Black-and-white landscape image colorization with Pytorch
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Updated
Jul 16, 2018 - Python
Black-and-white landscape image colorization with Pytorch
Conditional GAN for colorizing grayscale images
This is a Gray-Scale Image Colorizer that is based on a modified Pix2Pix structure
This is an Image-Colorization project for astronomical images
image colorization software for colorizing black and white images using AI.
Semester III and IV project
A PyTorch-based GAN model for colorizing grayscale SAR (Synthetic Aperture Radar) images. Utilizes a convolutional Generator and Discriminator in an adversarial setup to produce realistic color outputs.
ECCV16 and Siggraph17 onnx- converted colorizer
This project utilizes GANs for converting grayscale images to color, leveraging deep learning models to enhance colorization accuracy. It features customizable training pipelines, evaluation metrics, and supports further improvements with new models and techniques.
Image colorization with a Multivariate Bernoulli Mixture Density network.
Landscape and face image colorization with Generative Adversarial Networks (GANs)
An image/video colorization web application with authentication, user history and image editing posibilities
UNet model to colorize black & white images
Colors Black & White movies using Deep Learning
Deep Neural Net for coloring grayscale images using local and global image features
Deep learning-based application to colorize grayscale images using a CNN, with a Flask-based web interface
Converts black and white image to colour image using pre-trained models and OpenCV
Deep learning model for image colorization using U-Net++ with LAB color space input.
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