Neural-IMage-Assessment
Image Assessor
Trains neural networks to assess image aesthetics using pre-trained models and custom datasets
A PyTorch Implementation of Neural IMage Assessment
539 stars
5 watching
95 forks
Language: Python
last commit: over 3 years ago computer-visionimage-enhancementmachine-learningphoto-editing
Related projects:
| Repository | Description | Stars |
|---|---|---|
 truskovskiyk/nima.pytorch | Assesses and evaluates images using deep learning models | 335 |
 atiyo/deep_image_prior | Reconstructs images using untrained neural networks to manipulate and transform existing images | 216 |
 felixgwu/img_classification_pk_pytorch | A PyTorch project for comparing image classification models and facilitating quick experiment setup | 366 |
 d-li14/regnet.pytorch | An implementation of a PyTorch-based neural network architecture for image classification tasks. | 68 |
 zwx8981/dbcnn | A deep learning-based system for assessing the quality of images without their original references. | 108 |
 ypxie/pytorch-neucom | An implementation of the Differentiable Neural Computer architecture in PyTorch | 94 |
 owenzlz/deepimageblending | A PyTorch implementation of blending images by optimizing a Poisson loss with style and content loss | 435 |
 misaogura/flashtorch | Toolkit for visualizing neural network behavior in PyTorch | 737 |
 jiupinjia/neural-magic-eye | Training an image processing neural network to recover depth and content from autostereograms | 72 |
 ocampor/image-quality | Library providing a set of tools and algorithms for evaluating the quality of digital images | 402 |
 kaiyangzhou/dassl.pytorch | A PyTorch toolbox for supporting research and development of domain adaptation, generalization, and semi-supervised learning methods in computer vision. | 1,236 |
 bestivictory/ilgnet | A deep learning-based framework for image aesthetics assessment using a convolutional neural network structure | 112 |
 ethanhe42/u-net | A convolutional neural network architecture for biomedical image segmentation | 430 |
 akanimax/pro_gan_pytorch | Implementation of a deep learning model for generating high-quality images with improved stability and variation. | 538 |
 zcyang/imageqa-san | This project provides code for training image question answering models using stacked attention networks and convolutional neural networks. | 108 |