image_valid Examples#

This document contains JSON examples for image_valid metadata layouts.

missing_version#

 1{
 2    "@type": "ngff:Image",
 3    "multiscales": [
 4        {
 5            "name": "example",
 6            "datasets": [
 7                {
 8                    "path": "path/to/0"
 9                }
10            ],
11            "axes": [
12                "z",
13                "y",
14                "x"
15            ]
16        }
17    ]
18}

image_omero#

 1{
 2    "@id": "#my-image",
 3    "@type": "ngff:Image",
 4    "multiscales": [
 5        {
 6            "@id": "#my-pyramid",
 7            "version": "0.3",
 8            "name": "example",
 9            "datasets": [
10                {
11                    "path": "path/to/0"
12                },
13                {
14                    "path": "1"
15                },
16                {
17                    "path": "2"
18                }
19            ],
20            "type": "gaussian",
21            "metadata": {
22                "method": "skimage.transform.pyramid_gaussian",
23                "version": "0.16.1",
24                "args": [
25                    "true",
26                    "false"
27                ],
28                "kwargs": {
29                    "multichannel": true
30                }
31            },
32            "axes": [
33                "z",
34                "y",
35                "x"
36            ]
37        }
38    ],
39    "omero": {
40        "id": 1,
41        "version": "0.3",
42        "channels": [
43            {
44                "active": true,
45                "color": "0000FF",
46                "family": "linear",
47                "inverted": false,
48                "label": "1234",
49                "window": {
50                    "end": 1765.0,
51                    "max": 2555.0,
52                    "min": 5.0,
53                    "start": 0.0
54                }
55            }
56        ],
57        "rdefs": {
58            "defaultZ": 0,
59            "defaultT": 0,
60            "model": "color"
61        }
62    }
63}

missing_name#

 1{
 2    "@type": "ngff:Image",
 3    "multiscales": [
 4        {
 5            "version": "0.3",
 6            "datasets": [
 7                {
 8                    "path": "path/to/0"
 9                }
10            ],
11            "type": "gaussian",
12            "metadata": {
13                "method": "skimage.transform.pyramid_gaussian",
14                "version": "0.16.1",
15                "args": [
16                    "true",
17                    "false"
18                ],
19                "kwargs": {
20                    "multichannel": true
21                }
22            },
23            "axes": [
24                "z",
25                "y",
26                "x"
27            ]
28        }
29    ]
30}

image_metadata#

 1{
 2    "@id": "top",
 3    "@type": "ngff:Image",
 4    "multiscales": [
 5        {
 6            "@id": "inner",
 7            "version": "0.3",
 8            "name": "example",
 9            "datasets": [
10                {
11                    "path": "path/to/0"
12                }
13            ],
14            "type": "gaussian",
15            "metadata": {
16                "method": "skimage.transform.pyramid_gaussian",
17                "version": "0.16.1",
18                "args": [
19                    "true",
20                    "false"
21                ],
22                "kwargs": {
23                    "multichannel": true
24                }
25            },
26            "axes": [
27                "z",
28                "y",
29                "x"
30            ]
31        }
32    ]
33}

image#

 1{
 2    "@type": "ngff:Image",
 3    "multiscales": [
 4        {
 5            "datasets": [
 6                {"path": "path/to/0"},
 7                {"path": "1"},
 8                {"path": "2"}
 9            ],
10            "axes": [
11                "z", "y", "x"
12            ]
13        }
14    ]
15}