![]() ![]() # construct the argument parser and parse the argumentsĪp.add_argument("-i", "-image", type=str, required=True, Open up the bw2color_image.py file and insert the following code: # import the necessary packages Let’s go ahead and implement black and white image colorization script with OpenCV. Colorizing black and white images with OpenCV Our video script will either use your webcam or accept an input video file and then perform colorization. The image script can process any black and white (also known as grayscale) image you pass in. Our Caffe model and prototxt are inside the model/ directory along with the cluster points NumPy file. We have four sample black and white images in the images/ directory. Once you’ve extracted the zip, you should navigate into the project directory.įrom there, let’s use the tree command to inspect the project structure: $ tree -dirsfirst Go ahead and download the source code, model, and example images using the “Downloads” section of this post. To produce more plausible black and white image colorizations the authors also utilize a few additional techniques including mean annealing and a specialized loss function for color rebalancing (both of which are outside the scope of this post).įor more details on the image colorization algorithm and deep learning model, be sure to refer to the official publication of Zhang et al.
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