metadata.json

{
    "title": "2D semantic segmentation",
    "summary": "2D semantic segmentation trained on the Vaihingen dataset",
    "description": [
	   "Example application for ISPRS 2D Semantic Labeling Contest [1]:\n",
           "2D semantic segmentation (Vaihingen dataset [2]) that assigns labels to multiple object categories.\n\n",
           "**Vaihingen dataset**\n",
           "* 33 patches of different sizes with 9 cm spatial resolution",
           "* Manually classified into six land cover classes:",
           "* Impervious surfaces, Building, Low vegetation, Tree, Clutter/background",
           "* The groundtruth is provided for only 16 patches",
           "* For the remaining scenes it is unreleased and used for evaluation of submitted results",
           "",
           "**N.B.:** pre-trained weights can be found <a href=https://nc.deep-hybrid-datacloud.eu/s/eTqJexZ5PcBxXR6>here</a> (unzip before use!)",
           "",
           "**References**\n",
           "[1] <a href=http://www2.isprs.org/commissions/comm3/wg4/semantic-labeling.html>http://www2.isprs.org/commissions/comm3/wg4/semantic-labeling.html</a> \n",
           "[2] M. Cramer: The DGPF-Test on Digital Airborne Camera Evaluation Overview and Test Design, ",
                "PFG Photogrammetrie, Fernerkundung, Geoinformation, vol. 2010, no. 2, pp. 73-82, 2010.\n"
	],
    "keywords": [
        "tensorflow",
        "semantic segmentation",
        "cnn",
        "trainable",
        "inference",
        "pre-trained",
        "api-v2",
        "image"
    ],
    "license": "MIT",
    "date_creation": "2019-09-29",
    "dataset_url": "http://www2.isprs.org/commissions/comm3/wg4/2d-sem-label-vaihingen.html",
    "sources": {
		"dockerfile_repo": "https://github.com/deephdc/DEEP-OC-semseg_vaihingen",
		"docker_registry_repo": "deephdc/deep-oc-semseg_vaihingen",
		"code": "https://github.com/deephdc/semseg_vaihingen"
	},
    "continuous_integration": {
        "build_status_badge": "https://jenkins.indigo-datacloud.eu/buildStatus/icon?job=Pipeline-as-code/DEEP-OC-org/DEEP-OC-semseg_vaihingen/master",
        "build_status_url": "https://jenkins.indigo-datacloud.eu/job/Pipeline-as-code/job/DEEP-OC-org/job/DEEP-OC-semseg_vaihingen/job/master"
    },
    "tosca": [
        {
            "title": "Marathon",
            "url": "https://raw.githubusercontent.com/indigo-dc/tosca-templates/master/deep-oc/deep-oc-marathon.yml",
            "inputs": [
                "rclone_conf",
                "rclone_url",
                "rclone_vendor",
                "rclone_user",
                "rclone_pass"
            ]
        }
    ]
}