1// Copyright 2020 Google LLC 2// 3// Licensed under the Apache License, Version 2.0 (the "License"); 4// you may not use this file except in compliance with the License. 5// You may obtain a copy of the License at 6// 7// http://www.apache.org/licenses/LICENSE-2.0 8// 9// Unless required by applicable law or agreed to in writing, software 10// distributed under the License is distributed on an "AS IS" BASIS, 11// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12// See the License for the specific language governing permissions and 13// limitations under the License. 14 15// Code generated by protoc-gen-go. DO NOT EDIT. 16// versions: 17// protoc-gen-go v1.26.0 18// protoc v3.12.2 19// source: google/cloud/automl/v1beta1/classification.proto 20 21package automl 22 23import ( 24 reflect "reflect" 25 sync "sync" 26 27 _ "google.golang.org/genproto/googleapis/api/annotations" 28 protoreflect "google.golang.org/protobuf/reflect/protoreflect" 29 protoimpl "google.golang.org/protobuf/runtime/protoimpl" 30) 31 32const ( 33 // Verify that this generated code is sufficiently up-to-date. 34 _ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion) 35 // Verify that runtime/protoimpl is sufficiently up-to-date. 36 _ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20) 37) 38 39// Type of the classification problem. 40type ClassificationType int32 41 42const ( 43 // An un-set value of this enum. 44 ClassificationType_CLASSIFICATION_TYPE_UNSPECIFIED ClassificationType = 0 45 // At most one label is allowed per example. 46 ClassificationType_MULTICLASS ClassificationType = 1 47 // Multiple labels are allowed for one example. 48 ClassificationType_MULTILABEL ClassificationType = 2 49) 50 51// Enum value maps for ClassificationType. 52var ( 53 ClassificationType_name = map[int32]string{ 54 0: "CLASSIFICATION_TYPE_UNSPECIFIED", 55 1: "MULTICLASS", 56 2: "MULTILABEL", 57 } 58 ClassificationType_value = map[string]int32{ 59 "CLASSIFICATION_TYPE_UNSPECIFIED": 0, 60 "MULTICLASS": 1, 61 "MULTILABEL": 2, 62 } 63) 64 65func (x ClassificationType) Enum() *ClassificationType { 66 p := new(ClassificationType) 67 *p = x 68 return p 69} 70 71func (x ClassificationType) String() string { 72 return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) 73} 74 75func (ClassificationType) Descriptor() protoreflect.EnumDescriptor { 76 return file_google_cloud_automl_v1beta1_classification_proto_enumTypes[0].Descriptor() 77} 78 79func (ClassificationType) Type() protoreflect.EnumType { 80 return &file_google_cloud_automl_v1beta1_classification_proto_enumTypes[0] 81} 82 83func (x ClassificationType) Number() protoreflect.EnumNumber { 84 return protoreflect.EnumNumber(x) 85} 86 87// Deprecated: Use ClassificationType.Descriptor instead. 88func (ClassificationType) EnumDescriptor() ([]byte, []int) { 89 return file_google_cloud_automl_v1beta1_classification_proto_rawDescGZIP(), []int{0} 90} 91 92// Contains annotation details specific to classification. 93type ClassificationAnnotation struct { 94 state protoimpl.MessageState 95 sizeCache protoimpl.SizeCache 96 unknownFields protoimpl.UnknownFields 97 98 // Output only. A confidence estimate between 0.0 and 1.0. A higher value 99 // means greater confidence that the annotation is positive. If a user 100 // approves an annotation as negative or positive, the score value remains 101 // unchanged. If a user creates an annotation, the score is 0 for negative or 102 // 1 for positive. 103 Score float32 `protobuf:"fixed32,1,opt,name=score,proto3" json:"score,omitempty"` 104} 105 106func (x *ClassificationAnnotation) Reset() { 107 *x = ClassificationAnnotation{} 108 if protoimpl.UnsafeEnabled { 109 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[0] 110 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 111 ms.StoreMessageInfo(mi) 112 } 113} 114 115func (x *ClassificationAnnotation) String() string { 116 return protoimpl.X.MessageStringOf(x) 117} 118 119func (*ClassificationAnnotation) ProtoMessage() {} 120 121func (x *ClassificationAnnotation) ProtoReflect() protoreflect.Message { 122 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[0] 123 if protoimpl.UnsafeEnabled && x != nil { 124 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 125 if ms.LoadMessageInfo() == nil { 126 ms.StoreMessageInfo(mi) 127 } 128 return ms 129 } 130 return mi.MessageOf(x) 131} 132 133// Deprecated: Use ClassificationAnnotation.ProtoReflect.Descriptor instead. 134func (*ClassificationAnnotation) Descriptor() ([]byte, []int) { 135 return file_google_cloud_automl_v1beta1_classification_proto_rawDescGZIP(), []int{0} 136} 137 138func (x *ClassificationAnnotation) GetScore() float32 { 139 if x != nil { 140 return x.Score 141 } 142 return 0 143} 144 145// Contains annotation details specific to video classification. 146type VideoClassificationAnnotation struct { 147 state protoimpl.MessageState 148 sizeCache protoimpl.SizeCache 149 unknownFields protoimpl.UnknownFields 150 151 // Output only. Expresses the type of video classification. Possible values: 152 // 153 // * `segment` - Classification done on a specified by user 154 // time segment of a video. AnnotationSpec is answered to be present 155 // in that time segment, if it is present in any part of it. The video 156 // ML model evaluations are done only for this type of classification. 157 // 158 // * `shot`- Shot-level classification. 159 // AutoML Video Intelligence determines the boundaries 160 // for each camera shot in the entire segment of the video that user 161 // specified in the request configuration. AutoML Video Intelligence 162 // then returns labels and their confidence scores for each detected 163 // shot, along with the start and end time of the shot. 164 // WARNING: Model evaluation is not done for this classification type, 165 // the quality of it depends on training data, but there are no 166 // metrics provided to describe that quality. 167 // 168 // * `1s_interval` - AutoML Video Intelligence returns labels and their 169 // confidence scores for each second of the entire segment of the video 170 // that user specified in the request configuration. 171 // WARNING: Model evaluation is not done for this classification type, 172 // the quality of it depends on training data, but there are no 173 // metrics provided to describe that quality. 174 Type string `protobuf:"bytes,1,opt,name=type,proto3" json:"type,omitempty"` 175 // Output only . The classification details of this annotation. 176 ClassificationAnnotation *ClassificationAnnotation `protobuf:"bytes,2,opt,name=classification_annotation,json=classificationAnnotation,proto3" json:"classification_annotation,omitempty"` 177 // Output only . The time segment of the video to which the 178 // annotation applies. 179 TimeSegment *TimeSegment `protobuf:"bytes,3,opt,name=time_segment,json=timeSegment,proto3" json:"time_segment,omitempty"` 180} 181 182func (x *VideoClassificationAnnotation) Reset() { 183 *x = VideoClassificationAnnotation{} 184 if protoimpl.UnsafeEnabled { 185 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[1] 186 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 187 ms.StoreMessageInfo(mi) 188 } 189} 190 191func (x *VideoClassificationAnnotation) String() string { 192 return protoimpl.X.MessageStringOf(x) 193} 194 195func (*VideoClassificationAnnotation) ProtoMessage() {} 196 197func (x *VideoClassificationAnnotation) ProtoReflect() protoreflect.Message { 198 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[1] 199 if protoimpl.UnsafeEnabled && x != nil { 200 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 201 if ms.LoadMessageInfo() == nil { 202 ms.StoreMessageInfo(mi) 203 } 204 return ms 205 } 206 return mi.MessageOf(x) 207} 208 209// Deprecated: Use VideoClassificationAnnotation.ProtoReflect.Descriptor instead. 210func (*VideoClassificationAnnotation) Descriptor() ([]byte, []int) { 211 return file_google_cloud_automl_v1beta1_classification_proto_rawDescGZIP(), []int{1} 212} 213 214func (x *VideoClassificationAnnotation) GetType() string { 215 if x != nil { 216 return x.Type 217 } 218 return "" 219} 220 221func (x *VideoClassificationAnnotation) GetClassificationAnnotation() *ClassificationAnnotation { 222 if x != nil { 223 return x.ClassificationAnnotation 224 } 225 return nil 226} 227 228func (x *VideoClassificationAnnotation) GetTimeSegment() *TimeSegment { 229 if x != nil { 230 return x.TimeSegment 231 } 232 return nil 233} 234 235// Model evaluation metrics for classification problems. 236// Note: For Video Classification this metrics only describe quality of the 237// Video Classification predictions of "segment_classification" type. 238type ClassificationEvaluationMetrics struct { 239 state protoimpl.MessageState 240 sizeCache protoimpl.SizeCache 241 unknownFields protoimpl.UnknownFields 242 243 // Output only. The Area Under Precision-Recall Curve metric. Micro-averaged 244 // for the overall evaluation. 245 AuPrc float32 `protobuf:"fixed32,1,opt,name=au_prc,json=auPrc,proto3" json:"au_prc,omitempty"` 246 // Output only. The Area Under Precision-Recall Curve metric based on priors. 247 // Micro-averaged for the overall evaluation. 248 // Deprecated. 249 // 250 // Deprecated: Do not use. 251 BaseAuPrc float32 `protobuf:"fixed32,2,opt,name=base_au_prc,json=baseAuPrc,proto3" json:"base_au_prc,omitempty"` 252 // Output only. The Area Under Receiver Operating Characteristic curve metric. 253 // Micro-averaged for the overall evaluation. 254 AuRoc float32 `protobuf:"fixed32,6,opt,name=au_roc,json=auRoc,proto3" json:"au_roc,omitempty"` 255 // Output only. The Log Loss metric. 256 LogLoss float32 `protobuf:"fixed32,7,opt,name=log_loss,json=logLoss,proto3" json:"log_loss,omitempty"` 257 // Output only. Metrics for each confidence_threshold in 258 // 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and 259 // position_threshold = INT32_MAX_VALUE. 260 // ROC and precision-recall curves, and other aggregated metrics are derived 261 // from them. The confidence metrics entries may also be supplied for 262 // additional values of position_threshold, but from these no aggregated 263 // metrics are computed. 264 ConfidenceMetricsEntry []*ClassificationEvaluationMetrics_ConfidenceMetricsEntry `protobuf:"bytes,3,rep,name=confidence_metrics_entry,json=confidenceMetricsEntry,proto3" json:"confidence_metrics_entry,omitempty"` 265 // Output only. Confusion matrix of the evaluation. 266 // Only set for MULTICLASS classification problems where number 267 // of labels is no more than 10. 268 // Only set for model level evaluation, not for evaluation per label. 269 ConfusionMatrix *ClassificationEvaluationMetrics_ConfusionMatrix `protobuf:"bytes,4,opt,name=confusion_matrix,json=confusionMatrix,proto3" json:"confusion_matrix,omitempty"` 270 // Output only. The annotation spec ids used for this evaluation. 271 AnnotationSpecId []string `protobuf:"bytes,5,rep,name=annotation_spec_id,json=annotationSpecId,proto3" json:"annotation_spec_id,omitempty"` 272} 273 274func (x *ClassificationEvaluationMetrics) Reset() { 275 *x = ClassificationEvaluationMetrics{} 276 if protoimpl.UnsafeEnabled { 277 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[2] 278 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 279 ms.StoreMessageInfo(mi) 280 } 281} 282 283func (x *ClassificationEvaluationMetrics) String() string { 284 return protoimpl.X.MessageStringOf(x) 285} 286 287func (*ClassificationEvaluationMetrics) ProtoMessage() {} 288 289func (x *ClassificationEvaluationMetrics) ProtoReflect() protoreflect.Message { 290 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[2] 291 if protoimpl.UnsafeEnabled && x != nil { 292 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 293 if ms.LoadMessageInfo() == nil { 294 ms.StoreMessageInfo(mi) 295 } 296 return ms 297 } 298 return mi.MessageOf(x) 299} 300 301// Deprecated: Use ClassificationEvaluationMetrics.ProtoReflect.Descriptor instead. 302func (*ClassificationEvaluationMetrics) Descriptor() ([]byte, []int) { 303 return file_google_cloud_automl_v1beta1_classification_proto_rawDescGZIP(), []int{2} 304} 305 306func (x *ClassificationEvaluationMetrics) GetAuPrc() float32 { 307 if x != nil { 308 return x.AuPrc 309 } 310 return 0 311} 312 313// Deprecated: Do not use. 314func (x *ClassificationEvaluationMetrics) GetBaseAuPrc() float32 { 315 if x != nil { 316 return x.BaseAuPrc 317 } 318 return 0 319} 320 321func (x *ClassificationEvaluationMetrics) GetAuRoc() float32 { 322 if x != nil { 323 return x.AuRoc 324 } 325 return 0 326} 327 328func (x *ClassificationEvaluationMetrics) GetLogLoss() float32 { 329 if x != nil { 330 return x.LogLoss 331 } 332 return 0 333} 334 335func (x *ClassificationEvaluationMetrics) GetConfidenceMetricsEntry() []*ClassificationEvaluationMetrics_ConfidenceMetricsEntry { 336 if x != nil { 337 return x.ConfidenceMetricsEntry 338 } 339 return nil 340} 341 342func (x *ClassificationEvaluationMetrics) GetConfusionMatrix() *ClassificationEvaluationMetrics_ConfusionMatrix { 343 if x != nil { 344 return x.ConfusionMatrix 345 } 346 return nil 347} 348 349func (x *ClassificationEvaluationMetrics) GetAnnotationSpecId() []string { 350 if x != nil { 351 return x.AnnotationSpecId 352 } 353 return nil 354} 355 356// Metrics for a single confidence threshold. 357type ClassificationEvaluationMetrics_ConfidenceMetricsEntry struct { 358 state protoimpl.MessageState 359 sizeCache protoimpl.SizeCache 360 unknownFields protoimpl.UnknownFields 361 362 // Output only. Metrics are computed with an assumption that the model 363 // never returns predictions with score lower than this value. 364 ConfidenceThreshold float32 `protobuf:"fixed32,1,opt,name=confidence_threshold,json=confidenceThreshold,proto3" json:"confidence_threshold,omitempty"` 365 // Output only. Metrics are computed with an assumption that the model 366 // always returns at most this many predictions (ordered by their score, 367 // descendingly), but they all still need to meet the confidence_threshold. 368 PositionThreshold int32 `protobuf:"varint,14,opt,name=position_threshold,json=positionThreshold,proto3" json:"position_threshold,omitempty"` 369 // Output only. Recall (True Positive Rate) for the given confidence 370 // threshold. 371 Recall float32 `protobuf:"fixed32,2,opt,name=recall,proto3" json:"recall,omitempty"` 372 // Output only. Precision for the given confidence threshold. 373 Precision float32 `protobuf:"fixed32,3,opt,name=precision,proto3" json:"precision,omitempty"` 374 // Output only. False Positive Rate for the given confidence threshold. 375 FalsePositiveRate float32 `protobuf:"fixed32,8,opt,name=false_positive_rate,json=falsePositiveRate,proto3" json:"false_positive_rate,omitempty"` 376 // Output only. The harmonic mean of recall and precision. 377 F1Score float32 `protobuf:"fixed32,4,opt,name=f1_score,json=f1Score,proto3" json:"f1_score,omitempty"` 378 // Output only. The Recall (True Positive Rate) when only considering the 379 // label that has the highest prediction score and not below the confidence 380 // threshold for each example. 381 RecallAt1 float32 `protobuf:"fixed32,5,opt,name=recall_at1,json=recallAt1,proto3" json:"recall_at1,omitempty"` 382 // Output only. The precision when only considering the label that has the 383 // highest prediction score and not below the confidence threshold for each 384 // example. 385 PrecisionAt1 float32 `protobuf:"fixed32,6,opt,name=precision_at1,json=precisionAt1,proto3" json:"precision_at1,omitempty"` 386 // Output only. The False Positive Rate when only considering the label that 387 // has the highest prediction score and not below the confidence threshold 388 // for each example. 389 FalsePositiveRateAt1 float32 `protobuf:"fixed32,9,opt,name=false_positive_rate_at1,json=falsePositiveRateAt1,proto3" json:"false_positive_rate_at1,omitempty"` 390 // Output only. The harmonic mean of [recall_at1][google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.recall_at1] and [precision_at1][google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.precision_at1]. 391 F1ScoreAt1 float32 `protobuf:"fixed32,7,opt,name=f1_score_at1,json=f1ScoreAt1,proto3" json:"f1_score_at1,omitempty"` 392 // Output only. The number of model created labels that match a ground truth 393 // label. 394 TruePositiveCount int64 `protobuf:"varint,10,opt,name=true_positive_count,json=truePositiveCount,proto3" json:"true_positive_count,omitempty"` 395 // Output only. The number of model created labels that do not match a 396 // ground truth label. 397 FalsePositiveCount int64 `protobuf:"varint,11,opt,name=false_positive_count,json=falsePositiveCount,proto3" json:"false_positive_count,omitempty"` 398 // Output only. The number of ground truth labels that are not matched 399 // by a model created label. 400 FalseNegativeCount int64 `protobuf:"varint,12,opt,name=false_negative_count,json=falseNegativeCount,proto3" json:"false_negative_count,omitempty"` 401 // Output only. The number of labels that were not created by the model, 402 // but if they would, they would not match a ground truth label. 403 TrueNegativeCount int64 `protobuf:"varint,13,opt,name=true_negative_count,json=trueNegativeCount,proto3" json:"true_negative_count,omitempty"` 404} 405 406func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) Reset() { 407 *x = ClassificationEvaluationMetrics_ConfidenceMetricsEntry{} 408 if protoimpl.UnsafeEnabled { 409 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[3] 410 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 411 ms.StoreMessageInfo(mi) 412 } 413} 414 415func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) String() string { 416 return protoimpl.X.MessageStringOf(x) 417} 418 419func (*ClassificationEvaluationMetrics_ConfidenceMetricsEntry) ProtoMessage() {} 420 421func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) ProtoReflect() protoreflect.Message { 422 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[3] 423 if protoimpl.UnsafeEnabled && x != nil { 424 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 425 if ms.LoadMessageInfo() == nil { 426 ms.StoreMessageInfo(mi) 427 } 428 return ms 429 } 430 return mi.MessageOf(x) 431} 432 433// Deprecated: Use ClassificationEvaluationMetrics_ConfidenceMetricsEntry.ProtoReflect.Descriptor instead. 434func (*ClassificationEvaluationMetrics_ConfidenceMetricsEntry) Descriptor() ([]byte, []int) { 435 return file_google_cloud_automl_v1beta1_classification_proto_rawDescGZIP(), []int{2, 0} 436} 437 438func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetConfidenceThreshold() float32 { 439 if x != nil { 440 return x.ConfidenceThreshold 441 } 442 return 0 443} 444 445func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetPositionThreshold() int32 { 446 if x != nil { 447 return x.PositionThreshold 448 } 449 return 0 450} 451 452func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetRecall() float32 { 453 if x != nil { 454 return x.Recall 455 } 456 return 0 457} 458 459func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetPrecision() float32 { 460 if x != nil { 461 return x.Precision 462 } 463 return 0 464} 465 466func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetFalsePositiveRate() float32 { 467 if x != nil { 468 return x.FalsePositiveRate 469 } 470 return 0 471} 472 473func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetF1Score() float32 { 474 if x != nil { 475 return x.F1Score 476 } 477 return 0 478} 479 480func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetRecallAt1() float32 { 481 if x != nil { 482 return x.RecallAt1 483 } 484 return 0 485} 486 487func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetPrecisionAt1() float32 { 488 if x != nil { 489 return x.PrecisionAt1 490 } 491 return 0 492} 493 494func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetFalsePositiveRateAt1() float32 { 495 if x != nil { 496 return x.FalsePositiveRateAt1 497 } 498 return 0 499} 500 501func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetF1ScoreAt1() float32 { 502 if x != nil { 503 return x.F1ScoreAt1 504 } 505 return 0 506} 507 508func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetTruePositiveCount() int64 { 509 if x != nil { 510 return x.TruePositiveCount 511 } 512 return 0 513} 514 515func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetFalsePositiveCount() int64 { 516 if x != nil { 517 return x.FalsePositiveCount 518 } 519 return 0 520} 521 522func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetFalseNegativeCount() int64 { 523 if x != nil { 524 return x.FalseNegativeCount 525 } 526 return 0 527} 528 529func (x *ClassificationEvaluationMetrics_ConfidenceMetricsEntry) GetTrueNegativeCount() int64 { 530 if x != nil { 531 return x.TrueNegativeCount 532 } 533 return 0 534} 535 536// Confusion matrix of the model running the classification. 537type ClassificationEvaluationMetrics_ConfusionMatrix struct { 538 state protoimpl.MessageState 539 sizeCache protoimpl.SizeCache 540 unknownFields protoimpl.UnknownFields 541 542 // Output only. IDs of the annotation specs used in the confusion matrix. 543 // For Tables CLASSIFICATION 544 // 545 // [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] 546 // only list of [annotation_spec_display_name-s][] is populated. 547 AnnotationSpecId []string `protobuf:"bytes,1,rep,name=annotation_spec_id,json=annotationSpecId,proto3" json:"annotation_spec_id,omitempty"` 548 // Output only. Display name of the annotation specs used in the confusion 549 // matrix, as they were at the moment of the evaluation. For Tables 550 // CLASSIFICATION 551 // 552 // [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type], 553 // distinct values of the target column at the moment of the model 554 // evaluation are populated here. 555 DisplayName []string `protobuf:"bytes,3,rep,name=display_name,json=displayName,proto3" json:"display_name,omitempty"` 556 // Output only. Rows in the confusion matrix. The number of rows is equal to 557 // the size of `annotation_spec_id`. 558 // `row[i].example_count[j]` is the number of examples that have ground 559 // truth of the `annotation_spec_id[i]` and are predicted as 560 // `annotation_spec_id[j]` by the model being evaluated. 561 Row []*ClassificationEvaluationMetrics_ConfusionMatrix_Row `protobuf:"bytes,2,rep,name=row,proto3" json:"row,omitempty"` 562} 563 564func (x *ClassificationEvaluationMetrics_ConfusionMatrix) Reset() { 565 *x = ClassificationEvaluationMetrics_ConfusionMatrix{} 566 if protoimpl.UnsafeEnabled { 567 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[4] 568 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 569 ms.StoreMessageInfo(mi) 570 } 571} 572 573func (x *ClassificationEvaluationMetrics_ConfusionMatrix) String() string { 574 return protoimpl.X.MessageStringOf(x) 575} 576 577func (*ClassificationEvaluationMetrics_ConfusionMatrix) ProtoMessage() {} 578 579func (x *ClassificationEvaluationMetrics_ConfusionMatrix) ProtoReflect() protoreflect.Message { 580 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[4] 581 if protoimpl.UnsafeEnabled && x != nil { 582 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 583 if ms.LoadMessageInfo() == nil { 584 ms.StoreMessageInfo(mi) 585 } 586 return ms 587 } 588 return mi.MessageOf(x) 589} 590 591// Deprecated: Use ClassificationEvaluationMetrics_ConfusionMatrix.ProtoReflect.Descriptor instead. 592func (*ClassificationEvaluationMetrics_ConfusionMatrix) Descriptor() ([]byte, []int) { 593 return file_google_cloud_automl_v1beta1_classification_proto_rawDescGZIP(), []int{2, 1} 594} 595 596func (x *ClassificationEvaluationMetrics_ConfusionMatrix) GetAnnotationSpecId() []string { 597 if x != nil { 598 return x.AnnotationSpecId 599 } 600 return nil 601} 602 603func (x *ClassificationEvaluationMetrics_ConfusionMatrix) GetDisplayName() []string { 604 if x != nil { 605 return x.DisplayName 606 } 607 return nil 608} 609 610func (x *ClassificationEvaluationMetrics_ConfusionMatrix) GetRow() []*ClassificationEvaluationMetrics_ConfusionMatrix_Row { 611 if x != nil { 612 return x.Row 613 } 614 return nil 615} 616 617// Output only. A row in the confusion matrix. 618type ClassificationEvaluationMetrics_ConfusionMatrix_Row struct { 619 state protoimpl.MessageState 620 sizeCache protoimpl.SizeCache 621 unknownFields protoimpl.UnknownFields 622 623 // Output only. Value of the specific cell in the confusion matrix. 624 // The number of values each row has (i.e. the length of the row) is equal 625 // to the length of the `annotation_spec_id` field or, if that one is not 626 // populated, length of the [display_name][google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.display_name] field. 627 ExampleCount []int32 `protobuf:"varint,1,rep,packed,name=example_count,json=exampleCount,proto3" json:"example_count,omitempty"` 628} 629 630func (x *ClassificationEvaluationMetrics_ConfusionMatrix_Row) Reset() { 631 *x = ClassificationEvaluationMetrics_ConfusionMatrix_Row{} 632 if protoimpl.UnsafeEnabled { 633 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[5] 634 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 635 ms.StoreMessageInfo(mi) 636 } 637} 638 639func (x *ClassificationEvaluationMetrics_ConfusionMatrix_Row) String() string { 640 return protoimpl.X.MessageStringOf(x) 641} 642 643func (*ClassificationEvaluationMetrics_ConfusionMatrix_Row) ProtoMessage() {} 644 645func (x *ClassificationEvaluationMetrics_ConfusionMatrix_Row) ProtoReflect() protoreflect.Message { 646 mi := &file_google_cloud_automl_v1beta1_classification_proto_msgTypes[5] 647 if protoimpl.UnsafeEnabled && x != nil { 648 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 649 if ms.LoadMessageInfo() == nil { 650 ms.StoreMessageInfo(mi) 651 } 652 return ms 653 } 654 return mi.MessageOf(x) 655} 656 657// Deprecated: Use ClassificationEvaluationMetrics_ConfusionMatrix_Row.ProtoReflect.Descriptor instead. 658func (*ClassificationEvaluationMetrics_ConfusionMatrix_Row) Descriptor() ([]byte, []int) { 659 return file_google_cloud_automl_v1beta1_classification_proto_rawDescGZIP(), []int{2, 1, 0} 660} 661 662func (x *ClassificationEvaluationMetrics_ConfusionMatrix_Row) GetExampleCount() []int32 { 663 if x != nil { 664 return x.ExampleCount 665 } 666 return nil 667} 668 669var 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google.cloud.automl.v1beta1.ClassificationType 818 (*ClassificationAnnotation)(nil), // 1: google.cloud.automl.v1beta1.ClassificationAnnotation 819 (*VideoClassificationAnnotation)(nil), // 2: google.cloud.automl.v1beta1.VideoClassificationAnnotation 820 (*ClassificationEvaluationMetrics)(nil), // 3: google.cloud.automl.v1beta1.ClassificationEvaluationMetrics 821 (*ClassificationEvaluationMetrics_ConfidenceMetricsEntry)(nil), // 4: google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry 822 (*ClassificationEvaluationMetrics_ConfusionMatrix)(nil), // 5: google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix 823 (*ClassificationEvaluationMetrics_ConfusionMatrix_Row)(nil), // 6: google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row 824 (*TimeSegment)(nil), // 7: google.cloud.automl.v1beta1.TimeSegment 825} 826var file_google_cloud_automl_v1beta1_classification_proto_depIdxs = []int32{ 827 1, // 0: google.cloud.automl.v1beta1.VideoClassificationAnnotation.classification_annotation:type_name -> google.cloud.automl.v1beta1.ClassificationAnnotation 828 7, // 1: google.cloud.automl.v1beta1.VideoClassificationAnnotation.time_segment:type_name -> google.cloud.automl.v1beta1.TimeSegment 829 4, // 2: google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.confidence_metrics_entry:type_name -> google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry 830 5, // 3: google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.confusion_matrix:type_name -> google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix 831 6, // 4: google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.row:type_name -> google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row 832 5, // [5:5] is the sub-list for method output_type 833 5, // [5:5] is the sub-list for method input_type 834 5, // [5:5] is the sub-list for extension type_name 835 5, // [5:5] is the sub-list for extension extendee 836 0, // [0:5] is the sub-list for field type_name 837} 838 839func init() { file_google_cloud_automl_v1beta1_classification_proto_init() } 840func file_google_cloud_automl_v1beta1_classification_proto_init() { 841 if File_google_cloud_automl_v1beta1_classification_proto != nil { 842 return 843 } 844 file_google_cloud_automl_v1beta1_temporal_proto_init() 845 if !protoimpl.UnsafeEnabled { 846 file_google_cloud_automl_v1beta1_classification_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} { 847 switch v := v.(*ClassificationAnnotation); i { 848 case 0: 849 return &v.state 850 case 1: 851 return &v.sizeCache 852 case 2: 853 return &v.unknownFields 854 default: 855 return nil 856 } 857 } 858 file_google_cloud_automl_v1beta1_classification_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} { 859 switch v := v.(*VideoClassificationAnnotation); i { 860 case 0: 861 return &v.state 862 case 1: 863 return &v.sizeCache 864 case 2: 865 return &v.unknownFields 866 default: 867 return nil 868 } 869 } 870 file_google_cloud_automl_v1beta1_classification_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} { 871 switch v := v.(*ClassificationEvaluationMetrics); i { 872 case 0: 873 return &v.state 874 case 1: 875 return &v.sizeCache 876 case 2: 877 return &v.unknownFields 878 default: 879 return nil 880 } 881 } 882 file_google_cloud_automl_v1beta1_classification_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} { 883 switch v := v.(*ClassificationEvaluationMetrics_ConfidenceMetricsEntry); i { 884 case 0: 885 return &v.state 886 case 1: 887 return &v.sizeCache 888 case 2: 889 return &v.unknownFields 890 default: 891 return nil 892 } 893 } 894 file_google_cloud_automl_v1beta1_classification_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} { 895 switch v := v.(*ClassificationEvaluationMetrics_ConfusionMatrix); i { 896 case 0: 897 return &v.state 898 case 1: 899 return &v.sizeCache 900 case 2: 901 return &v.unknownFields 902 default: 903 return nil 904 } 905 } 906 file_google_cloud_automl_v1beta1_classification_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} { 907 switch v := v.(*ClassificationEvaluationMetrics_ConfusionMatrix_Row); i { 908 case 0: 909 return &v.state 910 case 1: 911 return &v.sizeCache 912 case 2: 913 return &v.unknownFields 914 default: 915 return nil 916 } 917 } 918 } 919 type x struct{} 920 out := protoimpl.TypeBuilder{ 921 File: protoimpl.DescBuilder{ 922 GoPackagePath: reflect.TypeOf(x{}).PkgPath(), 923 RawDescriptor: file_google_cloud_automl_v1beta1_classification_proto_rawDesc, 924 NumEnums: 1, 925 NumMessages: 6, 926 NumExtensions: 0, 927 NumServices: 0, 928 }, 929 GoTypes: file_google_cloud_automl_v1beta1_classification_proto_goTypes, 930 DependencyIndexes: file_google_cloud_automl_v1beta1_classification_proto_depIdxs, 931 EnumInfos: file_google_cloud_automl_v1beta1_classification_proto_enumTypes, 932 MessageInfos: file_google_cloud_automl_v1beta1_classification_proto_msgTypes, 933 }.Build() 934 File_google_cloud_automl_v1beta1_classification_proto = out.File 935 file_google_cloud_automl_v1beta1_classification_proto_rawDesc = nil 936 file_google_cloud_automl_v1beta1_classification_proto_goTypes = nil 937 file_google_cloud_automl_v1beta1_classification_proto_depIdxs = nil 938} 939