hefv57,github

hyperas

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

iFeature is a comprehensive Python-based toolkit for generating various numerical feature representation schemes from protein or peptide sequences. iFeature is capable of calculating and extracting a wide spectrum of 18 major sequence encoding schemes that encompass 53 different types of feature descriptors. Furthermore, iFeature also integrates five kinds of frequently used feature clustering algorithms, four feature selection algorithms and three dimensionality reduction algorithms.

ignite

High-level library to help with training neural networks in PyTorch

image-analogies

Generate image analogies using neural matching and blending.

image-captioning

Image Captioning using InceptionV3 and beam search

image-segmentation-keras

Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.

image-super-resolution

Implementation of Super Resolution CNN in Keras.

image-super-resolution-1

🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

image-to-image-papers

A collection of image to image papers

image_harmonization_datasets

Benchmark datasets and code used in our paper "DoveNet: Deep Image Harmonization via Domain Verification", CVPR2020. Useful for Image harmonization, image composition/compositing, etc.

image_reconstruction

Data denoising with auto-encoders. Python3/TensorFlow implementation.

image_to_numpy

Load an image file into a numpy array with Exif orientation support. Prevents upside-down and sideways images!

imageatm

Image classification for everyone.

imagenet-downloader

A simple way to browse ImageNet classes and download some images from it.

imagenet_utils

:arrow_double_down: Utils to help download images by id, crop bounding box, label images, etc.

imgclsmob

Sandbox for training convolutional networks for computer vision

imutils

A series of convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.