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Classification

                 Classification is the process of determining the class or category of an input image. The input image is analysed
                 using a Machine Learning Algorithm, which assigns it to one of the predefined categories. These categories are
                 established by training the algorithm on a set of labelled sample images. This foundational task in Computer Vision
                 has numerous practical applications, such as medical diagnostics, object recognition and autonomous vehicles.
                 Classification and Localisation


                 Localisation means where the object is located in the image. So, this combined task of classification and localisation
                 means processing the input image to identify its category along with the location of the object in the image.
                 Multiple Objects


                 This means giving multiple images as input to the Computer Vision application. It can be further divided into two
                 categories i.e. object detection and instance segmentation.
                 Object Detection

                 Object detection is the process of identifying or detecting the instances of real-world objects like cars, bicycles,
                 buses, animals, humans, or anything on which the detection model has been trained. This kind of system uses
                 object detection algorithms to extract the features of the object and after that Machine Learning Algorithms will
                 recognise the instances of an object category by matching it with the sample images already fed into the system.
                 It is commonly used in applications such as image retrieval and automated vehicle parking systems.
                 Instance Segmentation

                 Instance segmentation is the process of dividing an image into smaller segments to identify individual objects
                 within  it,  distinguishing  them  from  the  background  or  other  objects  in  the  image.  Each  object  instance  is
                 detected, classified, and assigned a unique label. Following this, every pixel in the image is labelled based on the
                 corresponding object instance it belongs to. A segmentation algorithm takes an image as input and outputs a
                 collection of regions (or segments).
                 Another example of Computer Vision analysis can be seen as follows:
                                                 Classification                                     Instance
                        Classification                                Object Detection
                                                 + Localisation                                  Segmentation










                            CAT                     CAT                    DOG, CAT                  DOG, CAT

                                     Single object                                  Multiple objects


                         Basics of Images


                 An image is a visual representation of any object. The term ‘image’ means a picture that has been created or
                 stored in electronic form. It can be described in terms of vector graphics or raster graphics. An image comprises
                 of a rectangular array of dots known as pixel. The size of the image is specified as width × height, in the number
                 of pixels.



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