您首先需要清楚地定义您要实现的内容：将功能提取到一组图像在实现机器学习算法方面有用！太多含糊了，给你任何指导。

You would first need to clearly define what you are trying to achieve: "extract feature to a set of images, in a way useful to implement a machine learning algorithm!" is much too vague to give you any guidance.

你是否想做：

• 图像整体的图像分类（例如室内场景与室外场景）？

• image classification of the picture as a whole (e.g. indoor scene vs outdoor scene)?

对象识别（例如，识别几个相同的对象在不同的​​图片）在一组图片的子部分内，可能使用各种尺寸的窗口的扫描程序？

object recognition (e.g. recognizing several instances of the same object in different pictures) inside sub-parts of a set of pictures, maybe using a scan procedures with windows of various sizes?

对象检测和类 - 基于分类（例如，在图片中发现所有出现的汽车或行人以及这些类的每一次实例的边界框）？

object detection and class-based categorization (e.g. finding all occurrences of cars or pedestrians in pictures and a bounding box around each occurrence of instances of those classes)?

全图像语义解析每个片段（构建，路，人，树）的像素分割+类分类...

full picture semantic parsing a.k.a. segmentation of the pixels + class categorization of each segment (build, road, people, trees)...

每个这些任务将需要不同的管道（特征提取+机器学习模型组合）。

Each of those tasks will require different pipelines (feature extraction + machine learning models combo).

您应该首先阅读一本关于该主题的书，例如： http://szeliski.org/Book/

You should probably start by reading a book on the subject, for instance: http://szeliski.org/Book/

另外作为附注，***可能不是***的地方提出这样的开放式问题。

Also as a side note, *** is probably not the best place to ask such open ended questions.