Algoritmia中文版

不会用ps？不会p照片？不想用美颜相机？那Algoritmia非常适合你，它是由加州大学的一个团队打造的软件，Algoritmia能照片变成彩色，更简单易用的处理照片。

Algoritmia特色说明

Algoritmia自动生成的颜色可能并不是碟子的真实颜色，这时候你就可以在碟子上选取一个点，然后在左侧的编辑框选择最准确的颜色，Algoritmia就会即刻生成效果图，你还可以进一步调整，直到满意为止。

功能

可手动调色

可一键自动化上色

黑白照变彩色照非常逼真

可将任意黑白照片添加色彩

采用智能色彩识别调节技术

软件介绍

来自加州大学的Richard Zhang及其团队推出了一款名为Algoritmia的APP，可以让黑白照片自动变成彩色，为不少人带来了福音。然而，Algoritmia也存在一些缺陷，它虽然能把照片变成彩色，但是颜色并不一定准确。该团队对Algoritmia进行了进一步优化，让用户可以参与进来，主动来挑选准确的颜色，Algoritmia会根据用户的选择自动调整，以达到最优效果，而这整个过程，比PS要简单的多。

官方英文简介

Interactive Deep Colorization

[Project Page] [Paper] [Demo Video] [Seminar Talk]

Richard Zhang*, Jun-Yan Zhu*, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, and Alexei A. Efros. Real-Time User-Guided Image Colorization with Learned Deep Priors. In ACM Transactions on Graphics (SIGGRAPH 2017). (*indicates equal contribution)

We first describe the system (0) Prerequisities and steps for (1) Getting started. We then describe the interactive colorization demo (2) Interactive Colorization (Local Hints Network). There are two demos: (a) a "barebones" version in iPython notebook and (b) the full GUI we used in our paper. We then provide an example of the (3) Global Hints Network.

(0) Prerequisites

Linux or OSX

Caffe

CPU or NVIDIA GPU + CUDA CuDNN.

(1) Getting Started

Clone this repo:

git clone https://github.com/junyanz/interactive-deep-colorization ideepcolorcd ideepcolor

Download the reference model

bash ./models/fetch_models.sh

Install Caffe and Python libraries (OpenCV)

(2) Interactive Colorization (Local Hints Network)

We provide a "barebones" demo in iPython notebook, which does not require QT. We also provide our full GUI demo.

2(a) Barebones Interactive Colorization Demo

Run ipython notebook and click on DemoInteractiveColorization.ipynb.

2(b) Full Demo GUI

Install Qt4 and QDarkStyle. (See [Requirements](## (A) Requirements))

Run the UI: python ideepcolor.py --gpu [GPU_ID]. Arguments are described below:

--win_size    [512] GUI window size --gpu         [0] GPU number --image_file  ['./test_imgs/mortar_pestle.jpg'] path to the image file

User interactions

Adding points: Left-click somewhere on the input pad

Moving points: Left-click and hold on a point on the input pad, drag to desired location, and let go

Changing colors: For currently selected point, choose a recommended color (middle-left) or choose a color on the ab color gamut (top-left)

Removing points: Right-click on a point on the input pad

Changing patch size: Mouse wheel changes the patch size from 1x1 to 9x9

Load image: Click the load image button and choose desired image

Restart: Click on the restart button. All points on the pad will be removed.

Save result: Click on the save button. This will save the resulting colorization in a directory where the image_file was, along with the user input ab values.

Quit: Click on the quit button.

(3) Global Hints Network

We include an example usage of our Global Hints Network, applied to global histogram transfer. We show its usage in an iPython notebook.

Add ./caffe_files to your PYTHONPATH

Run ipython notebook. Click on ./DemoGlobalHistogramTransfer.ipynb

(A) Requirements

Caffe (See Caffe installation document)

OpenCV

sudo apt-get install python-opencv

Qt4

sudo apt-get install python-qt4

QDarkStyle

sudo pip install qdarkstyle

(B) Cat Paper Collection

One of the authors objects to the inclusion of this list, due to an allergy. Another author objects on the basis that cats are silly creatures and this is a serious, scientific paper. However, if you love cats, and love reading cool graphics, vision, and learning papers, please check out the Cat Paper Collection: [Github] [Webpage]