50 Types of Car Parts -Image Classification

This dataset is curated to provide a diverse collection of images for 50 different types of car parts, making it suitable for various computer vision tasks, particularly image classification. The dataset is divided into three main subsets: training, validation, and testing, all containing images from the same 50 categories of car parts. It is ideal for automotive-related machine learning applications, especially for training models to identify and categorize car components.

The training set doesn’t have an equal number of images for each part. The class “Ignition Coil” has the most training images, which is 200, while the class “Leaf Spring” has the fewest, only 110 images.

Both the validation and test sets have 5 images for each of the 50 parts. The images are all in JPG format and have dimensions of 224 x 224 pixels with 3 color channels (RGB). These are the original images, without any modifications or changes made to them.