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75<h1><a href="vision_v1.html">Google Cloud Vision API</a> . <a href="vision_v1.images.html">images</a></h1>
76<h2>Instance Methods</h2>
77<p class="toc_element">
78 <code><a href="#annotate">annotate(body, x__xgafv=None)</a></code></p>
79<p class="firstline">Run image detection and annotation for a batch of images.</p>
80<h3>Method Details</h3>
81<div class="method">
82 <code class="details" id="annotate">annotate(body, x__xgafv=None)</code>
83 <pre>Run image detection and annotation for a batch of images.
84
85Args:
86 body: object, The request body. (required)
87 The object takes the form of:
88
89{ # Multiple image annotation requests are batched into a single service call.
90 "requests": [ # Individual image annotation requests for this batch.
91 { # Request for performing Google Cloud Vision API tasks over a user-provided
92 # image, with user-requested features.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]93 "imageContext": { # Image context and/or feature-specific parameters. # Additional context that may accompany the image.
94 "latLongRect": { # Rectangle determined by min and max `LatLng` pairs. # lat/long rectangle that specifies the location of the image.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]95 "minLatLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # Min lat/long pair.
96 # of doubles representing degrees latitude and degrees longitude. Unless
97 # specified otherwise, this must conform to the
98 # <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84
99 # standard</a>. Values must be within normalized ranges.
100 #
101 # Example of normalization code in Python:
102 #
103 # def NormalizeLongitude(longitude):
104 # """Wraps decimal degrees longitude to [-180.0, 180.0]."""
105 # q, r = divmod(longitude, 360.0)
106 # if r > 180.0 or (r == 180.0 and q <= -1.0):
107 # return r - 360.0
108 # return r
109 #
110 # def NormalizeLatLng(latitude, longitude):
111 # """Wraps decimal degrees latitude and longitude to
112 # [-90.0, 90.0] and [-180.0, 180.0], respectively."""
113 # r = latitude % 360.0
114 # if r <= 90.0:
115 # return r, NormalizeLongitude(longitude)
116 # elif r >= 270.0:
117 # return r - 360, NormalizeLongitude(longitude)
118 # else:
119 # return 180 - r, NormalizeLongitude(longitude + 180.0)
120 #
121 # assert 180.0 == NormalizeLongitude(180.0)
122 # assert -180.0 == NormalizeLongitude(-180.0)
123 # assert -179.0 == NormalizeLongitude(181.0)
124 # assert (0.0, 0.0) == NormalizeLatLng(360.0, 0.0)
125 # assert (0.0, 0.0) == NormalizeLatLng(-360.0, 0.0)
126 # assert (85.0, 180.0) == NormalizeLatLng(95.0, 0.0)
127 # assert (-85.0, -170.0) == NormalizeLatLng(-95.0, 10.0)
128 # assert (90.0, 10.0) == NormalizeLatLng(90.0, 10.0)
129 # assert (-90.0, -10.0) == NormalizeLatLng(-90.0, -10.0)
130 # assert (0.0, -170.0) == NormalizeLatLng(-180.0, 10.0)
131 # assert (0.0, -170.0) == NormalizeLatLng(180.0, 10.0)
132 # assert (-90.0, 10.0) == NormalizeLatLng(270.0, 10.0)
133 # assert (90.0, 10.0) == NormalizeLatLng(-270.0, 10.0)
134 "latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
135 "longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
136 },
137 "maxLatLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # Max lat/long pair.
138 # of doubles representing degrees latitude and degrees longitude. Unless
139 # specified otherwise, this must conform to the
140 # <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84
141 # standard</a>. Values must be within normalized ranges.
142 #
143 # Example of normalization code in Python:
144 #
145 # def NormalizeLongitude(longitude):
146 # """Wraps decimal degrees longitude to [-180.0, 180.0]."""
147 # q, r = divmod(longitude, 360.0)
148 # if r > 180.0 or (r == 180.0 and q <= -1.0):
149 # return r - 360.0
150 # return r
151 #
152 # def NormalizeLatLng(latitude, longitude):
153 # """Wraps decimal degrees latitude and longitude to
154 # [-90.0, 90.0] and [-180.0, 180.0], respectively."""
155 # r = latitude % 360.0
156 # if r <= 90.0:
157 # return r, NormalizeLongitude(longitude)
158 # elif r >= 270.0:
159 # return r - 360, NormalizeLongitude(longitude)
160 # else:
161 # return 180 - r, NormalizeLongitude(longitude + 180.0)
162 #
163 # assert 180.0 == NormalizeLongitude(180.0)
164 # assert -180.0 == NormalizeLongitude(-180.0)
165 # assert -179.0 == NormalizeLongitude(181.0)
166 # assert (0.0, 0.0) == NormalizeLatLng(360.0, 0.0)
167 # assert (0.0, 0.0) == NormalizeLatLng(-360.0, 0.0)
168 # assert (85.0, 180.0) == NormalizeLatLng(95.0, 0.0)
169 # assert (-85.0, -170.0) == NormalizeLatLng(-95.0, 10.0)
170 # assert (90.0, 10.0) == NormalizeLatLng(90.0, 10.0)
171 # assert (-90.0, -10.0) == NormalizeLatLng(-90.0, -10.0)
172 # assert (0.0, -170.0) == NormalizeLatLng(-180.0, 10.0)
173 # assert (0.0, -170.0) == NormalizeLatLng(180.0, 10.0)
174 # assert (-90.0, 10.0) == NormalizeLatLng(270.0, 10.0)
175 # assert (90.0, 10.0) == NormalizeLatLng(-270.0, 10.0)
176 "latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
177 "longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
178 },
179 },
180 "languageHints": [ # List of languages to use for TEXT_DETECTION. In most cases, an empty value
Jon Wayne Parrott7d5badb2016-08-16 12:44:29 -0700[diff] [blame]181 # yields the best results since it enables automatic language detection. For
182 # languages based on the Latin alphabet, setting `language_hints` is not
183 # needed. In rare cases, when the language of the text in the image is known,
184 # setting a hint will help get better results (although it will be a
185 # significant hindrance if the hint is wrong). Text detection returns an
186 # error if one or more of the specified languages is not one of the
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]187 # [supported languages](/vision/docs/languages).
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]188 "A String",
189 ],
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]190 "cropHintsParams": { # Parameters for crop hints annotation request. # Parameters for crop hints annotation request.
191 "aspectRatios": [ # Aspect ratios in floats, representing the ratio of the width to the height
192 # of the image. For example, if the desired aspect ratio is 4/3, the
193 # corresponding float value should be 1.33333. If not specified, the
194 # best possible crop is returned. The number of provided aspect ratios is
195 # limited to a maximum of 16; any aspect ratios provided after the 16th are
196 # ignored.
197 3.14,
198 ],
199 },
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]200 },
201 "image": { # Client image to perform Google Cloud Vision API tasks over. # The image to be processed.
202 "content": "A String", # Image content, represented as a stream of bytes.
Jon Wayne Parrott7d5badb2016-08-16 12:44:29 -0700[diff] [blame]203 # Note: as with all `bytes` fields, protobuffers use a pure binary
204 # representation, whereas JSON representations use base64.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]205 "source": { # External image source (Google Cloud Storage image location). # Google Cloud Storage image location. If both `content` and `source`
206 # are provided for an image, `content` takes precedence and is
207 # used to perform the image annotation request.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]208 "gcsImageUri": "A String", # NOTE: For new code `image_uri` below is preferred.
209 # Google Cloud Storage image URI, which must be in the following form:
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]210 # `gs://bucket_name/object_name` (for details, see
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]211 # [Google Cloud Storage Request
212 # URIs](https://cloud.google.com/storage/docs/reference-uris)).
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]213 # NOTE: Cloud Storage object versioning is not supported.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]214 "imageUri": "A String", # Image URI which supports:
215 # 1) Google Cloud Storage image URI, which must be in the following form:
216 # `gs://bucket_name/object_name` (for details, see
217 # [Google Cloud Storage Request
218 # URIs](https://cloud.google.com/storage/docs/reference-uris)).
219 # NOTE: Cloud Storage object versioning is not supported.
220 # 2) Publicly accessible image HTTP/HTTPS URL.
221 # This is preferred over the legacy `gcs_image_uri` above. When both
222 # `gcs_image_uri` and `image_uri` are specified, `image_uri` takes
223 # precedence.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]224 },
225 },
226 "features": [ # Requested features.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]227 { # Users describe the type of Google Cloud Vision API tasks to perform over
228 # images by using *Feature*s. Each Feature indicates a type of image
229 # detection task to perform. Features encode the Cloud Vision API
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]230 # vertical to operate on and the number of top-scoring results to return.
231 "type": "A String", # The feature type.
232 "maxResults": 42, # Maximum number of results of this type.
233 },
234 ],
235 },
236 ],
237 }
238
239 x__xgafv: string, V1 error format.
240 Allowed values
241 1 - v1 error format
242 2 - v2 error format
243
244Returns:
245 An object of the form:
246
247 { # Response to a batch image annotation request.
248 "responses": [ # Individual responses to image annotation requests within the batch.
249 { # Response to an image annotation request.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]250 "safeSearchAnnotation": { # Set of features pertaining to the image, computed by computer vision # If present, safe-search annotation has completed successfully.
251 # methods over safe-search verticals (for example, adult, spoof, medical,
252 # violence).
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame^]253 "medical": "A String", # Likelihood that this is a medical image.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]254 "spoof": "A String", # Spoof likelihood. The likelihood that an modification
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]255 # was made to the image's canonical version to make it appear
256 # funny or offensive.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]257 "violence": "A String", # Violence likelihood.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]258 "adult": "A String", # Represents the adult content likelihood for the image.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]259 },
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]260 "textAnnotations": [ # If present, text (OCR) detection has completed successfully.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]261 { # Set of detected entity features.
262 "confidence": 3.14, # The accuracy of the entity detection in an image.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]263 # For example, for an image in which the "Eiffel Tower" entity is detected,
264 # this field represents the confidence that there is a tower in the query
265 # image. Range [0, 1].
266 "description": "A String", # Entity textual description, expressed in its `locale` language.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]267 "locale": "A String", # The language code for the locale in which the entity textual
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]268 # `description` is expressed.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]269 "topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]270 # image. For example, the relevancy of "tower" is likely higher to an image
271 # containing the detected "Eiffel Tower" than to an image containing a
272 # detected distant towering building, even though the confidence that
273 # there is a tower in each image may be the same. Range [0, 1].
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame^]274 "mid": "A String", # Opaque entity ID. Some IDs may be available in
275 # [Google Knowledge Graph Search API](https://developers.google.com/knowledge-graph/).
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]276 "locations": [ # The location information for the detected entity. Multiple
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]277 # `LocationInfo` elements can be present because one location may
278 # indicate the location of the scene in the image, and another location
279 # may indicate the location of the place where the image was taken.
280 # Location information is usually present for landmarks.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]281 { # Detected entity location information.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]282 "latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]283 # of doubles representing degrees latitude and degrees longitude. Unless
284 # specified otherwise, this must conform to the
285 # <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84
286 # standard</a>. Values must be within normalized ranges.
287 #
288 # Example of normalization code in Python:
289 #
290 # def NormalizeLongitude(longitude):
291 # """Wraps decimal degrees longitude to [-180.0, 180.0]."""
292 # q, r = divmod(longitude, 360.0)
293 # if r > 180.0 or (r == 180.0 and q <= -1.0):
294 # return r - 360.0
295 # return r
296 #
297 # def NormalizeLatLng(latitude, longitude):
298 # """Wraps decimal degrees latitude and longitude to
299 # [-90.0, 90.0] and [-180.0, 180.0], respectively."""
300 # r = latitude % 360.0
301 # if r <= 90.0:
302 # return r, NormalizeLongitude(longitude)
303 # elif r >= 270.0:
304 # return r - 360, NormalizeLongitude(longitude)
305 # else:
306 # return 180 - r, NormalizeLongitude(longitude + 180.0)
307 #
308 # assert 180.0 == NormalizeLongitude(180.0)
309 # assert -180.0 == NormalizeLongitude(-180.0)
310 # assert -179.0 == NormalizeLongitude(181.0)
311 # assert (0.0, 0.0) == NormalizeLatLng(360.0, 0.0)
312 # assert (0.0, 0.0) == NormalizeLatLng(-360.0, 0.0)
313 # assert (85.0, 180.0) == NormalizeLatLng(95.0, 0.0)
314 # assert (-85.0, -170.0) == NormalizeLatLng(-95.0, 10.0)
315 # assert (90.0, 10.0) == NormalizeLatLng(90.0, 10.0)
316 # assert (-90.0, -10.0) == NormalizeLatLng(-90.0, -10.0)
317 # assert (0.0, -170.0) == NormalizeLatLng(-180.0, 10.0)
318 # assert (0.0, -170.0) == NormalizeLatLng(180.0, 10.0)
319 # assert (-90.0, 10.0) == NormalizeLatLng(270.0, 10.0)
320 # assert (90.0, 10.0) == NormalizeLatLng(-270.0, 10.0)
321 "latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
322 "longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
323 },
324 },
325 ],
326 "score": 3.14, # Overall score of the result. Range [0, 1].
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]327 "boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Currently not produced
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]328 # for `LABEL_DETECTION` features. For `TEXT_DETECTION` (OCR), `boundingPoly`s
329 # are produced for the entire text detected in an image region, followed by
330 # `boundingPoly`s for each word within the detected text.
331 "vertices": [ # The bounding polygon vertices.
332 { # A vertex represents a 2D point in the image.
333 # NOTE: the vertex coordinates are in the same scale as the original image.
334 "y": 42, # Y coordinate.
335 "x": 42, # X coordinate.
336 },
337 ],
338 },
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]339 "properties": [ # Some entities may have optional user-supplied `Property` (name/value)
340 # fields, such a score or string that qualifies the entity.
341 { # A `Property` consists of a user-supplied name/value pair.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]342 "uint64Value": "A String", # Value of numeric properties.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]343 "name": "A String", # Name of the property.
344 "value": "A String", # Value of the property.
345 },
346 ],
347 },
348 ],
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]349 "webDetection": { # Relevant information for the image from the Internet. # If present, web detection has completed successfully.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]350 "webEntities": [ # Deduced entities from similar images on the Internet.
351 { # Entity deduced from similar images on the Internet.
352 "entityId": "A String", # Opaque entity ID.
353 "score": 3.14, # Overall relevancy score for the entity.
354 # Not normalized and not comparable across different image queries.
355 "description": "A String", # Canonical description of the entity, in English.
356 },
357 ],
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]358 "pagesWithMatchingImages": [ # Web pages containing the matching images from the Internet.
359 { # Metadata for web pages.
360 "url": "A String", # The result web page URL.
361 "score": 3.14, # Overall relevancy score for the web page.
362 # Not normalized and not comparable across different image queries.
363 },
364 ],
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]365 "visuallySimilarImages": [ # The visually similar image results.
366 { # Metadata for online images.
367 "url": "A String", # The result image URL.
368 "score": 3.14, # Overall relevancy score for the image.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]369 # Not normalized and not comparable across different image queries.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]370 },
371 ],
372 "partialMatchingImages": [ # Partial matching images from the Internet.
373 # Those images are similar enough to share some key-point features. For
374 # example an original image will likely have partial matching for its crops.
375 { # Metadata for online images.
376 "url": "A String", # The result image URL.
377 "score": 3.14, # Overall relevancy score for the image.
378 # Not normalized and not comparable across different image queries.
379 },
380 ],
381 "fullMatchingImages": [ # Fully matching images from the Internet.
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame^]382 # Can include resized copies of the query image.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]383 { # Metadata for online images.
384 "url": "A String", # The result image URL.
385 "score": 3.14, # Overall relevancy score for the image.
386 # Not normalized and not comparable across different image queries.
387 },
388 ],
389 },
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame^]390 "fullTextAnnotation": { # TextAnnotation contains a structured representation of OCR extracted text. # If present, text (OCR) detection or document (OCR) text detection has
391 # completed successfully.
392 # This annotation provides the structural hierarchy for the OCR detected
393 # text.
394 # The hierarchy of an OCR extracted text structure is like this:
395 # TextAnnotation -> Page -> Block -> Paragraph -> Word -> Symbol
396 # Each structural component, starting from Page, may further have their own
397 # properties. Properties describe detected languages, breaks etc.. Please
398 # refer to the google.cloud.vision.v1.TextAnnotation.TextProperty message
399 # definition below for more detail.
400 "text": "A String", # UTF-8 text detected on the pages.
401 "pages": [ # List of pages detected by OCR.
402 { # Detected page from OCR.
403 "width": 42, # Page width in pixels.
404 "property": { # Additional information detected on the structural component. # Additional information detected on the page.
405 "detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.
406 "isPrefix": True or False, # True if break prepends the element.
407 "type": "A String", # Detected break type.
408 },
409 "detectedLanguages": [ # A list of detected languages together with confidence.
410 { # Detected language for a structural component.
411 "languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
412 # information, see
413 # http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
414 "confidence": 3.14, # Confidence of detected language. Range [0, 1].
415 },
416 ],
417 },
418 "blocks": [ # List of blocks of text, images etc on this page.
419 { # Logical element on the page.
420 "boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the block.
421 # The vertices are in the order of top-left, top-right, bottom-right,
422 # bottom-left. When a rotation of the bounding box is detected the rotation
423 # is represented as around the top-left corner as defined when the text is
424 # read in the 'natural' orientation.
425 # For example:
426 # * when the text is horizontal it might look like:
427 # 0----1
428 # | |
429 # 3----2
430 # * when it's rotated 180 degrees around the top-left corner it becomes:
431 # 2----3
432 # | |
433 # 1----0
434 # and the vertice order will still be (0, 1, 2, 3).
435 "vertices": [ # The bounding polygon vertices.
436 { # A vertex represents a 2D point in the image.
437 # NOTE: the vertex coordinates are in the same scale as the original image.
438 "y": 42, # Y coordinate.
439 "x": 42, # X coordinate.
440 },
441 ],
442 },
443 "blockType": "A String", # Detected block type (text, image etc) for this block.
444 "property": { # Additional information detected on the structural component. # Additional information detected for the block.
445 "detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.
446 "isPrefix": True or False, # True if break prepends the element.
447 "type": "A String", # Detected break type.
448 },
449 "detectedLanguages": [ # A list of detected languages together with confidence.
450 { # Detected language for a structural component.
451 "languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
452 # information, see
453 # http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
454 "confidence": 3.14, # Confidence of detected language. Range [0, 1].
455 },
456 ],
457 },
458 "paragraphs": [ # List of paragraphs in this block (if this blocks is of type text).
459 { # Structural unit of text representing a number of words in certain order.
460 "boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the paragraph.
461 # The vertices are in the order of top-left, top-right, bottom-right,
462 # bottom-left. When a rotation of the bounding box is detected the rotation
463 # is represented as around the top-left corner as defined when the text is
464 # read in the 'natural' orientation.
465 # For example:
466 # * when the text is horizontal it might look like:
467 # 0----1
468 # | |
469 # 3----2
470 # * when it's rotated 180 degrees around the top-left corner it becomes:
471 # 2----3
472 # | |
473 # 1----0
474 # and the vertice order will still be (0, 1, 2, 3).
475 "vertices": [ # The bounding polygon vertices.
476 { # A vertex represents a 2D point in the image.
477 # NOTE: the vertex coordinates are in the same scale as the original image.
478 "y": 42, # Y coordinate.
479 "x": 42, # X coordinate.
480 },
481 ],
482 },
483 "property": { # Additional information detected on the structural component. # Additional information detected for the paragraph.
484 "detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.
485 "isPrefix": True or False, # True if break prepends the element.
486 "type": "A String", # Detected break type.
487 },
488 "detectedLanguages": [ # A list of detected languages together with confidence.
489 { # Detected language for a structural component.
490 "languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
491 # information, see
492 # http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
493 "confidence": 3.14, # Confidence of detected language. Range [0, 1].
494 },
495 ],
496 },
497 "words": [ # List of words in this paragraph.
498 { # A word representation.
499 "boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the word.
500 # The vertices are in the order of top-left, top-right, bottom-right,
501 # bottom-left. When a rotation of the bounding box is detected the rotation
502 # is represented as around the top-left corner as defined when the text is
503 # read in the 'natural' orientation.
504 # For example:
505 # * when the text is horizontal it might look like:
506 # 0----1
507 # | |
508 # 3----2
509 # * when it's rotated 180 degrees around the top-left corner it becomes:
510 # 2----3
511 # | |
512 # 1----0
513 # and the vertice order will still be (0, 1, 2, 3).
514 "vertices": [ # The bounding polygon vertices.
515 { # A vertex represents a 2D point in the image.
516 # NOTE: the vertex coordinates are in the same scale as the original image.
517 "y": 42, # Y coordinate.
518 "x": 42, # X coordinate.
519 },
520 ],
521 },
522 "symbols": [ # List of symbols in the word.
523 # The order of the symbols follows the natural reading order.
524 { # A single symbol representation.
525 "boundingBox": { # A bounding polygon for the detected image annotation. # The bounding box for the symbol.
526 # The vertices are in the order of top-left, top-right, bottom-right,
527 # bottom-left. When a rotation of the bounding box is detected the rotation
528 # is represented as around the top-left corner as defined when the text is
529 # read in the 'natural' orientation.
530 # For example:
531 # * when the text is horizontal it might look like:
532 # 0----1
533 # | |
534 # 3----2
535 # * when it's rotated 180 degrees around the top-left corner it becomes:
536 # 2----3
537 # | |
538 # 1----0
539 # and the vertice order will still be (0, 1, 2, 3).
540 "vertices": [ # The bounding polygon vertices.
541 { # A vertex represents a 2D point in the image.
542 # NOTE: the vertex coordinates are in the same scale as the original image.
543 "y": 42, # Y coordinate.
544 "x": 42, # X coordinate.
545 },
546 ],
547 },
548 "text": "A String", # The actual UTF-8 representation of the symbol.
549 "property": { # Additional information detected on the structural component. # Additional information detected for the symbol.
550 "detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.
551 "isPrefix": True or False, # True if break prepends the element.
552 "type": "A String", # Detected break type.
553 },
554 "detectedLanguages": [ # A list of detected languages together with confidence.
555 { # Detected language for a structural component.
556 "languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
557 # information, see
558 # http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
559 "confidence": 3.14, # Confidence of detected language. Range [0, 1].
560 },
561 ],
562 },
563 },
564 ],
565 "property": { # Additional information detected on the structural component. # Additional information detected for the word.
566 "detectedBreak": { # Detected start or end of a structural component. # Detected start or end of a text segment.
567 "isPrefix": True or False, # True if break prepends the element.
568 "type": "A String", # Detected break type.
569 },
570 "detectedLanguages": [ # A list of detected languages together with confidence.
571 { # Detected language for a structural component.
572 "languageCode": "A String", # The BCP-47 language code, such as "en-US" or "sr-Latn". For more
573 # information, see
574 # http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
575 "confidence": 3.14, # Confidence of detected language. Range [0, 1].
576 },
577 ],
578 },
579 },
580 ],
581 },
582 ],
583 },
584 ],
585 "height": 42, # Page height in pixels.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]586 },
587 ],
588 },
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]589 "labelAnnotations": [ # If present, label detection has completed successfully.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]590 { # Set of detected entity features.
591 "confidence": 3.14, # The accuracy of the entity detection in an image.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]592 # For example, for an image in which the "Eiffel Tower" entity is detected,
593 # this field represents the confidence that there is a tower in the query
594 # image. Range [0, 1].
595 "description": "A String", # Entity textual description, expressed in its `locale` language.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]596 "locale": "A String", # The language code for the locale in which the entity textual
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]597 # `description` is expressed.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]598 "topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]599 # image. For example, the relevancy of "tower" is likely higher to an image
600 # containing the detected "Eiffel Tower" than to an image containing a
601 # detected distant towering building, even though the confidence that
602 # there is a tower in each image may be the same. Range [0, 1].
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame^]603 "mid": "A String", # Opaque entity ID. Some IDs may be available in
604 # [Google Knowledge Graph Search API](https://developers.google.com/knowledge-graph/).
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]605 "locations": [ # The location information for the detected entity. Multiple
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]606 # `LocationInfo` elements can be present because one location may
607 # indicate the location of the scene in the image, and another location
608 # may indicate the location of the place where the image was taken.
609 # Location information is usually present for landmarks.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]610 { # Detected entity location information.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]611 "latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]612 # of doubles representing degrees latitude and degrees longitude. Unless
613 # specified otherwise, this must conform to the
614 # <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84
615 # standard</a>. Values must be within normalized ranges.
616 #
617 # Example of normalization code in Python:
618 #
619 # def NormalizeLongitude(longitude):
620 # """Wraps decimal degrees longitude to [-180.0, 180.0]."""
621 # q, r = divmod(longitude, 360.0)
622 # if r > 180.0 or (r == 180.0 and q <= -1.0):
623 # return r - 360.0
624 # return r
625 #
626 # def NormalizeLatLng(latitude, longitude):
627 # """Wraps decimal degrees latitude and longitude to
628 # [-90.0, 90.0] and [-180.0, 180.0], respectively."""
629 # r = latitude % 360.0
630 # if r <= 90.0:
631 # return r, NormalizeLongitude(longitude)
632 # elif r >= 270.0:
633 # return r - 360, NormalizeLongitude(longitude)
634 # else:
635 # return 180 - r, NormalizeLongitude(longitude + 180.0)
636 #
637 # assert 180.0 == NormalizeLongitude(180.0)
638 # assert -180.0 == NormalizeLongitude(-180.0)
639 # assert -179.0 == NormalizeLongitude(181.0)
640 # assert (0.0, 0.0) == NormalizeLatLng(360.0, 0.0)
641 # assert (0.0, 0.0) == NormalizeLatLng(-360.0, 0.0)
642 # assert (85.0, 180.0) == NormalizeLatLng(95.0, 0.0)
643 # assert (-85.0, -170.0) == NormalizeLatLng(-95.0, 10.0)
644 # assert (90.0, 10.0) == NormalizeLatLng(90.0, 10.0)
645 # assert (-90.0, -10.0) == NormalizeLatLng(-90.0, -10.0)
646 # assert (0.0, -170.0) == NormalizeLatLng(-180.0, 10.0)
647 # assert (0.0, -170.0) == NormalizeLatLng(180.0, 10.0)
648 # assert (-90.0, 10.0) == NormalizeLatLng(270.0, 10.0)
649 # assert (90.0, 10.0) == NormalizeLatLng(-270.0, 10.0)
650 "latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
651 "longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
652 },
653 },
654 ],
655 "score": 3.14, # Overall score of the result. Range [0, 1].
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]656 "boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Currently not produced
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]657 # for `LABEL_DETECTION` features. For `TEXT_DETECTION` (OCR), `boundingPoly`s
658 # are produced for the entire text detected in an image region, followed by
659 # `boundingPoly`s for each word within the detected text.
660 "vertices": [ # The bounding polygon vertices.
661 { # A vertex represents a 2D point in the image.
662 # NOTE: the vertex coordinates are in the same scale as the original image.
663 "y": 42, # Y coordinate.
664 "x": 42, # X coordinate.
665 },
666 ],
667 },
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]668 "properties": [ # Some entities may have optional user-supplied `Property` (name/value)
669 # fields, such a score or string that qualifies the entity.
670 { # A `Property` consists of a user-supplied name/value pair.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]671 "uint64Value": "A String", # Value of numeric properties.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]672 "name": "A String", # Name of the property.
673 "value": "A String", # Value of the property.
674 },
675 ],
676 },
677 ],
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]678 "imagePropertiesAnnotation": { # Stores image properties, such as dominant colors. # If present, image properties were extracted successfully.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]679 "dominantColors": { # Set of dominant colors and their corresponding scores. # If present, dominant colors completed successfully.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]680 "colors": [ # RGB color values with their score and pixel fraction.
681 { # Color information consists of RGB channels, score, and the fraction of
682 # the image that the color occupies in the image.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]683 "color": { # Represents a color in the RGBA color space. This representation is designed # RGB components of the color.
684 # for simplicity of conversion to/from color representations in various
685 # languages over compactness; for example, the fields of this representation
686 # can be trivially provided to the constructor of "java.awt.Color" in Java; it
687 # can also be trivially provided to UIColor's "+colorWithRed:green:blue:alpha"
688 # method in iOS; and, with just a little work, it can be easily formatted into
689 # a CSS "rgba()" string in JavaScript, as well. Here are some examples:
690 #
691 # Example (Java):
692 #
693 # import com.google.type.Color;
694 #
695 # // ...
696 # public static java.awt.Color fromProto(Color protocolor) {
697 # float alpha = protocolor.hasAlpha()
698 # ? protocolor.getAlpha().getValue()
699 # : 1.0;
700 #
701 # return new java.awt.Color(
702 # protocolor.getRed(),
703 # protocolor.getGreen(),
704 # protocolor.getBlue(),
705 # alpha);
706 # }
707 #
708 # public static Color toProto(java.awt.Color color) {
709 # float red = (float) color.getRed();
710 # float green = (float) color.getGreen();
711 # float blue = (float) color.getBlue();
712 # float denominator = 255.0;
713 # Color.Builder resultBuilder =
714 # Color
715 # .newBuilder()
716 # .setRed(red / denominator)
717 # .setGreen(green / denominator)
718 # .setBlue(blue / denominator);
719 # int alpha = color.getAlpha();
720 # if (alpha != 255) {
721 # result.setAlpha(
722 # FloatValue
723 # .newBuilder()
724 # .setValue(((float) alpha) / denominator)
725 # .build());
726 # }
727 # return resultBuilder.build();
728 # }
729 # // ...
730 #
731 # Example (iOS / Obj-C):
732 #
733 # // ...
734 # static UIColor* fromProto(Color* protocolor) {
735 # float red = [protocolor red];
736 # float green = [protocolor green];
737 # float blue = [protocolor blue];
738 # FloatValue* alpha_wrapper = [protocolor alpha];
739 # float alpha = 1.0;
740 # if (alpha_wrapper != nil) {
741 # alpha = [alpha_wrapper value];
742 # }
743 # return [UIColor colorWithRed:red green:green blue:blue alpha:alpha];
744 # }
745 #
746 # static Color* toProto(UIColor* color) {
747 # CGFloat red, green, blue, alpha;
748 # if (![color getRed:&red green:&green blue:&blue alpha:&alpha]) {
749 # return nil;
750 # }
751 # Color* result = [Color alloc] init];
752 # [result setRed:red];
753 # [result setGreen:green];
754 # [result setBlue:blue];
755 # if (alpha <= 0.9999) {
756 # [result setAlpha:floatWrapperWithValue(alpha)];
757 # }
758 # [result autorelease];
759 # return result;
760 # }
761 # // ...
762 #
763 # Example (JavaScript):
764 #
765 # // ...
766 #
767 # var protoToCssColor = function(rgb_color) {
768 # var redFrac = rgb_color.red || 0.0;
769 # var greenFrac = rgb_color.green || 0.0;
770 # var blueFrac = rgb_color.blue || 0.0;
771 # var red = Math.floor(redFrac * 255);
772 # var green = Math.floor(greenFrac * 255);
773 # var blue = Math.floor(blueFrac * 255);
774 #
775 # if (!('alpha' in rgb_color)) {
776 # return rgbToCssColor_(red, green, blue);
777 # }
778 #
779 # var alphaFrac = rgb_color.alpha.value || 0.0;
780 # var rgbParams = [red, green, blue].join(',');
781 # return ['rgba(', rgbParams, ',', alphaFrac, ')'].join('');
782 # };
783 #
784 # var rgbToCssColor_ = function(red, green, blue) {
785 # var rgbNumber = new Number((red << 16) | (green << 8) | blue);
786 # var hexString = rgbNumber.toString(16);
787 # var missingZeros = 6 - hexString.length;
788 # var resultBuilder = ['#'];
789 # for (var i = 0; i < missingZeros; i++) {
790 # resultBuilder.push('0');
791 # }
792 # resultBuilder.push(hexString);
793 # return resultBuilder.join('');
794 # };
795 #
796 # // ...
797 "blue": 3.14, # The amount of blue in the color as a value in the interval [0, 1].
798 "alpha": 3.14, # The fraction of this color that should be applied to the pixel. That is,
799 # the final pixel color is defined by the equation:
800 #
801 # pixel color = alpha * (this color) + (1.0 - alpha) * (background color)
802 #
803 # This means that a value of 1.0 corresponds to a solid color, whereas
804 # a value of 0.0 corresponds to a completely transparent color. This
805 # uses a wrapper message rather than a simple float scalar so that it is
806 # possible to distinguish between a default value and the value being unset.
807 # If omitted, this color object is to be rendered as a solid color
808 # (as if the alpha value had been explicitly given with a value of 1.0).
809 "green": 3.14, # The amount of green in the color as a value in the interval [0, 1].
810 "red": 3.14, # The amount of red in the color as a value in the interval [0, 1].
811 },
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]812 "pixelFraction": 3.14, # The fraction of pixels the color occupies in the image.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]813 # Value in range [0, 1].
814 "score": 3.14, # Image-specific score for this color. Value in range [0, 1].
815 },
816 ],
817 },
818 },
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]819 "faceAnnotations": [ # If present, face detection has completed successfully.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]820 { # A face annotation object contains the results of face detection.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]821 "sorrowLikelihood": "A String", # Sorrow likelihood.
822 "landmarkingConfidence": 3.14, # Face landmarking confidence. Range [0, 1].
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]823 "underExposedLikelihood": "A String", # Under-exposed likelihood.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]824 "detectionConfidence": 3.14, # Detection confidence. Range [0, 1].
825 "joyLikelihood": "A String", # Joy likelihood.
826 "landmarks": [ # Detected face landmarks.
827 { # A face-specific landmark (for example, a face feature).
828 # Landmark positions may fall outside the bounds of the image
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]829 # if the face is near one or more edges of the image.
830 # Therefore it is NOT guaranteed that `0 <= x < width` or
831 # `0 <= y < height`.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]832 "position": { # A 3D position in the image, used primarily for Face detection landmarks. # Face landmark position.
833 # A valid Position must have both x and y coordinates.
834 # The position coordinates are in the same scale as the original image.
835 "y": 3.14, # Y coordinate.
836 "x": 3.14, # X coordinate.
837 "z": 3.14, # Z coordinate (or depth).
838 },
839 "type": "A String", # Face landmark type.
840 },
841 ],
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]842 "surpriseLikelihood": "A String", # Surprise likelihood.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]843 "blurredLikelihood": "A String", # Blurred likelihood.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]844 "tiltAngle": 3.14, # Pitch angle, which indicates the upwards/downwards angle that the face is
845 # pointing relative to the image's horizontal plane. Range [-180,180].
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]846 "angerLikelihood": "A String", # Anger likelihood.
847 "boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon around the face. The coordinates of the bounding box
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]848 # are in the original image's scale, as returned in `ImageParams`.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]849 # The bounding box is computed to "frame" the face in accordance with human
850 # expectations. It is based on the landmarker results.
851 # Note that one or more x and/or y coordinates may not be generated in the
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]852 # `BoundingPoly` (the polygon will be unbounded) if only a partial face
853 # appears in the image to be annotated.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]854 "vertices": [ # The bounding polygon vertices.
855 { # A vertex represents a 2D point in the image.
856 # NOTE: the vertex coordinates are in the same scale as the original image.
857 "y": 42, # Y coordinate.
858 "x": 42, # X coordinate.
859 },
860 ],
861 },
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]862 "rollAngle": 3.14, # Roll angle, which indicates the amount of clockwise/anti-clockwise rotation
863 # of the face relative to the image vertical about the axis perpendicular to
864 # the face. Range [-180,180].
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame^]865 "panAngle": 3.14, # Yaw angle, which indicates the leftward/rightward angle that the face is
866 # pointing relative to the vertical plane perpendicular to the image. Range
867 # [-180,180].
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]868 "headwearLikelihood": "A String", # Headwear likelihood.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]869 "fdBoundingPoly": { # A bounding polygon for the detected image annotation. # The `fd_bounding_poly` bounding polygon is tighter than the
870 # `boundingPoly`, and encloses only the skin part of the face. Typically, it
871 # is used to eliminate the face from any image analysis that detects the
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]872 # "amount of skin" visible in an image. It is not based on the
873 # landmarker results, only on the initial face detection, hence
874 # the <code>fd</code> (face detection) prefix.
875 "vertices": [ # The bounding polygon vertices.
876 { # A vertex represents a 2D point in the image.
877 # NOTE: the vertex coordinates are in the same scale as the original image.
878 "y": 42, # Y coordinate.
879 "x": 42, # X coordinate.
880 },
881 ],
882 },
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]883 },
884 ],
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]885 "logoAnnotations": [ # If present, logo detection has completed successfully.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]886 { # Set of detected entity features.
887 "confidence": 3.14, # The accuracy of the entity detection in an image.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]888 # For example, for an image in which the "Eiffel Tower" entity is detected,
889 # this field represents the confidence that there is a tower in the query
890 # image. Range [0, 1].
891 "description": "A String", # Entity textual description, expressed in its `locale` language.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]892 "locale": "A String", # The language code for the locale in which the entity textual
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]893 # `description` is expressed.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]894 "topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]895 # image. For example, the relevancy of "tower" is likely higher to an image
896 # containing the detected "Eiffel Tower" than to an image containing a
897 # detected distant towering building, even though the confidence that
898 # there is a tower in each image may be the same. Range [0, 1].
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame^]899 "mid": "A String", # Opaque entity ID. Some IDs may be available in
900 # [Google Knowledge Graph Search API](https://developers.google.com/knowledge-graph/).
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]901 "locations": [ # The location information for the detected entity. Multiple
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]902 # `LocationInfo` elements can be present because one location may
903 # indicate the location of the scene in the image, and another location
904 # may indicate the location of the place where the image was taken.
905 # Location information is usually present for landmarks.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]906 { # Detected entity location information.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]907 "latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]908 # of doubles representing degrees latitude and degrees longitude. Unless
909 # specified otherwise, this must conform to the
910 # <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84
911 # standard</a>. Values must be within normalized ranges.
912 #
913 # Example of normalization code in Python:
914 #
915 # def NormalizeLongitude(longitude):
916 # """Wraps decimal degrees longitude to [-180.0, 180.0]."""
917 # q, r = divmod(longitude, 360.0)
918 # if r > 180.0 or (r == 180.0 and q <= -1.0):
919 # return r - 360.0
920 # return r
921 #
922 # def NormalizeLatLng(latitude, longitude):
923 # """Wraps decimal degrees latitude and longitude to
924 # [-90.0, 90.0] and [-180.0, 180.0], respectively."""
925 # r = latitude % 360.0
926 # if r <= 90.0:
927 # return r, NormalizeLongitude(longitude)
928 # elif r >= 270.0:
929 # return r - 360, NormalizeLongitude(longitude)
930 # else:
931 # return 180 - r, NormalizeLongitude(longitude + 180.0)
932 #
933 # assert 180.0 == NormalizeLongitude(180.0)
934 # assert -180.0 == NormalizeLongitude(-180.0)
935 # assert -179.0 == NormalizeLongitude(181.0)
936 # assert (0.0, 0.0) == NormalizeLatLng(360.0, 0.0)
937 # assert (0.0, 0.0) == NormalizeLatLng(-360.0, 0.0)
938 # assert (85.0, 180.0) == NormalizeLatLng(95.0, 0.0)
939 # assert (-85.0, -170.0) == NormalizeLatLng(-95.0, 10.0)
940 # assert (90.0, 10.0) == NormalizeLatLng(90.0, 10.0)
941 # assert (-90.0, -10.0) == NormalizeLatLng(-90.0, -10.0)
942 # assert (0.0, -170.0) == NormalizeLatLng(-180.0, 10.0)
943 # assert (0.0, -170.0) == NormalizeLatLng(180.0, 10.0)
944 # assert (-90.0, 10.0) == NormalizeLatLng(270.0, 10.0)
945 # assert (90.0, 10.0) == NormalizeLatLng(-270.0, 10.0)
946 "latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
947 "longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
948 },
949 },
950 ],
951 "score": 3.14, # Overall score of the result. Range [0, 1].
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]952 "boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Currently not produced
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]953 # for `LABEL_DETECTION` features. For `TEXT_DETECTION` (OCR), `boundingPoly`s
954 # are produced for the entire text detected in an image region, followed by
955 # `boundingPoly`s for each word within the detected text.
956 "vertices": [ # The bounding polygon vertices.
957 { # A vertex represents a 2D point in the image.
958 # NOTE: the vertex coordinates are in the same scale as the original image.
959 "y": 42, # Y coordinate.
960 "x": 42, # X coordinate.
961 },
962 ],
963 },
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]964 "properties": [ # Some entities may have optional user-supplied `Property` (name/value)
965 # fields, such a score or string that qualifies the entity.
966 { # A `Property` consists of a user-supplied name/value pair.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]967 "uint64Value": "A String", # Value of numeric properties.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]968 "name": "A String", # Name of the property.
969 "value": "A String", # Value of the property.
970 },
971 ],
972 },
973 ],
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]974 "landmarkAnnotations": [ # If present, landmark detection has completed successfully.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]975 { # Set of detected entity features.
976 "confidence": 3.14, # The accuracy of the entity detection in an image.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]977 # For example, for an image in which the "Eiffel Tower" entity is detected,
978 # this field represents the confidence that there is a tower in the query
979 # image. Range [0, 1].
980 "description": "A String", # Entity textual description, expressed in its `locale` language.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]981 "locale": "A String", # The language code for the locale in which the entity textual
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]982 # `description` is expressed.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]983 "topicality": 3.14, # The relevancy of the ICA (Image Content Annotation) label to the
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]984 # image. For example, the relevancy of "tower" is likely higher to an image
985 # containing the detected "Eiffel Tower" than to an image containing a
986 # detected distant towering building, even though the confidence that
987 # there is a tower in each image may be the same. Range [0, 1].
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame^]988 "mid": "A String", # Opaque entity ID. Some IDs may be available in
989 # [Google Knowledge Graph Search API](https://developers.google.com/knowledge-graph/).
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]990 "locations": [ # The location information for the detected entity. Multiple
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]991 # `LocationInfo` elements can be present because one location may
992 # indicate the location of the scene in the image, and another location
993 # may indicate the location of the place where the image was taken.
994 # Location information is usually present for landmarks.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]995 { # Detected entity location information.
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]996 "latLng": { # An object representing a latitude/longitude pair. This is expressed as a pair # lat/long location coordinates.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]997 # of doubles representing degrees latitude and degrees longitude. Unless
998 # specified otherwise, this must conform to the
999 # <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84
1000 # standard</a>. Values must be within normalized ranges.
1001 #
1002 # Example of normalization code in Python:
1003 #
1004 # def NormalizeLongitude(longitude):
1005 # """Wraps decimal degrees longitude to [-180.0, 180.0]."""
1006 # q, r = divmod(longitude, 360.0)
1007 # if r > 180.0 or (r == 180.0 and q <= -1.0):
1008 # return r - 360.0
1009 # return r
1010 #
1011 # def NormalizeLatLng(latitude, longitude):
1012 # """Wraps decimal degrees latitude and longitude to
1013 # [-90.0, 90.0] and [-180.0, 180.0], respectively."""
1014 # r = latitude % 360.0
1015 # if r <= 90.0:
1016 # return r, NormalizeLongitude(longitude)
1017 # elif r >= 270.0:
1018 # return r - 360, NormalizeLongitude(longitude)
1019 # else:
1020 # return 180 - r, NormalizeLongitude(longitude + 180.0)
1021 #
1022 # assert 180.0 == NormalizeLongitude(180.0)
1023 # assert -180.0 == NormalizeLongitude(-180.0)
1024 # assert -179.0 == NormalizeLongitude(181.0)
1025 # assert (0.0, 0.0) == NormalizeLatLng(360.0, 0.0)
1026 # assert (0.0, 0.0) == NormalizeLatLng(-360.0, 0.0)
1027 # assert (85.0, 180.0) == NormalizeLatLng(95.0, 0.0)
1028 # assert (-85.0, -170.0) == NormalizeLatLng(-95.0, 10.0)
1029 # assert (90.0, 10.0) == NormalizeLatLng(90.0, 10.0)
1030 # assert (-90.0, -10.0) == NormalizeLatLng(-90.0, -10.0)
1031 # assert (0.0, -170.0) == NormalizeLatLng(-180.0, 10.0)
1032 # assert (0.0, -170.0) == NormalizeLatLng(180.0, 10.0)
1033 # assert (-90.0, 10.0) == NormalizeLatLng(270.0, 10.0)
1034 # assert (90.0, 10.0) == NormalizeLatLng(-270.0, 10.0)
1035 "latitude": 3.14, # The latitude in degrees. It must be in the range [-90.0, +90.0].
1036 "longitude": 3.14, # The longitude in degrees. It must be in the range [-180.0, +180.0].
1037 },
1038 },
1039 ],
1040 "score": 3.14, # Overall score of the result. Range [0, 1].
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]1041 "boundingPoly": { # A bounding polygon for the detected image annotation. # Image region to which this entity belongs. Currently not produced
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]1042 # for `LABEL_DETECTION` features. For `TEXT_DETECTION` (OCR), `boundingPoly`s
1043 # are produced for the entire text detected in an image region, followed by
1044 # `boundingPoly`s for each word within the detected text.
1045 "vertices": [ # The bounding polygon vertices.
1046 { # A vertex represents a 2D point in the image.
1047 # NOTE: the vertex coordinates are in the same scale as the original image.
1048 "y": 42, # Y coordinate.
1049 "x": 42, # X coordinate.
1050 },
1051 ],
1052 },
Jon Wayne Parrott692617a2017-01-06 09:58:29 -0800[diff] [blame]1053 "properties": [ # Some entities may have optional user-supplied `Property` (name/value)
1054 # fields, such a score or string that qualifies the entity.
1055 { # A `Property` consists of a user-supplied name/value pair.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1056 "uint64Value": "A String", # Value of numeric properties.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]1057 "name": "A String", # Name of the property.
1058 "value": "A String", # Value of the property.
1059 },
1060 ],
1061 },
1062 ],
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame^]1063 "error": { # The `Status` type defines a logical error model that is suitable for different # If set, represents the error message for the operation.
1064 # Note that filled-in image annotations are guaranteed to be
1065 # correct, even when `error` is set.
1066 # programming environments, including REST APIs and RPC APIs. It is used by
1067 # [gRPC](https://github.com/grpc). The error model is designed to be:
1068 #
1069 # - Simple to use and understand for most users
1070 # - Flexible enough to meet unexpected needs
1071 #
1072 # # Overview
1073 #
1074 # The `Status` message contains three pieces of data: error code, error message,
1075 # and error details. The error code should be an enum value of
1076 # google.rpc.Code, but it may accept additional error codes if needed. The
1077 # error message should be a developer-facing English message that helps
1078 # developers *understand* and *resolve* the error. If a localized user-facing
1079 # error message is needed, put the localized message in the error details or
1080 # localize it in the client. The optional error details may contain arbitrary
1081 # information about the error. There is a predefined set of error detail types
1082 # in the package `google.rpc` that can be used for common error conditions.
1083 #
1084 # # Language mapping
1085 #
1086 # The `Status` message is the logical representation of the error model, but it
1087 # is not necessarily the actual wire format. When the `Status` message is
1088 # exposed in different client libraries and different wire protocols, it can be
1089 # mapped differently. For example, it will likely be mapped to some exceptions
1090 # in Java, but more likely mapped to some error codes in C.
1091 #
1092 # # Other uses
1093 #
1094 # The error model and the `Status` message can be used in a variety of
1095 # environments, either with or without APIs, to provide a
1096 # consistent developer experience across different environments.
1097 #
1098 # Example uses of this error model include:
1099 #
1100 # - Partial errors. If a service needs to return partial errors to the client,
1101 # it may embed the `Status` in the normal response to indicate the partial
1102 # errors.
1103 #
1104 # - Workflow errors. A typical workflow has multiple steps. Each step may
1105 # have a `Status` message for error reporting.
1106 #
1107 # - Batch operations. If a client uses batch request and batch response, the
1108 # `Status` message should be used directly inside batch response, one for
1109 # each error sub-response.
1110 #
1111 # - Asynchronous operations. If an API call embeds asynchronous operation
1112 # results in its response, the status of those operations should be
1113 # represented directly using the `Status` message.
1114 #
1115 # - Logging. If some API errors are stored in logs, the message `Status` could
1116 # be used directly after any stripping needed for security/privacy reasons.
1117 "message": "A String", # A developer-facing error message, which should be in English. Any
1118 # user-facing error message should be localized and sent in the
1119 # google.rpc.Status.details field, or localized by the client.
1120 "code": 42, # The status code, which should be an enum value of google.rpc.Code.
1121 "details": [ # A list of messages that carry the error details. There will be a
1122 # common set of message types for APIs to use.
1123 {
1124 "a_key": "", # Properties of the object. Contains field @type with type URL.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1125 },
1126 ],
1127 },
1128 "cropHintsAnnotation": { # Set of crop hints that are used to generate new crops when serving images. # If present, crop hints have completed successfully.
1129 "cropHints": [ # Crop hint results.
1130 { # Single crop hint that is used to generate a new crop when serving an image.
1131 "confidence": 3.14, # Confidence of this being a salient region. Range [0, 1].
1132 "boundingPoly": { # A bounding polygon for the detected image annotation. # The bounding polygon for the crop region. The coordinates of the bounding
1133 # box are in the original image's scale, as returned in `ImageParams`.
1134 "vertices": [ # The bounding polygon vertices.
1135 { # A vertex represents a 2D point in the image.
1136 # NOTE: the vertex coordinates are in the same scale as the original image.
1137 "y": 42, # Y coordinate.
1138 "x": 42, # X coordinate.
1139 },
1140 ],
1141 },
1142 "importanceFraction": 3.14, # Fraction of importance of this salient region with respect to the original
1143 # image.
Jon Wayne Parrott0a471d32016-05-19 10:54:38 -0700[diff] [blame]1144 },
1145 ],
1146 },
1147 },
1148 ],
1149 }</pre>
1150</div>
1151
1152</body></html>