NIMA: Neural IMage Assessment This is a PyTorch implementation of the paper NIMA: Neural IMage Assessment (accepted at IEEE Transactions on Image Processing) by Hossein Talebi and Peyman Milanfar. You can learn more from this post at Google Research Blog. Implementation Details The model was trained on the AVA (Aesthetic Visual Analysis) dataset containing 255,500+ images. You can get it from here. Note: there may be some corrupted images in the dataset, remove them first before you start training. Use […]

FastPhotoStyle Given a content photo and a style photo, the code can transfer the style of the style photo to the content photo. The details of the algorithm behind the code is documented in our arxiv paper. Please cite the paper if this code repository is used in your publications. GitHub https://github.com/NVIDIA/FastPhotoStyle    

Deep-Image-Analogy This project is a python implementation of Deep Image Analogy. Some results Requirements python 3 opencv3 If you use anaconda, you can install opencv3 by conda install opencv pytorch See pytorch for installation Codes in branch “master” works with pytorch 0.4 Codes in branch “pytorch0.3” works with pytorch 0.3 cuda (CPU version is not implemented yet) Usage (demo) python main.py –resize_ratio 0.5 –weight 2 –img_A_path data/demo/ava.png –img_BP_path data/demo/mona.png –use_cuda True GitHub https://github.com/Ben-Louis/Deep-Image-Analogy-PyTorch    

PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from this post at Google Research Blog. Installing Docker docker run -it truskovskiyk/nima:latest /bin/bash PYPI package (In Progress) pip install nima VirtualEnv git clone https://github.com/truskovskiyk/nima.pytorch.git cd nima.pytorch virtualenv -p python3.7 env source ./env/bin/activate Dataset The model was trained on the AVA (Aesthetic Visual Analysis) datasetYou can get it from hereHere are some examples of images with theire scores Pre-train […]