From Image Classification to Object Detection

Image classification vs. object detection

While the image classification problem focuses on classifying the images, in object detection, there might be more than one object we’re searching for. Our task is to find all of them placed in the most appropriate boxes with their belonging classes. Therefore, our goal is relatively more complex than image classification. We have to first detect the objects by locating them with bounding boxes, then classify them to decide which class this box (thing) belongs to.

To sum up:

• Image classification: It predicts the class of an image.

• Object localization: It locates the presence of objects in an image and indicates their location with a bounding box.

• Object detection: It locates the presence of objects with a bounding box and detects the classes of the located objects in these boxes.

Since object detection involves providing both the location and the class of an object instance, we can consider it a sum of these two tasks. Depending on the object detection architecture, both tasks can be solved simultaneously or sequentially. We need to know that both tasks should be solved in an object detection model.

The image classification task involves classifying images. However, the task seems more complex now, with multiple issues to solve. We need to locate objects with bounding boxes, which means we need to predict four coordinates of this box. We then need to apply classification to decide which class belongs to this object. The localization task is not a classification problem but a regression problem!

Classification vs. regression

When working with classification and regression tasks, it is always good to know the difference between them. Let’s take a look at the regression types and the relationship between regression and classification:

Linear regression

Linear regression makes predictions for continuous or numeric variables. For example, predicting a house’s rent price according to its location, size, and how old it is. It’s not a classification but a continuous numerical answer that the model has to find.

One of the equations for a simple linear regression task is $y=mx$ ...