[
    {
        "Variant name": "main",
        "Reviewer name": "David Coeurjolly <david.coeurjolly@liris.cnrs.fr>",
        "Is master variant (boolean)": true,
        "Is variant deprecated (boolean)": false,
        "Title": "Multi-Scale Label-Map Extraction for Texture Synthesis",
        "DOI": "10.1145/2897824.2925964",
        "Year": 2016,
        "ACM Keywords": [
            "Image processing",
            "Texturing"
        ],
        "Topic {Rendering, Animation and Simulation, Geometry, Images, Virtual Reality, Fabrication}": "Images",
        "Co-authors from academia (boolean)": true,
        "Co-authors from industry (boolean)": false,
        "ACM Open Access (boolean)": false,
        "PDF on the authors' webpage / institution (boolean)": true,
        "PDF URL": "https://graphics.cs.yale.edu/sites/default/files/multi-scale_label-map_extraction_for_texture_synthesis.pdf",
        "PDF on Arxiv or any openarchive initiatives (boolean)": false,
        "Arxiv/OAI page URL": "",
        "Project URL": "https://graphics.cs.yale.edu/publications/multi-scale-label-map-extraction-texture-synthesis",
        "Code available (boolean)": true,
        "If code not available, pseudo-code available (boolean)": false,
        "If pseudo-code, could the paper be trivially implemented? {0..4}": "",
        "Code URL": "https://github.com/ylockerman/multi-scale-label-map-extraction/",
        "Code URL2": "",
        "MD5 sum (for archives)": "",
        "git/hg/svn commit hash or revision number": "adde38ce238e48075e049971f6031412aaaab0b2",
        "MD5 sum (for archives) URL2": "",
        "git/hg/svn commit hash or revision number URL2": "",
        "Software Heritage permalink": "https://archive.softwareheritage.org/swh:1:dir:e9cc85c35030f07ccd9f4c27a6a73627a54b4c6b;origin=https://github.com/ylockerman/multi-scale-label-map-extraction/",
        "Software type {Code, Binary, Partial Code}": "Code",
        "Code License (if any)": "MIT",
        "Are the code authors explicit? (boolean)": true,
        "Build/Configure mechanism": "CMakeLists, Not applicable (python, Matlab..)",
        "Dependencies": "numpy/scipy/bottleneck/joblib/Mako/msgpack_python/pyamg / pyopencl/pytools/scikit-image/matplotlib/scikit-learn",
        "Does the software require paywall/proprietary software/material (boolean)?": false,
        "Does the code need data (not examples) (boolean)": false,
        "Nature of the data (pretrained model, LUT...)": "",
        "License of the data": "",
        "Able to perform a replicability test (boolean)": true,
        "If not able to perform a test, was it due to missing hardware/software? (boolean)": false,
        "Documentation score {0=NA,1,2,3}": 0,
        "Dependencies score {0=NA, 1,2,3,4,5}": 5,
        "Build/configure score {0=NA, 1,2,3,4,5}": 2,
        "Fixing bugs score (if any) {0=NA, 1,2,3,4,5}": 0,
        "Replicate paper results score {0=NA, 1,2,3,4,5}": 0,
        "Adaptability score to other contexts {0=NA, 1,2,3,4,5}": 0,
        "Time spent for the test (code download to first successful run, [0,10], 10min slots, 100min max)": 3,
        "Operating system for the test": "Mac OS",
        "Build instructions/comments": "No explanations are given to build/execute the code. After installing the dependencies, I have tried to run an example in the 'src' folder:\n\npython ../examples/SLIC_compare.py\n\nwhich crashes due to opencl/Tk issues.",
        "Misc. comments": "",
        "Software language": "C/C++, Python"
    }
]