metadata.json

{
    "title": "Apple tree blossom image segmentation",
    "summary": "We suggest a 2D image segmentation model based on UNET algorithm to segment images with blossoming apple tree",
    "description": [
		"Apple flowers are very sensitive to temperature",
           "The study of their development makes it possible to study climate change.",
           "This module proposes a model for the segmentation of apple blossom images.",
           "This model is based on the UNET algorithm.",
           "We suggest a tool for inference of images and a tool for retrain a model",
           "The model in inference and retraining is tensorflow model in h5 format."
	],
    "keywords": [
        "tensorflow",
        "trainable", 
        "inference", 
        "pre-trained",
        "deep learning",
        "docker",
        "api-v2"
    ],
    "license": "MIT",
    "date_creation": "2022-07-26",
    "sources": {
		"dockerfile_repo": "https://github.com/hereariim/DEEP-OC-blossom",
		"docker_registry_repo": "deephdc/uc-hereariim-deep-oc-blossom",
		"code": "https://github.com/hereariim/blossom",
        "pre_trained_weights": "https://github.com/hereariim/blossom/tree/master/blossom/models"
	},
    "continuous_integration": {
        "build_status_badge": "https://jenkins.indigo-datacloud.eu/buildStatus/icon?job=Pipeline-as-code/DEEP-OC-org/UC-hereariim-DEEP-OC-blossom/master",
        "build_status_url": "https://jenkins.indigo-datacloud.eu/job/Pipeline-as-code/job/DEEP-OC-org/job/UC-hereariim-DEEP-OC-blossom/job/master"
    },
    "tosca": [
        {
            "title": "Mesos (CPU)",
            "url": "https://raw.githubusercontent.com/indigo-dc/tosca-templates/master/deep-oc/deep-oc-marathon-webdav.yml",
            "inputs": [
                "rclone_conf",
                "rclone_url",
                "rclone_vendor",
                "rclone_user",
                "rclone_pass"
            ]
        }
    ]
}