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Detection of shapes and counting in toy manufacturing industry with help of Phython

机译:在Python的帮助下检测玩具制造业的形状和计数

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摘要

The proposed work focused on detection of shapes of toy and its count in the particular area to segregate the items manufactured in the toy industry for packing. The identification of shapes using Ramer-Douglas-Peucker algorithm in Phython language is a technique implemented with the help of open CV image processing tool. The prototype of the model is developed by giving a sample input image with different shapes as file. The screen in the phython language shows the name of the shapes with its count in the input sample file. The proposed idea may extend in tool manufacturing industry to identify the different shapes of part which is difficult to segregate and consume more man power for the particular process.
机译:拟议的工作侧重于检测玩具形状及其计数,在特定区域中分离玩具行业制造的物品进行包装。使用Ramthon语言中的Ramer-Douglas-Peucker算法的形状的识别是在开放式CV图像处理工具的帮助下实现的技术。通过为文件提供不同形状的样本输入图像来开发模型的原型。植物语言中的屏幕显示输入示例文件中的形状的名称。该提议的想法可以在工具制造业中延伸,以识别难以隔离和消耗更多的人为特定过程的不同形式的部分。

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