银物检测 [英] Silver Object Detection

问题描述

嗨。

我想在不同的地方检测银色物体，如下图中的这个罐子：



http://8pic.ir/images/87258923242677915413.png [ ^ ]



什么是使用open cv执行此操作的最佳方法？

Hi.
I want detect the silver objects in different places like this Canister in this picture :

http://8pic.ir/images/87258923242677915413.png[^]

whats the best way to do this with open cv ?

推荐答案

如果我理解你的问题是正确的，那么你正在研究一个机器学习项目，目标的一部分是检测银材料，银球，银勺等。

但是，在你能做到这一点之前，你必须训练你的机器来区分不同材料的物体，比如银，玻璃，木头等。这在AI中被称为监督训练或监督学习。 />


一般来说，建立有监督的培训AI项目的方法如下：

1.收集很多具有已知类别的数据，在您的情况下，已知但不同材料的对象的图像，每个数据的数量应该大致相同，以便保持数据平衡;

2.将数据拆分为训练集和测试集，比如说60％的训练集和40％的测试集;

3.在训练集上训练机器学习模型;

4.测试在测试装置上训练的模型来测量精度。



有许多有监督的训练AI技术可以用来实现这一点，ANN和SVM只是其中的一部分。



由于您对OpenCV感兴趣，没有比访问其官方网站更好的地方了。 了解更多信息。

If I understand you question correctly, you are working on a machine learning project and part of the objective is to detect objects of silver materials, say silver ball, silver spoon etc.
However, before you can do that, you have to train your machine to differentiate objects of different materials, say silver, glass, wood etc. This is called supervised training or supervised learning in AI.

Generally, the approach towards building a supervised training AI project is as follows:
1. Collect a lot of data with known categories, in your case, images of objects of known but different materials the quantity of each should be about the same so as to maintain data balance;
2. Split the data into a training set and test set, say 60% training set and 40% test set;
3. Train the machine learning model on the training set;
4. Test the trained model on the test set to measure the accuracy.

There are many supervised training AI techniques that you can use to achieve this, ANN and SVM are just some of them.

Since you are interested in OpenCV, there are no better place than to visit its official website for more information.

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