AUTOMATIC COLORIZATION USING CONVOLUTIONAL NEURAL NETWORKS

Automatic Colorization helps to hallucinate what an input gray scale image would look like when colorized. Automatic coloring makes it look and feel better than Grayscale. One of the most important technologies used in Machine learning is Deep Learning. Deep learning is nothing but to train the computer with certain algorithms which imitates the working of the human brain. Some of the areas in which it is used are medical, Industrial Automation, Electronics etc. The main objective of this project is coloring Grayscale images. We have umbrellaed the concepts of convolutional neural networks along with the use of the Opencv library in Python to construct our desired model. A user interface has also been fabricated to get personalized inputs using PIL. The user had to give details about boundaries, what colors to put, etc. Colorization requires considerable user intervention and remains a tedious, time consuming, and expensive task. So, in this paper we try to build a model to colorize the grayscale images automatically by using some modern deep learning techniques. In colorization task, the model needs to find characteristics to map grayscale images with colored ones.