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        當(dāng)前位置:首頁(yè)安卓軟件圖像拍照 → Algoritmia中文版app下載 v1.0 最新版
        Algoritmia中文版app下載v1.0 最新版

        Algoritmia中文版app下載

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        • 分類(lèi):圖像拍照
        • 大。10.1M
        • 語(yǔ)言:中文
        • 版本:v1.0 最新版
        • 時(shí)間:2017-05-21
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        • 官網(wǎng):暫無(wú)
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        • 平臺(tái):Android
        • 標(biāo)簽:
        全自動(dòng)化黑白照片上色,將你過(guò)去的記憶重現(xiàn)光彩。
        應(yīng)用截圖
        • Algoritmia中文版app下載v1.0 最新版
        • Algoritmia中文版app下載v1.0 最新版
        • Algoritmia中文版app下載v1.0 最新版
        • Algoritmia中文版app下載v1.0 最新版
        應(yīng)用介紹

        Algoritmia中文版,幫助用戶(hù)快速對(duì)黑白照片進(jìn)行上色處理。Algoritmia漢化版app,經(jīng)過(guò)了1年多的改進(jìn),在自動(dòng)化上色方面得到了更大的提升,用戶(hù)在使用Algoritmia軟件,也可以選擇性的使用手動(dòng)上色功能哦。

        Algoritmia中文版應(yīng)用功能:

        可手動(dòng)調(diào)色

        可一鍵自動(dòng)化上色

        黑白照變彩色照非常逼真

        可將任意黑白照片添加色彩

        采用智能色彩識(shí)別調(diào)節(jié)技術(shù)

        Algoritmia英文詳情介紹:

        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]

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