101) a prompt word used to indicate to find a yarn spindle; obtaining (S 102) multiple images of a trolley where the yarn spindle indicated by the prompt word is located, a first image among the multiple images including all yarn spindles carried by a first carrying area among two carrying areas included in the trolley, and a second image among the multiple images including all yarn spindles carried by a second carrying area among the two carrying areas; and inputting (S103) the multiple images and the prompt word into a target detection model to obtain a output image indicating a position of the yarn spindle; where the target detection model is able to identify yarn spindles in an input image based on the yarn spindle indicated by the prompt word to obtain an image indicating the position of the yarn spindle.