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Data formats
This document describes the various data formats that are used in the system.
Raw annotation data
The client sends raw data for image annotations in a JSON format which is a list of shapes. Each shape is a dictionary with the following keys:
type: The type of the shape which can be:bbox(bounding box, rectangle)polygonpolylinepoint
shape: The shape data. Its format depends on the shapetype:For
bboxit is a dictionary with keys x, y, w, h: ~json {"x": x, "y": y, "w": w, "h": h}~For
polygonandpolylineit is a list of points; each point is a dictionary with keys x and y: ~json [{"x": x1, "y": y1}, {"x": x2, "y": y2}, ...]~ The only difference betweenpolygonandpolylineis that the former is supposed to be closed so the last point is connected to the first one.For
pointit is a dictionary with keys x and y: ~json {"x": x, "y": y}~All coordinates are floating-point numbers in the range [0, 1] and relative to the image size, with the origin in the top-left corner.
object: The ID of the type of object (label) depicted in the shape. This ID is a human-readable string that must be registered in the system before being used on shapes.
The server sends the same data back to the client, to use to show the existing annotations for an image.
Example
[
{
"type": "bbox",
"shape": {"x": 0.1, "y": 0.1, "w": 0.5, "h": 0.5},
"object": "Cat (Felis catus)"
},
{
"type": "polygon",
"shape": [{"x": 0, "y": 0}, {"x": 1, "y": 0}, {"x": 0, "y": 1}],
"object": "Slice of pizza margherita"
},
{
"type": "point",
"shape": {"x": 0.5, "y": 0.5},
"object": "Cat (Felis catus) - left eye"
}
]
Query format
The query format is based on YAML and used to query for pictures in the system.
Structure
The root can have 3 keys:
want: A list of rules that the images must satisfy. If not provided, no filtering is done.exclude: A list of rules that the images must not satisfy. If not provided, no filtering is done.include_obsolete: If true the query may return images with a designated replacement. If false (default) this won't be possible.
want and exclude are lists of rules. Each rule is a dictionary with a single
key (this is to allow multiple rules of the same kind). Accepted rules are:
has_object: [object1, object2, ...]: The image must contain any of the objects in the list.nature: [nature1, nature2, ...]: The image must have one of the natures in the list. Natures are strings like "photo" that indicate the source of the image.licence: [licence1, licence2, ...]: The image must have one of the licences in the list. If possible, licence IDs are SPDX identifiers, non-standard ones are prefixed withX-.author: [author1, author2, ...]: The image's author's username must be in the list.title: query: Search for titles (ilike).description: query: Search for descriptions (ilike).origin_url: query: Search for origin URLs. The query matches the beginning of the URL excluding the protocol. (likecommons.wikimedia.org)above_width: width: The image must have a width greater than or equal to the given value, in pixels.above_height: height: The image must have a height greater than or equal to the given value, in pixels.below_width: width: The image must have a width less than or equal to the given value, in pixels.below_height: height: The image must have a height less than or equal to the given value, in pixels.before_date: timestamp: The image must have been uploaded before the given Unix timestamp.after_date: timestamp: The image must have been uploaded after the given Unix timestamp.in_gallery: [gallery1, gallery2, ...]: The image must be in any of the galleries (by ID) in the list.
ordering, offset and limit can be specified as query parameters in the
URL. ordering can be one of date-desc, date-asc, title-asc, title-desc,
number-regions-desc, number-regions-asc, random. offset and limit are
integers that specify the number of images to skip and the maximum number of
images to return, respectively.
Example
# Restrictions for queried images
want:
# This means that the image must contain both rules, so both a cat and a dog
- has_object: ["Cat (Felis catus)"]
- has_object: ["Dog (Canis lupus familiaris)"]
# Or we can put them in a list to mean that the image can contain any of the
# objects in the list
- has_object: ["Grass", "Flower"]
# So the image must contain a cat and a dog, as well as either grass or
# a flower
# The following rule restricts the images to those with a certain source,
# like a camera or a drawing; omitting this rule means that the images can
# be of any source
- nature: ["photo", "computer-3d-art"]
# The following rule restricts the images to those with a certain licence
- licence: ["CC-BY-1.0", "CC-BY-2.0", "CC-BY-3.0", "CC-BY-4.0", "CC0-1.0",
"Unlicense", "WTFPL", "MIT", "BSD-2-Clause", "BSD-3-Clause",
"Apache-2.0", "X-informal-attribution", "X-informal-do-anything",
"X-public-domain-old", "X-public-domain"]
# Prohibitions for queried images
exclude:
# This means that the image must not contain any of the objects in the list
- has_object: ["Human"]
# This excludes images uploaded before the given date
- before_date: 1546300800
# This requires images to have a minimum resolution
- below_width: 800
- below_height: 600
# In summary, we want images that contain both a cat and a dog, either a grass
# or a flower, but not a human, taken after 2019-01-01, must be a photo or a
# 3D render, must carry one of certain permissive licences and have a resolution
# of at least 800x600 pixels.
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Data formats
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============
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This document describes the various data formats that are used in the system.
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Raw annotation data
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-------------------
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The client sends raw data for image annotations in a JSON format which is a list
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of shapes. Each shape is a dictionary with the following keys:
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* `type`: The type of the shape which can be:
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* `bbox` (bounding box, rectangle)
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* `polygon`
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* `polyline`
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* `point`
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* `shape`: The shape data. Its format depends on the shape `type`:
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* For `bbox` it is a dictionary with keys x, y, w, h:
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~~~json
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{"x": x, "y": y, "w": w, "h": h}
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~~~
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* For `polygon` and `polyline` it is a list of points; each point is a
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dictionary with keys x and y:
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~~~json
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[{"x": x1, "y": y1}, {"x": x2, "y": y2}, ...]
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~~~
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The only difference between `polygon` and `polyline` is that the former is
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supposed to be closed so the last point is connected to the first one.
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* For `point` it is a dictionary with keys x and y:
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~~~json
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{"x": x, "y": y}
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~~~
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* All coordinates are floating-point numbers in the range [0, 1] and relative
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to the image size, with the origin in the top-left corner.
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* `object`: The ID of the type of object (label) depicted in the shape. This ID
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is a human-readable string that must be registered in the system before
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being used on shapes.
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The server sends the same data back to the client, to use to show the existing
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annotations for an image.
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### Example
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~~~json
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[
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{
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"type": "bbox",
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"shape": {"x": 0.1, "y": 0.1, "w": 0.5, "h": 0.5},
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"object": "Cat (Felis catus)"
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},
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{
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"type": "polygon",
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"shape": [{"x": 0, "y": 0}, {"x": 1, "y": 0}, {"x": 0, "y": 1}],
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"object": "Slice of pizza margherita"
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},
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{
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"type": "point",
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"shape": {"x": 0.5, "y": 0.5},
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"object": "Cat (Felis catus) - left eye"
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}
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]
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~~~
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Query format
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------------
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The query format is based on YAML and used to query for pictures in the system.
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### Structure
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The root can have 3 keys:
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* `want`: A list of rules that the images must satisfy. If not provided, no
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filtering is done.
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* `exclude`: A list of rules that the images must not satisfy. If not provided,
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no filtering is done.
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* `include_obsolete`: If true the query may return images with a designated
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replacement. If false (default) this won't be possible.
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`want` and `exclude` are lists of rules. Each rule is a dictionary with a single
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key (this is to allow multiple rules of the same kind). Accepted rules are:
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* `has_object: [object1, object2, ...]`: The image must contain any of the
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objects in the list.
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* `nature: [nature1, nature2, ...]`: The image must have one of the natures in
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the list. Natures are strings like "photo" that indicate the source of the
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image.
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* `licence: [licence1, licence2, ...]`: The image must have one of the licences
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in the list. If possible, licence IDs are SPDX identifiers, non-standard ones
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are prefixed with `X-`.
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* `author: [author1, author2, ...]`: The image's author's username must be in
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the list.
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* `title: query`: Search for titles (`ilike`).
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* `description: query`: Search for descriptions (`ilike`).
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* `origin_url: query`: Search for origin URLs. The query matches the beginning
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of the URL excluding the protocol. (like `commons.wikimedia.org`)
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* `above_width: width`: The image must have a width greater than or equal to
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the given value, in pixels.
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* `above_height: height`: The image must have a height greater than or equal to
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the given value, in pixels.
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* `below_width: width`: The image must have a width less than or equal to the
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given value, in pixels.
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* `below_height: height`: The image must have a height less than or equal to the
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given value, in pixels.
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* `before_date: timestamp`: The image must have been uploaded before the given
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Unix timestamp.
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* `after_date: timestamp`: The image must have been uploaded after the given
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Unix timestamp.
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* `in_gallery: [gallery1, gallery2, ...]`: The image must be in any of the
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galleries (by ID) in the list.
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`ordering`, `offset` and `limit` can be specified as query parameters in the
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URL. `ordering` can be one of `date-desc`, `date-asc`, `title-asc`, `title-desc`,
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`number-regions-desc`, `number-regions-asc`, `random`. `offset` and `limit` are
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integers that specify the number of images to skip and the maximum number of
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images to return, respectively.
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### Example
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~~~yaml
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# Restrictions for queried images
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want:
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# This means that the image must contain both rules, so both a cat and a dog
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- has_object: ["Cat (Felis catus)"]
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- has_object: ["Dog (Canis lupus familiaris)"]
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# Or we can put them in a list to mean that the image can contain any of the
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# objects in the list
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- has_object: ["Grass", "Flower"]
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# So the image must contain a cat and a dog, as well as either grass or
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# a flower
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# The following rule restricts the images to those with a certain source,
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# like a camera or a drawing; omitting this rule means that the images can
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# be of any source
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- nature: ["photo", "computer-3d-art"]
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# The following rule restricts the images to those with a certain licence
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- licence: ["CC-BY-1.0", "CC-BY-2.0", "CC-BY-3.0", "CC-BY-4.0", "CC0-1.0",
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"Unlicense", "WTFPL", "MIT", "BSD-2-Clause", "BSD-3-Clause",
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"Apache-2.0", "X-informal-attribution", "X-informal-do-anything",
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"X-public-domain-old", "X-public-domain"]
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# Prohibitions for queried images
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exclude:
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# This means that the image must not contain any of the objects in the list
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- has_object: ["Human"]
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# This excludes images uploaded before the given date
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- before_date: 1546300800
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# This requires images to have a minimum resolution
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- below_width: 800
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- below_height: 600
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# In summary, we want images that contain both a cat and a dog, either a grass
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# or a flower, but not a human, taken after 2019-01-01, must be a photo or a
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# 3D render, must carry one of certain permissive licences and have a resolution
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# of at least 800x600 pixels.
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~~~
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