1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
|
<html><body>
<style>
body, h1, h2, h3, div, span, p, pre, a {
margin: 0;
padding: 0;
border: 0;
font-weight: inherit;
font-style: inherit;
font-size: 100%;
font-family: inherit;
vertical-align: baseline;
}
body {
font-size: 13px;
padding: 1em;
}
h1 {
font-size: 26px;
margin-bottom: 1em;
}
h2 {
font-size: 24px;
margin-bottom: 1em;
}
h3 {
font-size: 20px;
margin-bottom: 1em;
margin-top: 1em;
}
pre, code {
line-height: 1.5;
font-family: Monaco, 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Lucida Console', monospace;
}
pre {
margin-top: 0.5em;
}
h1, h2, h3, p {
font-family: Arial, sans serif;
}
h1, h2, h3 {
border-bottom: solid #CCC 1px;
}
.toc_element {
margin-top: 0.5em;
}
.firstline {
margin-left: 2 em;
}
.method {
margin-top: 1em;
border: solid 1px #CCC;
padding: 1em;
background: #EEE;
}
.details {
font-weight: bold;
font-size: 14px;
}
</style>
<h1><a href="datalabeling_v1beta1.html">Data Labeling API</a> . <a href="datalabeling_v1beta1.projects.html">projects</a> . <a href="datalabeling_v1beta1.projects.datasets.html">datasets</a> . <a href="datalabeling_v1beta1.projects.datasets.annotatedDatasets.html">annotatedDatasets</a> . <a href="datalabeling_v1beta1.projects.datasets.annotatedDatasets.examples.html">examples</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
<code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
<code><a href="#get">get(name, filter=None, x__xgafv=None)</a></code></p>
<p class="firstline">Gets an example by resource name, including both data and annotation.</p>
<p class="toc_element">
<code><a href="#list">list(parent, filter=None, pageSize=None, pageToken=None, x__xgafv=None)</a></code></p>
<p class="firstline">Lists examples in an annotated dataset. Pagination is supported.</p>
<p class="toc_element">
<code><a href="#list_next">list_next()</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<h3>Method Details</h3>
<div class="method">
<code class="details" id="close">close()</code>
<pre>Close httplib2 connections.</pre>
</div>
<div class="method">
<code class="details" id="get">get(name, filter=None, x__xgafv=None)</code>
<pre>Gets an example by resource name, including both data and annotation.
Args:
name: string, Required. Name of example, format: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}/examples/{example_id} (required)
filter: string, Optional. An expression for filtering Examples. Filter by annotation_spec.display_name is supported. Format "annotation_spec.display_name = {display_name}"
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # An Example is a piece of data and its annotation. For example, an image with label "house".
"annotations": [ # Output only. Annotations for the piece of data in Example. One piece of data can have multiple annotations.
{ # Annotation for Example. Each example may have one or more annotations. For example in image classification problem, each image might have one or more labels. We call labels binded with this image an Annotation.
"annotationMetadata": { # Additional information associated with the annotation. # Output only. Annotation metadata, including information like votes for labels.
"operatorMetadata": { # General information useful for labels coming from contributors. # Metadata related to human labeling.
"comments": [ # Comments from contributors.
"A String",
],
"labelVotes": 42, # The total number of contributors that choose this label.
"score": 3.14, # Confidence score corresponding to a label. For examle, if 3 contributors have answered the question and 2 of them agree on the final label, the confidence score will be 0.67 (2/3).
"totalVotes": 42, # The total number of contributors that answer this question.
},
},
"annotationSentiment": "A String", # Output only. Sentiment for this annotation.
"annotationSource": "A String", # Output only. The source of the annotation.
"annotationValue": { # Annotation value for an example. # Output only. This is the actual annotation value, e.g classification, bounding box values are stored here.
"imageBoundingPolyAnnotation": { # Image bounding poly annotation. It represents a polygon including bounding box in the image. # Annotation value for image bounding box, oriented bounding box and polygon cases.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of object in this bounding polygon.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"boundingPoly": { # A bounding polygon in the image.
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image. NOTE: the vertex coordinates are in the same scale as the original image.
"x": 42, # X coordinate.
"y": 42, # Y coordinate.
},
],
},
"normalizedBoundingPoly": { # Normalized bounding polygon.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.
"x": 3.14, # X coordinate.
"y": 3.14, # Y coordinate.
},
],
},
},
"imageClassificationAnnotation": { # Image classification annotation definition. # Annotation value for image classification case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of image.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
},
"imagePolylineAnnotation": { # A polyline for the image annotation. # Annotation value for image polyline cases. Polyline here is different from BoundingPoly. It is formed by line segments connected to each other but not closed form(Bounding Poly). The line segments can cross each other.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of this polyline.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"normalizedPolyline": { # Normalized polyline.
"normalizedVertices": [ # The normalized polyline vertices.
{ # A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.
"x": 3.14, # X coordinate.
"y": 3.14, # Y coordinate.
},
],
},
"polyline": { # A line with multiple line segments.
"vertices": [ # The polyline vertices.
{ # A vertex represents a 2D point in the image. NOTE: the vertex coordinates are in the same scale as the original image.
"x": 42, # X coordinate.
"y": 42, # Y coordinate.
},
],
},
},
"imageSegmentationAnnotation": { # Image segmentation annotation. # Annotation value for image segmentation.
"annotationColors": { # The mapping between rgb color and annotation spec. The key is the rgb color represented in format of rgb(0, 0, 0). The value is the AnnotationSpec.
"a_key": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
},
"imageBytes": "A String", # A byte string of a full image's color map.
"mimeType": "A String", # Image format.
},
"textClassificationAnnotation": { # Text classification annotation. # Annotation value for text classification case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of the text.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
},
"textEntityExtractionAnnotation": { # Text entity extraction annotation. # Annotation value for text entity extraction case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of the text entities.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"sequentialSegment": { # Start and end position in a sequence (e.g. text segment). # Position of the entity.
"end": 42, # End position (exclusive).
"start": 42, # Start position (inclusive).
},
},
"videoClassificationAnnotation": { # Video classification annotation. # Annotation value for video classification case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of the segment specified by time_segment.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"timeSegment": { # A time period inside of an example that has a time dimension (e.g. video). # The time segment of the video to which the annotation applies.
"endTimeOffset": "A String", # End of the time segment (exclusive), represented as the duration since the example start.
"startTimeOffset": "A String", # Start of the time segment (inclusive), represented as the duration since the example start.
},
},
"videoEventAnnotation": { # Video event annotation. # Annotation value for video event case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of the event in this annotation.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"timeSegment": { # A time period inside of an example that has a time dimension (e.g. video). # The time segment of the video to which the annotation applies.
"endTimeOffset": "A String", # End of the time segment (exclusive), represented as the duration since the example start.
"startTimeOffset": "A String", # Start of the time segment (inclusive), represented as the duration since the example start.
},
},
"videoObjectTrackingAnnotation": { # Video object tracking annotation. # Annotation value for video object detection and tracking case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of the object tracked in this annotation.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"objectTrackingFrames": [ # The list of frames where this object track appears.
{ # Video frame level annotation for object detection and tracking.
"boundingPoly": { # A bounding polygon in the image.
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image. NOTE: the vertex coordinates are in the same scale as the original image.
"x": 42, # X coordinate.
"y": 42, # Y coordinate.
},
],
},
"normalizedBoundingPoly": { # Normalized bounding polygon.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.
"x": 3.14, # X coordinate.
"y": 3.14, # Y coordinate.
},
],
},
"timeOffset": "A String", # The time offset of this frame relative to the beginning of the video.
},
],
"timeSegment": { # A time period inside of an example that has a time dimension (e.g. video). # The time segment of the video to which object tracking applies.
"endTimeOffset": "A String", # End of the time segment (exclusive), represented as the duration since the example start.
"startTimeOffset": "A String", # Start of the time segment (inclusive), represented as the duration since the example start.
},
},
},
"name": "A String", # Output only. Unique name of this annotation, format is: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/{annotated_dataset}/examples/{example_id}/annotations/{annotation_id}
},
],
"imagePayload": { # Container of information about an image. # The image payload, a container of the image bytes/uri.
"imageThumbnail": "A String", # A byte string of a thumbnail image.
"imageUri": "A String", # Image uri from the user bucket.
"mimeType": "A String", # Image format.
"signedUri": "A String", # Signed uri of the image file in the service bucket.
},
"name": "A String", # Output only. Name of the example, in format of: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}/examples/{example_id}
"textPayload": { # Container of information about a piece of text. # The text payload, a container of the text content.
"textContent": "A String", # Text content.
},
"videoPayload": { # Container of information of a video. # The video payload, a container of the video uri.
"frameRate": 3.14, # FPS of the video.
"mimeType": "A String", # Video format.
"signedUri": "A String", # Signed uri of the video file in the service bucket.
"videoThumbnails": [ # The list of video thumbnails.
{ # Container of information of a video thumbnail.
"thumbnail": "A String", # A byte string of the video frame.
"timeOffset": "A String", # Time offset relative to the beginning of the video, corresponding to the video frame where the thumbnail has been extracted from.
},
],
"videoUri": "A String", # Video uri from the user bucket.
},
}</pre>
</div>
<div class="method">
<code class="details" id="list">list(parent, filter=None, pageSize=None, pageToken=None, x__xgafv=None)</code>
<pre>Lists examples in an annotated dataset. Pagination is supported.
Args:
parent: string, Required. Example resource parent. (required)
filter: string, Optional. An expression for filtering Examples. For annotated datasets that have annotation spec set, filter by annotation_spec.display_name is supported. Format "annotation_spec.display_name = {display_name}"
pageSize: integer, Optional. Requested page size. Server may return fewer results than requested. Default value is 100.
pageToken: string, Optional. A token identifying a page of results for the server to return. Typically obtained by ListExamplesResponse.next_page_token of the previous [DataLabelingService.ListExamples] call. Return first page if empty.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # Results of listing Examples in and annotated dataset.
"examples": [ # The list of examples to return.
{ # An Example is a piece of data and its annotation. For example, an image with label "house".
"annotations": [ # Output only. Annotations for the piece of data in Example. One piece of data can have multiple annotations.
{ # Annotation for Example. Each example may have one or more annotations. For example in image classification problem, each image might have one or more labels. We call labels binded with this image an Annotation.
"annotationMetadata": { # Additional information associated with the annotation. # Output only. Annotation metadata, including information like votes for labels.
"operatorMetadata": { # General information useful for labels coming from contributors. # Metadata related to human labeling.
"comments": [ # Comments from contributors.
"A String",
],
"labelVotes": 42, # The total number of contributors that choose this label.
"score": 3.14, # Confidence score corresponding to a label. For examle, if 3 contributors have answered the question and 2 of them agree on the final label, the confidence score will be 0.67 (2/3).
"totalVotes": 42, # The total number of contributors that answer this question.
},
},
"annotationSentiment": "A String", # Output only. Sentiment for this annotation.
"annotationSource": "A String", # Output only. The source of the annotation.
"annotationValue": { # Annotation value for an example. # Output only. This is the actual annotation value, e.g classification, bounding box values are stored here.
"imageBoundingPolyAnnotation": { # Image bounding poly annotation. It represents a polygon including bounding box in the image. # Annotation value for image bounding box, oriented bounding box and polygon cases.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of object in this bounding polygon.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"boundingPoly": { # A bounding polygon in the image.
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image. NOTE: the vertex coordinates are in the same scale as the original image.
"x": 42, # X coordinate.
"y": 42, # Y coordinate.
},
],
},
"normalizedBoundingPoly": { # Normalized bounding polygon.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.
"x": 3.14, # X coordinate.
"y": 3.14, # Y coordinate.
},
],
},
},
"imageClassificationAnnotation": { # Image classification annotation definition. # Annotation value for image classification case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of image.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
},
"imagePolylineAnnotation": { # A polyline for the image annotation. # Annotation value for image polyline cases. Polyline here is different from BoundingPoly. It is formed by line segments connected to each other but not closed form(Bounding Poly). The line segments can cross each other.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of this polyline.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"normalizedPolyline": { # Normalized polyline.
"normalizedVertices": [ # The normalized polyline vertices.
{ # A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.
"x": 3.14, # X coordinate.
"y": 3.14, # Y coordinate.
},
],
},
"polyline": { # A line with multiple line segments.
"vertices": [ # The polyline vertices.
{ # A vertex represents a 2D point in the image. NOTE: the vertex coordinates are in the same scale as the original image.
"x": 42, # X coordinate.
"y": 42, # Y coordinate.
},
],
},
},
"imageSegmentationAnnotation": { # Image segmentation annotation. # Annotation value for image segmentation.
"annotationColors": { # The mapping between rgb color and annotation spec. The key is the rgb color represented in format of rgb(0, 0, 0). The value is the AnnotationSpec.
"a_key": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
},
"imageBytes": "A String", # A byte string of a full image's color map.
"mimeType": "A String", # Image format.
},
"textClassificationAnnotation": { # Text classification annotation. # Annotation value for text classification case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of the text.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
},
"textEntityExtractionAnnotation": { # Text entity extraction annotation. # Annotation value for text entity extraction case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of the text entities.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"sequentialSegment": { # Start and end position in a sequence (e.g. text segment). # Position of the entity.
"end": 42, # End position (exclusive).
"start": 42, # Start position (inclusive).
},
},
"videoClassificationAnnotation": { # Video classification annotation. # Annotation value for video classification case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of the segment specified by time_segment.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"timeSegment": { # A time period inside of an example that has a time dimension (e.g. video). # The time segment of the video to which the annotation applies.
"endTimeOffset": "A String", # End of the time segment (exclusive), represented as the duration since the example start.
"startTimeOffset": "A String", # Start of the time segment (inclusive), represented as the duration since the example start.
},
},
"videoEventAnnotation": { # Video event annotation. # Annotation value for video event case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of the event in this annotation.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"timeSegment": { # A time period inside of an example that has a time dimension (e.g. video). # The time segment of the video to which the annotation applies.
"endTimeOffset": "A String", # End of the time segment (exclusive), represented as the duration since the example start.
"startTimeOffset": "A String", # Start of the time segment (inclusive), represented as the duration since the example start.
},
},
"videoObjectTrackingAnnotation": { # Video object tracking annotation. # Annotation value for video object detection and tracking case.
"annotationSpec": { # Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as `dog` or `cat` must reference an AnnotationSpec for `dog` and an AnnotationSpec for `cat`. # Label of the object tracked in this annotation.
"description": "A String", # Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.
"displayName": "A String", # Required. The display name of the AnnotationSpec. Maximum of 64 characters.
"index": 42, # Output only. This is the integer index of the AnnotationSpec. The index for the whole AnnotationSpecSet is sequential starting from 0. For example, an AnnotationSpecSet with classes `dog` and `cat`, might contain one AnnotationSpec with `{ display_name: "dog", index: 0 }` and one AnnotationSpec with `{ display_name: "cat", index: 1 }`. This is especially useful for model training as it encodes the string labels into numeric values.
},
"objectTrackingFrames": [ # The list of frames where this object track appears.
{ # Video frame level annotation for object detection and tracking.
"boundingPoly": { # A bounding polygon in the image.
"vertices": [ # The bounding polygon vertices.
{ # A vertex represents a 2D point in the image. NOTE: the vertex coordinates are in the same scale as the original image.
"x": 42, # X coordinate.
"y": 42, # Y coordinate.
},
],
},
"normalizedBoundingPoly": { # Normalized bounding polygon.
"normalizedVertices": [ # The bounding polygon normalized vertices.
{ # A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.
"x": 3.14, # X coordinate.
"y": 3.14, # Y coordinate.
},
],
},
"timeOffset": "A String", # The time offset of this frame relative to the beginning of the video.
},
],
"timeSegment": { # A time period inside of an example that has a time dimension (e.g. video). # The time segment of the video to which object tracking applies.
"endTimeOffset": "A String", # End of the time segment (exclusive), represented as the duration since the example start.
"startTimeOffset": "A String", # Start of the time segment (inclusive), represented as the duration since the example start.
},
},
},
"name": "A String", # Output only. Unique name of this annotation, format is: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/{annotated_dataset}/examples/{example_id}/annotations/{annotation_id}
},
],
"imagePayload": { # Container of information about an image. # The image payload, a container of the image bytes/uri.
"imageThumbnail": "A String", # A byte string of a thumbnail image.
"imageUri": "A String", # Image uri from the user bucket.
"mimeType": "A String", # Image format.
"signedUri": "A String", # Signed uri of the image file in the service bucket.
},
"name": "A String", # Output only. Name of the example, in format of: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}/examples/{example_id}
"textPayload": { # Container of information about a piece of text. # The text payload, a container of the text content.
"textContent": "A String", # Text content.
},
"videoPayload": { # Container of information of a video. # The video payload, a container of the video uri.
"frameRate": 3.14, # FPS of the video.
"mimeType": "A String", # Video format.
"signedUri": "A String", # Signed uri of the video file in the service bucket.
"videoThumbnails": [ # The list of video thumbnails.
{ # Container of information of a video thumbnail.
"thumbnail": "A String", # A byte string of the video frame.
"timeOffset": "A String", # Time offset relative to the beginning of the video, corresponding to the video frame where the thumbnail has been extracted from.
},
],
"videoUri": "A String", # Video uri from the user bucket.
},
},
],
"nextPageToken": "A String", # A token to retrieve next page of results.
}</pre>
</div>
<div class="method">
<code class="details" id="list_next">list_next()</code>
<pre>Retrieves the next page of results.
Args:
previous_request: The request for the previous page. (required)
previous_response: The response from the request for the previous page. (required)
Returns:
A request object that you can call 'execute()' on to request the next
page. Returns None if there are no more items in the collection.
</pre>
</div>
</body></html>
|
