const ::google::protobuf::Descriptor* ProposalParameter_descriptor_ = NULL;
const ::google::protobuf::internal::GeneratedMessageReflection*
ProposalParameter_reflection_ = NULL;
+const ::google::protobuf::Descriptor* PSROIPoolingParameter_descriptor_ = NULL;
+const ::google::protobuf::internal::GeneratedMessageReflection*
+ PSROIPoolingParameter_reflection_ = NULL;
const ::google::protobuf::EnumDescriptor* Type_descriptor_ = NULL;
const ::google::protobuf::EnumDescriptor* Phase_descriptor_ = NULL;
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(PriorBoxParameter, _internal_metadata_));
PriorBoxParameter_CodeType_descriptor_ = PriorBoxParameter_descriptor_->enum_type(0);
DetectionOutputParameter_descriptor_ = file->message_type(6);
- static const int DetectionOutputParameter_offsets_[9] = {
+ static const int DetectionOutputParameter_offsets_[10] = {
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(DetectionOutputParameter, num_classes_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(DetectionOutputParameter, share_location_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(DetectionOutputParameter, background_label_id_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(DetectionOutputParameter, variance_encoded_in_target_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(DetectionOutputParameter, keep_top_k_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(DetectionOutputParameter, confidence_threshold_),
+ GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(DetectionOutputParameter, normalized_bbox_),
};
DetectionOutputParameter_reflection_ =
::google::protobuf::internal::GeneratedMessageReflection::NewGeneratedMessageReflection(
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(ParamSpec, _internal_metadata_));
ParamSpec_DimCheckMode_descriptor_ = ParamSpec_descriptor_->enum_type(0);
LayerParameter_descriptor_ = file->message_type(15);
- static const int LayerParameter_offsets_[64] = {
+ static const int LayerParameter_offsets_[65] = {
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(LayerParameter, name_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(LayerParameter, type_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(LayerParameter, bottom_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(LayerParameter, prelu_param_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(LayerParameter, prior_box_param_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(LayerParameter, proposal_param_),
+ GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(LayerParameter, psroi_pooling_param_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(LayerParameter, python_param_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(LayerParameter, recurrent_param_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(LayerParameter, reduction_param_),
-1,
sizeof(ProposalParameter),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(ProposalParameter, _internal_metadata_));
+ PSROIPoolingParameter_descriptor_ = file->message_type(70);
+ static const int PSROIPoolingParameter_offsets_[3] = {
+ GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(PSROIPoolingParameter, spatial_scale_),
+ GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(PSROIPoolingParameter, output_dim_),
+ GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(PSROIPoolingParameter, group_size_),
+ };
+ PSROIPoolingParameter_reflection_ =
+ ::google::protobuf::internal::GeneratedMessageReflection::NewGeneratedMessageReflection(
+ PSROIPoolingParameter_descriptor_,
+ PSROIPoolingParameter::internal_default_instance(),
+ PSROIPoolingParameter_offsets_,
+ GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(PSROIPoolingParameter, _has_bits_),
+ -1,
+ -1,
+ sizeof(PSROIPoolingParameter),
+ GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(PSROIPoolingParameter, _internal_metadata_));
Type_descriptor_ = file->enum_type(0);
Phase_descriptor_ = file->enum_type(1);
}
ROIPoolingParameter_descriptor_, ROIPoolingParameter::internal_default_instance());
::google::protobuf::MessageFactory::InternalRegisterGeneratedMessage(
ProposalParameter_descriptor_, ProposalParameter::internal_default_instance());
+ ::google::protobuf::MessageFactory::InternalRegisterGeneratedMessage(
+ PSROIPoolingParameter_descriptor_, PSROIPoolingParameter::internal_default_instance());
}
} // namespace
delete ROIPoolingParameter_reflection_;
ProposalParameter_default_instance_.Shutdown();
delete ProposalParameter_reflection_;
+ PSROIPoolingParameter_default_instance_.Shutdown();
+ delete PSROIPoolingParameter_reflection_;
}
void protobuf_InitDefaults_opencv_2dcaffe_2eproto_impl() {
NormalizedBBox_default_instance_.DefaultConstruct();
ROIPoolingParameter_default_instance_.DefaultConstruct();
ProposalParameter_default_instance_.DefaultConstruct();
+ PSROIPoolingParameter_default_instance_.DefaultConstruct();
BlobShape_default_instance_.get_mutable()->InitAsDefaultInstance();
BlobProto_default_instance_.get_mutable()->InitAsDefaultInstance();
BlobProtoVector_default_instance_.get_mutable()->InitAsDefaultInstance();
NormalizedBBox_default_instance_.get_mutable()->InitAsDefaultInstance();
ROIPoolingParameter_default_instance_.get_mutable()->InitAsDefaultInstance();
ProposalParameter_default_instance_.get_mutable()->InitAsDefaultInstance();
+ PSROIPoolingParameter_default_instance_.get_mutable()->InitAsDefaultInstance();
}
GOOGLE_PROTOBUF_DECLARE_ONCE(protobuf_InitDefaults_opencv_2dcaffe_2eproto_once_);
"\006step_h\030\013 \001(\002\022\016\n\006step_w\030\014 \001(\002\022\023\n\006offset\030"
"\r \001(\002:\0030.5\022\020\n\010offset_h\030\016 \003(\002\022\020\n\010offset_w"
"\030\017 \003(\002\022\r\n\005width\030\020 \003(\002\022\016\n\006height\030\021 \003(\002\"\'\n"
- "\010CodeType\022\n\n\006CORNER\020\001\022\017\n\013CENTER_SIZE\020\002\"\222"
+ "\010CodeType\022\n\n\006CORNER\020\001\022\017\n\013CENTER_SIZE\020\002\"\261"
"\003\n\030DetectionOutputParameter\022\023\n\013num_class"
"es\030\001 \001(\r\022\034\n\016share_location\030\002 \001(\010:\004true\022\036"
"\n\023background_label_id\030\003 \001(\005:\0010\022\?\n\tnms_pa"
"Parameter.CodeType:\006CORNER\022)\n\032variance_e"
"ncoded_in_target\030\010 \001(\010:\005false\022\026\n\nkeep_to"
"p_k\030\007 \001(\005:\002-1\022\034\n\024confidence_threshold\030\t "
- "\001(\002\"\201\001\n\005Datum\022\020\n\010channels\030\001 \001(\005\022\016\n\006heigh"
- "t\030\002 \001(\005\022\r\n\005width\030\003 \001(\005\022\014\n\004data\030\004 \001(\014\022\r\n\005"
- "label\030\005 \001(\005\022\022\n\nfloat_data\030\006 \003(\002\022\026\n\007encod"
- "ed\030\007 \001(\010:\005false\"\221\002\n\017FillerParameter\022\026\n\004t"
- "ype\030\001 \001(\t:\010constant\022\020\n\005value\030\002 \001(\002:\0010\022\016\n"
- "\003min\030\003 \001(\002:\0010\022\016\n\003max\030\004 \001(\002:\0011\022\017\n\004mean\030\005 "
- "\001(\002:\0010\022\016\n\003std\030\006 \001(\002:\0011\022\022\n\006sparse\030\007 \001(\005:\002"
- "-1\022I\n\rvariance_norm\030\010 \001(\0162*.opencv_caffe"
- ".FillerParameter.VarianceNorm:\006FAN_IN\"4\n"
- "\014VarianceNorm\022\n\n\006FAN_IN\020\000\022\013\n\007FAN_OUT\020\001\022\013"
- "\n\007AVERAGE\020\002\"\252\002\n\014NetParameter\022\014\n\004name\030\001 \001"
- "(\t\022\r\n\005input\030\003 \003(\t\022,\n\013input_shape\030\010 \003(\0132\027"
- ".opencv_caffe.BlobShape\022\021\n\tinput_dim\030\004 \003"
- "(\005\022\035\n\016force_backward\030\005 \001(\010:\005false\022%\n\005sta"
- "te\030\006 \001(\0132\026.opencv_caffe.NetState\022\031\n\ndebu"
- "g_info\030\007 \001(\010:\005false\022+\n\005layer\030d \003(\0132\034.ope"
- "ncv_caffe.LayerParameter\022.\n\006layers\030\002 \003(\013"
- "2\036.opencv_caffe.V1LayerParameter\"\332\n\n\017Sol"
- "verParameter\022\013\n\003net\030\030 \001(\t\022-\n\tnet_param\030\031"
- " \001(\0132\032.opencv_caffe.NetParameter\022\021\n\ttrai"
- "n_net\030\001 \001(\t\022\020\n\010test_net\030\002 \003(\t\0223\n\017train_n"
- "et_param\030\025 \001(\0132\032.opencv_caffe.NetParamet"
- "er\0222\n\016test_net_param\030\026 \003(\0132\032.opencv_caff"
- "e.NetParameter\022+\n\013train_state\030\032 \001(\0132\026.op"
- "encv_caffe.NetState\022*\n\ntest_state\030\033 \003(\0132"
- "\026.opencv_caffe.NetState\022\021\n\ttest_iter\030\003 \003"
- "(\005\022\030\n\rtest_interval\030\004 \001(\005:\0010\022 \n\021test_com"
- "pute_loss\030\023 \001(\010:\005false\022!\n\023test_initializ"
- "ation\030 \001(\010:\004true\022\017\n\007base_lr\030\005 \001(\002\022\017\n\007di"
- "splay\030\006 \001(\005\022\027\n\014average_loss\030! \001(\005:\0011\022\020\n\010"
- "max_iter\030\007 \001(\005\022\024\n\titer_size\030$ \001(\005:\0011\022\021\n\t"
- "lr_policy\030\010 \001(\t\022\r\n\005gamma\030\t \001(\002\022\r\n\005power\030"
- "\n \001(\002\022\020\n\010momentum\030\013 \001(\002\022\024\n\014weight_decay\030"
- "\014 \001(\002\022\037\n\023regularization_type\030\035 \001(\t:\002L2\022\020"
- "\n\010stepsize\030\r \001(\005\022\021\n\tstepvalue\030\" \003(\005\022\032\n\016c"
- "lip_gradients\030# \001(\002:\002-1\022\023\n\010snapshot\030\016 \001("
- "\005:\0010\022\027\n\017snapshot_prefix\030\017 \001(\t\022\034\n\rsnapsho"
- "t_diff\030\020 \001(\010:\005false\022R\n\017snapshot_format\030%"
- " \001(\0162,.opencv_caffe.SolverParameter.Snap"
- "shotFormat:\013BINARYPROTO\022B\n\013solver_mode\030\021"
- " \001(\0162(.opencv_caffe.SolverParameter.Solv"
- "erMode:\003GPU\022\024\n\tdevice_id\030\022 \001(\005:\0010\022\027\n\013ran"
- "dom_seed\030\024 \001(\003:\002-1\022\021\n\004type\030( \001(\t:\003SGD\022\024\n"
- "\005delta\030\037 \001(\002:\0051e-08\022\030\n\tmomentum2\030\' \001(\002:\005"
- "0.999\022\027\n\trms_decay\030& \001(\002:\0040.99\022\031\n\ndebug_"
- "info\030\027 \001(\010:\005false\022\"\n\024snapshot_after_trai"
- "n\030\034 \001(\010:\004true\022B\n\013solver_type\030\036 \001(\0162(.ope"
- "ncv_caffe.SolverParameter.SolverType:\003SG"
- "D\"+\n\016SnapshotFormat\022\010\n\004HDF5\020\000\022\017\n\013BINARYP"
- "ROTO\020\001\"\036\n\nSolverMode\022\007\n\003CPU\020\000\022\007\n\003GPU\020\001\"U"
- "\n\nSolverType\022\007\n\003SGD\020\000\022\014\n\010NESTEROV\020\001\022\013\n\007A"
- "DAGRAD\020\002\022\013\n\007RMSPROP\020\003\022\014\n\010ADADELTA\020\004\022\010\n\004A"
- "DAM\020\005\"s\n\013SolverState\022\014\n\004iter\030\001 \001(\005\022\023\n\013le"
- "arned_net\030\002 \001(\t\022(\n\007history\030\003 \003(\0132\027.openc"
- "v_caffe.BlobProto\022\027\n\014current_step\030\004 \001(\005:"
- "\0010\"U\n\010NetState\022(\n\005phase\030\001 \001(\0162\023.opencv_c"
- "affe.Phase:\004TEST\022\020\n\005level\030\002 \001(\005:\0010\022\r\n\005st"
- "age\030\003 \003(\t\"z\n\014NetStateRule\022\"\n\005phase\030\001 \001(\016"
- "2\023.opencv_caffe.Phase\022\021\n\tmin_level\030\002 \001(\005"
- "\022\021\n\tmax_level\030\003 \001(\005\022\r\n\005stage\030\004 \003(\t\022\021\n\tno"
- "t_stage\030\005 \003(\t\"\252\001\n\tParamSpec\022\014\n\004name\030\001 \001("
- "\t\0228\n\nshare_mode\030\002 \001(\0162$.opencv_caffe.Par"
- "amSpec.DimCheckMode\022\022\n\007lr_mult\030\003 \001(\002:\0011\022"
- "\025\n\ndecay_mult\030\004 \001(\002:\0011\"*\n\014DimCheckMode\022\n"
- "\n\006STRICT\020\000\022\016\n\nPERMISSIVE\020\001\"\340\031\n\016LayerPara"
- "meter\022\014\n\004name\030\001 \001(\t\022\014\n\004type\030\002 \001(\t\022\016\n\006bot"
- "tom\030\003 \003(\t\022\013\n\003top\030\004 \003(\t\022\"\n\005phase\030\n \001(\0162\023."
- "opencv_caffe.Phase\022\023\n\013loss_weight\030\005 \003(\002\022"
- "&\n\005param\030\006 \003(\0132\027.opencv_caffe.ParamSpec\022"
- "&\n\005blobs\030\007 \003(\0132\027.opencv_caffe.BlobProto\022"
- "\026\n\016propagate_down\030\013 \003(\010\022+\n\007include\030\010 \003(\013"
- "2\032.opencv_caffe.NetStateRule\022+\n\007exclude\030"
- "\t \003(\0132\032.opencv_caffe.NetStateRule\022>\n\017tra"
- "nsform_param\030d \001(\0132%.opencv_caffe.Transf"
- "ormationParameter\022/\n\nloss_param\030e \001(\0132\033."
- "opencv_caffe.LossParameter\0227\n\016accuracy_p"
- "aram\030f \001(\0132\037.opencv_caffe.AccuracyParame"
- "ter\0223\n\014argmax_param\030g \001(\0132\035.opencv_caffe"
- ".ArgMaxParameter\022;\n\020batch_norm_param\030\213\001 "
- "\001(\0132 .opencv_caffe.BatchNormParameter\0220\n"
- "\nbias_param\030\215\001 \001(\0132\033.opencv_caffe.BiasPa"
- "rameter\0223\n\014concat_param\030h \001(\0132\035.opencv_c"
- "affe.ConcatParameter\022F\n\026contrastive_loss"
- "_param\030i \001(\0132&.opencv_caffe.ContrastiveL"
- "ossParameter\022=\n\021convolution_param\030j \001(\0132"
- "\".opencv_caffe.ConvolutionParameter\0220\n\nc"
- "rop_param\030\220\001 \001(\0132\033.opencv_caffe.CropPara"
- "meter\022/\n\ndata_param\030k \001(\0132\033.opencv_caffe"
- ".DataParameter\022G\n\026detection_output_param"
- "\030\223\001 \001(\0132&.opencv_caffe.DetectionOutputPa"
- "rameter\0225\n\rdropout_param\030l \001(\0132\036.opencv_"
- "caffe.DropoutParameter\022:\n\020dummy_data_par"
- "am\030m \001(\0132 .opencv_caffe.DummyDataParamet"
- "er\0225\n\reltwise_param\030n \001(\0132\036.opencv_caffe"
- ".EltwiseParameter\022.\n\telu_param\030\214\001 \001(\0132\032."
- "opencv_caffe.ELUParameter\0222\n\013embed_param"
- "\030\211\001 \001(\0132\034.opencv_caffe.EmbedParameter\022-\n"
- "\texp_param\030o \001(\0132\032.opencv_caffe.ExpParam"
- "eter\0226\n\rflatten_param\030\207\001 \001(\0132\036.opencv_ca"
- "ffe.FlattenParameter\0228\n\017hdf5_data_param\030"
- "p \001(\0132\037.opencv_caffe.HDF5DataParameter\022<"
- "\n\021hdf5_output_param\030q \001(\0132!.opencv_caffe"
- ".HDF5OutputParameter\022:\n\020hinge_loss_param"
- "\030r \001(\0132 .opencv_caffe.HingeLossParameter"
- "\022:\n\020image_data_param\030s \001(\0132 .opencv_caff"
- "e.ImageDataParameter\022@\n\023infogain_loss_pa"
- "ram\030t \001(\0132#.opencv_caffe.InfogainLossPar"
- "ameter\022@\n\023inner_product_param\030u \001(\0132#.op"
- "encv_caffe.InnerProductParameter\0222\n\013inpu"
- "t_param\030\217\001 \001(\0132\034.opencv_caffe.InputParam"
- "eter\022.\n\tlog_param\030\206\001 \001(\0132\032.opencv_caffe."
- "LogParameter\022-\n\tlrn_param\030v \001(\0132\032.opencv"
- "_caffe.LRNParameter\022<\n\021memory_data_param"
- "\030w \001(\0132!.opencv_caffe.MemoryDataParamete"
- "r\022-\n\tmvn_param\030x \001(\0132\032.opencv_caffe.MVNP"
- "arameter\0229\n\nnorm_param\030\225\001 \001(\0132$.opencv_c"
- "affe.NormalizeBBoxParameter\0226\n\rpermute_p"
- "aram\030\224\001 \001(\0132\036.opencv_caffe.PermuteParame"
- "ter\022:\n\017parameter_param\030\221\001 \001(\0132 .opencv_c"
- "affe.ParameterParameter\0225\n\rpooling_param"
- "\030y \001(\0132\036.opencv_caffe.PoolingParameter\0221"
- "\n\013power_param\030z \001(\0132\034.opencv_caffe.Power"
- "Parameter\0222\n\013prelu_param\030\203\001 \001(\0132\034.opencv"
- "_caffe.PReLUParameter\0229\n\017prior_box_param"
- "\030\226\001 \001(\0132\037.opencv_caffe.PriorBoxParameter"
- "\0228\n\016proposal_param\030\311\001 \001(\0132\037.opencv_caffe"
- ".ProposalParameter\0224\n\014python_param\030\202\001 \001("
- "\0132\035.opencv_caffe.PythonParameter\022:\n\017recu"
- "rrent_param\030\222\001 \001(\0132 .opencv_caffe.Recurr"
- "entParameter\022:\n\017reduction_param\030\210\001 \001(\0132 "
- ".opencv_caffe.ReductionParameter\022/\n\nrelu"
- "_param\030{ \001(\0132\033.opencv_caffe.ReLUParamete"
- "r\0226\n\rreshape_param\030\205\001 \001(\0132\036.opencv_caffe"
- ".ReshapeParameter\022\?\n\021roi_pooling_param\030\327"
- "\307\370\003 \001(\0132!.opencv_caffe.ROIPoolingParamet"
- "er\0222\n\013scale_param\030\216\001 \001(\0132\034.opencv_caffe."
- "ScaleParameter\0225\n\rsigmoid_param\030| \001(\0132\036."
- "opencv_caffe.SigmoidParameter\0225\n\rsoftmax"
- "_param\030} \001(\0132\036.opencv_caffe.SoftmaxParam"
- "eter\022.\n\tspp_param\030\204\001 \001(\0132\032.opencv_caffe."
- "SPPParameter\0221\n\013slice_param\030~ \001(\0132\034.open"
- "cv_caffe.SliceParameter\022/\n\ntanh_param\030\177 "
- "\001(\0132\033.opencv_caffe.TanHParameter\022:\n\017thre"
- "shold_param\030\200\001 \001(\0132 .opencv_caffe.Thresh"
- "oldParameter\0220\n\ntile_param\030\212\001 \001(\0132\033.open"
- "cv_caffe.TileParameter\022=\n\021window_data_pa"
- "ram\030\201\001 \001(\0132!.opencv_caffe.WindowDataPara"
- "meter\"\266\001\n\027TransformationParameter\022\020\n\005sca"
- "le\030\001 \001(\002:\0011\022\025\n\006mirror\030\002 \001(\010:\005false\022\024\n\tcr"
- "op_size\030\003 \001(\r:\0010\022\021\n\tmean_file\030\004 \001(\t\022\022\n\nm"
- "ean_value\030\005 \003(\002\022\032\n\013force_color\030\006 \001(\010:\005fa"
- "lse\022\031\n\nforce_gray\030\007 \001(\010:\005false\"\311\001\n\rLossP"
- "arameter\022\024\n\014ignore_label\030\001 \001(\005\022K\n\rnormal"
- "ization\030\003 \001(\0162-.opencv_caffe.LossParamet"
- "er.NormalizationMode:\005VALID\022\021\n\tnormalize"
- "\030\002 \001(\010\"B\n\021NormalizationMode\022\010\n\004FULL\020\000\022\t\n"
- "\005VALID\020\001\022\016\n\nBATCH_SIZE\020\002\022\010\n\004NONE\020\003\"L\n\021Ac"
- "curacyParameter\022\020\n\005top_k\030\001 \001(\r:\0011\022\017\n\004axi"
- "s\030\002 \001(\005:\0011\022\024\n\014ignore_label\030\003 \001(\005\"M\n\017ArgM"
- "axParameter\022\032\n\013out_max_val\030\001 \001(\010:\005false\022"
- "\020\n\005top_k\030\002 \001(\r:\0011\022\014\n\004axis\030\003 \001(\005\"9\n\017Conca"
- "tParameter\022\017\n\004axis\030\002 \001(\005:\0011\022\025\n\nconcat_di"
- "m\030\001 \001(\r:\0011\"j\n\022BatchNormParameter\022\030\n\020use_"
- "global_stats\030\001 \001(\010\022&\n\027moving_average_fra"
- "ction\030\002 \001(\002:\0050.999\022\022\n\003eps\030\003 \001(\002:\0051e-05\"d"
- "\n\rBiasParameter\022\017\n\004axis\030\001 \001(\005:\0011\022\023\n\010num_"
- "axes\030\002 \001(\005:\0011\022-\n\006filler\030\003 \001(\0132\035.opencv_c"
- "affe.FillerParameter\"L\n\030ContrastiveLossP"
- "arameter\022\021\n\006margin\030\001 \001(\002:\0011\022\035\n\016legacy_ve"
- "rsion\030\002 \001(\010:\005false\"\221\004\n\024ConvolutionParame"
- "ter\022\022\n\nnum_output\030\001 \001(\r\022\027\n\tbias_term\030\002 \001"
- "(\010:\004true\022\013\n\003pad\030\003 \003(\r\022\023\n\013kernel_size\030\004 \003"
- "(\r\022\016\n\006stride\030\006 \003(\r\022\020\n\010dilation\030\022 \003(\r\022\020\n\005"
- "pad_h\030\t \001(\r:\0010\022\020\n\005pad_w\030\n \001(\r:\0010\022\020\n\010kern"
- "el_h\030\013 \001(\r\022\020\n\010kernel_w\030\014 \001(\r\022\020\n\010stride_h"
- "\030\r \001(\r\022\020\n\010stride_w\030\016 \001(\r\022\020\n\005group\030\005 \001(\r:"
- "\0011\0224\n\rweight_filler\030\007 \001(\0132\035.opencv_caffe"
- ".FillerParameter\0222\n\013bias_filler\030\010 \001(\0132\035."
- "opencv_caffe.FillerParameter\022B\n\006engine\030\017"
- " \001(\0162).opencv_caffe.ConvolutionParameter"
- ".Engine:\007DEFAULT\022\017\n\004axis\030\020 \001(\005:\0011\022\036\n\017for"
- "ce_nd_im2col\030\021 \001(\010:\005false\"+\n\006Engine\022\013\n\007D"
- "EFAULT\020\000\022\t\n\005CAFFE\020\001\022\t\n\005CUDNN\020\002\"0\n\rCropPa"
- "rameter\022\017\n\004axis\030\001 \001(\005:\0012\022\016\n\006offset\030\002 \003(\r"
- "\"\253\002\n\rDataParameter\022\016\n\006source\030\001 \001(\t\022\022\n\nba"
- "tch_size\030\004 \001(\r\022\024\n\trand_skip\030\007 \001(\r:\0010\0228\n\007"
- "backend\030\010 \001(\0162\036.opencv_caffe.DataParamet"
- "er.DB:\007LEVELDB\022\020\n\005scale\030\002 \001(\002:\0011\022\021\n\tmean"
- "_file\030\003 \001(\t\022\024\n\tcrop_size\030\005 \001(\r:\0010\022\025\n\006mir"
- "ror\030\006 \001(\010:\005false\022\"\n\023force_encoded_color\030"
- "\t \001(\010:\005false\022\023\n\010prefetch\030\n \001(\r:\0014\"\033\n\002DB\022"
- "\013\n\007LEVELDB\020\000\022\010\n\004LMDB\020\001\"[\n\036NonMaximumSupp"
- "ressionParameter\022\032\n\rnms_threshold\030\001 \001(\002:"
- "\0030.3\022\r\n\005top_k\030\002 \001(\005\022\016\n\003eta\030\003 \001(\002:\0011\"\252\001\n\023"
- "SaveOutputParameter\022\030\n\020output_directory\030"
- "\001 \001(\t\022\032\n\022output_name_prefix\030\002 \001(\t\022\025\n\rout"
- "put_format\030\003 \001(\t\022\026\n\016label_map_file\030\004 \001(\t"
- "\022\026\n\016name_size_file\030\005 \001(\t\022\026\n\016num_test_ima"
- "ge\030\006 \001(\r\"I\n\020DropoutParameter\022\032\n\rdropout_"
- "ratio\030\001 \001(\002:\0030.5\022\031\n\013scale_train\030\002 \001(\010:\004t"
- "rue\"\256\001\n\022DummyDataParameter\0222\n\013data_fille"
- "r\030\001 \003(\0132\035.opencv_caffe.FillerParameter\022&"
- "\n\005shape\030\006 \003(\0132\027.opencv_caffe.BlobShape\022\013"
- "\n\003num\030\002 \003(\r\022\020\n\010channels\030\003 \003(\r\022\016\n\006height\030"
- "\004 \003(\r\022\r\n\005width\030\005 \003(\r\"\254\001\n\020EltwiseParamete"
- "r\022@\n\toperation\030\001 \001(\0162(.opencv_caffe.Eltw"
- "iseParameter.EltwiseOp:\003SUM\022\r\n\005coeff\030\002 \003"
- "(\002\022\036\n\020stable_prod_grad\030\003 \001(\010:\004true\"\'\n\tEl"
- "twiseOp\022\010\n\004PROD\020\000\022\007\n\003SUM\020\001\022\007\n\003MAX\020\002\" \n\014E"
- "LUParameter\022\020\n\005alpha\030\001 \001(\002:\0011\"\272\001\n\016EmbedP"
- "arameter\022\022\n\nnum_output\030\001 \001(\r\022\021\n\tinput_di"
- "m\030\002 \001(\r\022\027\n\tbias_term\030\003 \001(\010:\004true\0224\n\rweig"
- "ht_filler\030\004 \001(\0132\035.opencv_caffe.FillerPar"
- "ameter\0222\n\013bias_filler\030\005 \001(\0132\035.opencv_caf"
- "fe.FillerParameter\"D\n\014ExpParameter\022\020\n\004ba"
- "se\030\001 \001(\002:\002-1\022\020\n\005scale\030\002 \001(\002:\0011\022\020\n\005shift\030"
- "\003 \001(\002:\0010\"9\n\020FlattenParameter\022\017\n\004axis\030\001 \001"
- "(\005:\0011\022\024\n\010end_axis\030\002 \001(\005:\002-1\"O\n\021HDF5DataP"
- "arameter\022\016\n\006source\030\001 \001(\t\022\022\n\nbatch_size\030\002"
- " \001(\r\022\026\n\007shuffle\030\003 \001(\010:\005false\"(\n\023HDF5Outp"
- "utParameter\022\021\n\tfile_name\030\001 \001(\t\"e\n\022HingeL"
- "ossParameter\0227\n\004norm\030\001 \001(\0162%.opencv_caff"
- "e.HingeLossParameter.Norm:\002L1\"\026\n\004Norm\022\006\n"
- "\002L1\020\001\022\006\n\002L2\020\002\"\227\002\n\022ImageDataParameter\022\016\n\006"
- "source\030\001 \001(\t\022\025\n\nbatch_size\030\004 \001(\r:\0011\022\024\n\tr"
- "and_skip\030\007 \001(\r:\0010\022\026\n\007shuffle\030\010 \001(\010:\005fals"
- "e\022\025\n\nnew_height\030\t \001(\r:\0010\022\024\n\tnew_width\030\n "
- "\001(\r:\0010\022\026\n\010is_color\030\013 \001(\010:\004true\022\020\n\005scale\030"
- "\002 \001(\002:\0011\022\021\n\tmean_file\030\003 \001(\t\022\024\n\tcrop_size"
- "\030\005 \001(\r:\0010\022\025\n\006mirror\030\006 \001(\010:\005false\022\025\n\013root"
- "_folder\030\014 \001(\t:\000\"\'\n\025InfogainLossParameter"
- "\022\016\n\006source\030\001 \001(\t\"\331\001\n\025InnerProductParamet"
- "er\022\022\n\nnum_output\030\001 \001(\r\022\027\n\tbias_term\030\002 \001("
- "\010:\004true\0224\n\rweight_filler\030\003 \001(\0132\035.opencv_"
- "caffe.FillerParameter\0222\n\013bias_filler\030\004 \001"
- "(\0132\035.opencv_caffe.FillerParameter\022\017\n\004axi"
- "s\030\005 \001(\005:\0011\022\030\n\ttranspose\030\006 \001(\010:\005false\"8\n\016"
- "InputParameter\022&\n\005shape\030\001 \003(\0132\027.opencv_c"
- "affe.BlobShape\"D\n\014LogParameter\022\020\n\004base\030\001"
- " \001(\002:\002-1\022\020\n\005scale\030\002 \001(\002:\0011\022\020\n\005shift\030\003 \001("
- "\002:\0010\"\306\002\n\014LRNParameter\022\025\n\nlocal_size\030\001 \001("
- "\r:\0015\022\020\n\005alpha\030\002 \001(\002:\0011\022\022\n\004beta\030\003 \001(\002:\0040."
- "75\022K\n\013norm_region\030\004 \001(\0162%.opencv_caffe.L"
- "RNParameter.NormRegion:\017ACROSS_CHANNELS\022"
- "\014\n\001k\030\005 \001(\002:\0011\022:\n\006engine\030\006 \001(\0162!.opencv_c"
- "affe.LRNParameter.Engine:\007DEFAULT\"5\n\nNor"
- "mRegion\022\023\n\017ACROSS_CHANNELS\020\000\022\022\n\016WITHIN_C"
- "HANNEL\020\001\"+\n\006Engine\022\013\n\007DEFAULT\020\000\022\t\n\005CAFFE"
- "\020\001\022\t\n\005CUDNN\020\002\"Z\n\023MemoryDataParameter\022\022\n\n"
- "batch_size\030\001 \001(\r\022\020\n\010channels\030\002 \001(\r\022\016\n\006he"
- "ight\030\003 \001(\r\022\r\n\005width\030\004 \001(\r\"d\n\014MVNParamete"
- "r\022 \n\022normalize_variance\030\001 \001(\010:\004true\022\036\n\017a"
- "cross_channels\030\002 \001(\010:\005false\022\022\n\003eps\030\003 \001(\002"
- ":\0051e-09\"<\n\022ParameterParameter\022&\n\005shape\030\001"
- " \001(\0132\027.opencv_caffe.BlobShape\"\311\003\n\020Poolin"
- "gParameter\022<\n\004pool\030\001 \001(\0162).opencv_caffe."
- "PoolingParameter.PoolMethod:\003MAX\022\016\n\003pad\030"
- "\004 \001(\r:\0010\022\020\n\005pad_h\030\t \001(\r:\0010\022\020\n\005pad_w\030\n \001("
- "\r:\0010\022\023\n\013kernel_size\030\002 \001(\r\022\020\n\010kernel_h\030\005 "
- "\001(\r\022\020\n\010kernel_w\030\006 \001(\r\022\021\n\006stride\030\003 \001(\r:\0011"
- "\022\020\n\010stride_h\030\007 \001(\r\022\020\n\010stride_w\030\010 \001(\r\022>\n\006"
- "engine\030\013 \001(\0162%.opencv_caffe.PoolingParam"
- "eter.Engine:\007DEFAULT\022\035\n\016global_pooling\030\014"
- " \001(\010:\005false\022\027\n\tceil_mode\030\r \001(\010:\004true\".\n\n"
- "PoolMethod\022\007\n\003MAX\020\000\022\007\n\003AVE\020\001\022\016\n\nSTOCHAST"
- "IC\020\002\"+\n\006Engine\022\013\n\007DEFAULT\020\000\022\t\n\005CAFFE\020\001\022\t"
- "\n\005CUDNN\020\002\"F\n\016PowerParameter\022\020\n\005power\030\001 \001"
- "(\002:\0011\022\020\n\005scale\030\002 \001(\002:\0011\022\020\n\005shift\030\003 \001(\002:\001"
- "0\"g\n\017PythonParameter\022\016\n\006module\030\001 \001(\t\022\r\n\005"
- "layer\030\002 \001(\t\022\023\n\tparam_str\030\003 \001(\t:\000\022 \n\021shar"
- "e_in_parallel\030\004 \001(\010:\005false\"\316\001\n\022Recurrent"
- "Parameter\022\025\n\nnum_output\030\001 \001(\r:\0010\0224\n\rweig"
- "ht_filler\030\002 \001(\0132\035.opencv_caffe.FillerPar"
- "ameter\0222\n\013bias_filler\030\003 \001(\0132\035.opencv_caf"
- "fe.FillerParameter\022\031\n\ndebug_info\030\004 \001(\010:\005"
- "false\022\034\n\rexpose_hidden\030\005 \001(\010:\005false\"\264\001\n\022"
- "ReductionParameter\022D\n\toperation\030\001 \001(\0162,."
- "opencv_caffe.ReductionParameter.Reductio"
- "nOp:\003SUM\022\017\n\004axis\030\002 \001(\005:\0010\022\020\n\005coeff\030\003 \001(\002"
- ":\0011\"5\n\013ReductionOp\022\007\n\003SUM\020\001\022\010\n\004ASUM\020\002\022\t\n"
- "\005SUMSQ\020\003\022\010\n\004MEAN\020\004\"\224\001\n\rReLUParameter\022\031\n\016"
- "negative_slope\030\001 \001(\002:\0010\022;\n\006engine\030\002 \001(\0162"
- "\".opencv_caffe.ReLUParameter.Engine:\007DEF"
- "AULT\"+\n\006Engine\022\013\n\007DEFAULT\020\000\022\t\n\005CAFFE\020\001\022\t"
- "\n\005CUDNN\020\002\"a\n\020ReshapeParameter\022&\n\005shape\030\001"
- " \001(\0132\027.opencv_caffe.BlobShape\022\017\n\004axis\030\002 "
- "\001(\005:\0010\022\024\n\010num_axes\030\003 \001(\005:\002-1\"\263\001\n\016ScalePa"
- "rameter\022\017\n\004axis\030\001 \001(\005:\0011\022\023\n\010num_axes\030\002 \001"
- "(\005:\0011\022-\n\006filler\030\003 \001(\0132\035.opencv_caffe.Fil"
- "lerParameter\022\030\n\tbias_term\030\004 \001(\010:\005false\0222"
- "\n\013bias_filler\030\005 \001(\0132\035.opencv_caffe.Fille"
- "rParameter\"\177\n\020SigmoidParameter\022>\n\006engine"
- "\030\001 \001(\0162%.opencv_caffe.SigmoidParameter.E"
- "ngine:\007DEFAULT\"+\n\006Engine\022\013\n\007DEFAULT\020\000\022\t\n"
- "\005CAFFE\020\001\022\t\n\005CUDNN\020\002\"L\n\016SliceParameter\022\017\n"
- "\004axis\030\003 \001(\005:\0011\022\023\n\013slice_point\030\002 \003(\r\022\024\n\ts"
- "lice_dim\030\001 \001(\r:\0011\"\220\001\n\020SoftmaxParameter\022>"
- "\n\006engine\030\001 \001(\0162%.opencv_caffe.SoftmaxPar"
- "ameter.Engine:\007DEFAULT\022\017\n\004axis\030\002 \001(\005:\0011\""
- "+\n\006Engine\022\013\n\007DEFAULT\020\000\022\t\n\005CAFFE\020\001\022\t\n\005CUD"
- "NN\020\002\"y\n\rTanHParameter\022;\n\006engine\030\001 \001(\0162\"."
- "opencv_caffe.TanHParameter.Engine:\007DEFAU"
- "LT\"+\n\006Engine\022\013\n\007DEFAULT\020\000\022\t\n\005CAFFE\020\001\022\t\n\005"
- "CUDNN\020\002\"/\n\rTileParameter\022\017\n\004axis\030\001 \001(\005:\001"
- "1\022\r\n\005tiles\030\002 \001(\005\"*\n\022ThresholdParameter\022\024"
- "\n\tthreshold\030\001 \001(\002:\0010\"\301\002\n\023WindowDataParam"
- "eter\022\016\n\006source\030\001 \001(\t\022\020\n\005scale\030\002 \001(\002:\0011\022\021"
- "\n\tmean_file\030\003 \001(\t\022\022\n\nbatch_size\030\004 \001(\r\022\024\n"
- "\tcrop_size\030\005 \001(\r:\0010\022\025\n\006mirror\030\006 \001(\010:\005fal"
- "se\022\031\n\014fg_threshold\030\007 \001(\002:\0030.5\022\031\n\014bg_thre"
- "shold\030\010 \001(\002:\0030.5\022\031\n\013fg_fraction\030\t \001(\002:\0040"
- ".25\022\026\n\013context_pad\030\n \001(\r:\0010\022\027\n\tcrop_mode"
- "\030\013 \001(\t:\004warp\022\033\n\014cache_images\030\014 \001(\010:\005fals"
- "e\022\025\n\013root_folder\030\r \001(\t:\000\"\371\001\n\014SPPParamete"
- "r\022\026\n\016pyramid_height\030\001 \001(\r\0228\n\004pool\030\002 \001(\0162"
- "%.opencv_caffe.SPPParameter.PoolMethod:\003"
- "MAX\022:\n\006engine\030\006 \001(\0162!.opencv_caffe.SPPPa"
- "rameter.Engine:\007DEFAULT\".\n\nPoolMethod\022\007\n"
- "\003MAX\020\000\022\007\n\003AVE\020\001\022\016\n\nSTOCHASTIC\020\002\"+\n\006Engin"
- "e\022\013\n\007DEFAULT\020\000\022\t\n\005CAFFE\020\001\022\t\n\005CUDNN\020\002\"\334\025\n"
- "\020V1LayerParameter\022\016\n\006bottom\030\002 \003(\t\022\013\n\003top"
- "\030\003 \003(\t\022\014\n\004name\030\004 \001(\t\022+\n\007include\030 \003(\0132\032."
- "opencv_caffe.NetStateRule\022+\n\007exclude\030! \003"
- "(\0132\032.opencv_caffe.NetStateRule\0226\n\004type\030\005"
- " \001(\0162(.opencv_caffe.V1LayerParameter.Lay"
- "erType\022&\n\005blobs\030\006 \003(\0132\027.opencv_caffe.Blo"
- "bProto\022\016\n\005param\030\351\007 \003(\t\022E\n\017blob_share_mod"
- "e\030\352\007 \003(\0162+.opencv_caffe.V1LayerParameter"
- ".DimCheckMode\022\020\n\010blobs_lr\030\007 \003(\002\022\024\n\014weigh"
- "t_decay\030\010 \003(\002\022\023\n\013loss_weight\030# \003(\002\0227\n\016ac"
- "curacy_param\030\033 \001(\0132\037.opencv_caffe.Accura"
- "cyParameter\0223\n\014argmax_param\030\027 \001(\0132\035.open"
- "cv_caffe.ArgMaxParameter\0223\n\014concat_param"
- "\030\t \001(\0132\035.opencv_caffe.ConcatParameter\022F\n"
- "\026contrastive_loss_param\030( \001(\0132&.opencv_c"
- "affe.ContrastiveLossParameter\022=\n\021convolu"
- "tion_param\030\n \001(\0132\".opencv_caffe.Convolut"
- "ionParameter\022/\n\ndata_param\030\013 \001(\0132\033.openc"
- "v_caffe.DataParameter\0225\n\rdropout_param\030\014"
- " \001(\0132\036.opencv_caffe.DropoutParameter\022:\n\020"
- "dummy_data_param\030\032 \001(\0132 .opencv_caffe.Du"
- "mmyDataParameter\0225\n\reltwise_param\030\030 \001(\0132"
- "\036.opencv_caffe.EltwiseParameter\022-\n\texp_p"
- "aram\030) \001(\0132\032.opencv_caffe.ExpParameter\0228"
- "\n\017hdf5_data_param\030\r \001(\0132\037.opencv_caffe.H"
- "DF5DataParameter\022<\n\021hdf5_output_param\030\016 "
- "\001(\0132!.opencv_caffe.HDF5OutputParameter\022:"
- "\n\020hinge_loss_param\030\035 \001(\0132 .opencv_caffe."
- "HingeLossParameter\022:\n\020image_data_param\030\017"
- " \001(\0132 .opencv_caffe.ImageDataParameter\022@"
- "\n\023infogain_loss_param\030\020 \001(\0132#.opencv_caf"
- "fe.InfogainLossParameter\022@\n\023inner_produc"
- "t_param\030\021 \001(\0132#.opencv_caffe.InnerProduc"
- "tParameter\022-\n\tlrn_param\030\022 \001(\0132\032.opencv_c"
- "affe.LRNParameter\022<\n\021memory_data_param\030\026"
- " \001(\0132!.opencv_caffe.MemoryDataParameter\022"
- "-\n\tmvn_param\030\" \001(\0132\032.opencv_caffe.MVNPar"
- "ameter\0225\n\rpooling_param\030\023 \001(\0132\036.opencv_c"
- "affe.PoolingParameter\0221\n\013power_param\030\025 \001"
- "(\0132\034.opencv_caffe.PowerParameter\022/\n\nrelu"
- "_param\030\036 \001(\0132\033.opencv_caffe.ReLUParamete"
- "r\0225\n\rsigmoid_param\030& \001(\0132\036.opencv_caffe."
- "SigmoidParameter\0225\n\rsoftmax_param\030\' \001(\0132"
- "\036.opencv_caffe.SoftmaxParameter\0221\n\013slice"
- "_param\030\037 \001(\0132\034.opencv_caffe.SliceParamet"
- "er\022/\n\ntanh_param\030% \001(\0132\033.opencv_caffe.Ta"
- "nHParameter\0229\n\017threshold_param\030\031 \001(\0132 .o"
- "pencv_caffe.ThresholdParameter\022<\n\021window"
- "_data_param\030\024 \001(\0132!.opencv_caffe.WindowD"
- "ataParameter\022>\n\017transform_param\030$ \001(\0132%."
- "opencv_caffe.TransformationParameter\022/\n\n"
- "loss_param\030* \001(\0132\033.opencv_caffe.LossPara"
- "meter\022-\n\005layer\030\001 \001(\0132\036.opencv_caffe.V0La"
- "yerParameter\"\330\004\n\tLayerType\022\010\n\004NONE\020\000\022\n\n\006"
- "ABSVAL\020#\022\014\n\010ACCURACY\020\001\022\n\n\006ARGMAX\020\036\022\010\n\004BN"
- "LL\020\002\022\n\n\006CONCAT\020\003\022\024\n\020CONTRASTIVE_LOSS\020%\022\017"
- "\n\013CONVOLUTION\020\004\022\010\n\004DATA\020\005\022\021\n\rDECONVOLUTI"
- "ON\020\'\022\013\n\007DROPOUT\020\006\022\016\n\nDUMMY_DATA\020 \022\022\n\016EUC"
- "LIDEAN_LOSS\020\007\022\013\n\007ELTWISE\020\031\022\007\n\003EXP\020&\022\013\n\007F"
- "LATTEN\020\010\022\r\n\tHDF5_DATA\020\t\022\017\n\013HDF5_OUTPUT\020\n"
- "\022\016\n\nHINGE_LOSS\020\034\022\n\n\006IM2COL\020\013\022\016\n\nIMAGE_DA"
- "TA\020\014\022\021\n\rINFOGAIN_LOSS\020\r\022\021\n\rINNER_PRODUCT"
- "\020\016\022\007\n\003LRN\020\017\022\017\n\013MEMORY_DATA\020\035\022\035\n\031MULTINOM"
- "IAL_LOGISTIC_LOSS\020\020\022\007\n\003MVN\020\"\022\013\n\007POOLING\020"
- "\021\022\t\n\005POWER\020\032\022\010\n\004RELU\020\022\022\013\n\007SIGMOID\020\023\022\036\n\032S"
- "IGMOID_CROSS_ENTROPY_LOSS\020\033\022\013\n\007SILENCE\020$"
- "\022\013\n\007SOFTMAX\020\024\022\020\n\014SOFTMAX_LOSS\020\025\022\t\n\005SPLIT"
- "\020\026\022\t\n\005SLICE\020!\022\010\n\004TANH\020\027\022\017\n\013WINDOW_DATA\020\030"
- "\022\r\n\tTHRESHOLD\020\037\"*\n\014DimCheckMode\022\n\n\006STRIC"
- "T\020\000\022\016\n\nPERMISSIVE\020\001\"\240\010\n\020V0LayerParameter"
- "\022\014\n\004name\030\001 \001(\t\022\014\n\004type\030\002 \001(\t\022\022\n\nnum_outp"
- "ut\030\003 \001(\r\022\026\n\010biasterm\030\004 \001(\010:\004true\0224\n\rweig"
- "ht_filler\030\005 \001(\0132\035.opencv_caffe.FillerPar"
- "ameter\0222\n\013bias_filler\030\006 \001(\0132\035.opencv_caf"
- "fe.FillerParameter\022\016\n\003pad\030\007 \001(\r:\0010\022\022\n\nke"
- "rnelsize\030\010 \001(\r\022\020\n\005group\030\t \001(\r:\0011\022\021\n\006stri"
- "de\030\n \001(\r:\0011\022<\n\004pool\030\013 \001(\0162).opencv_caffe"
- ".V0LayerParameter.PoolMethod:\003MAX\022\032\n\rdro"
- "pout_ratio\030\014 \001(\002:\0030.5\022\025\n\nlocal_size\030\r \001("
- "\r:\0015\022\020\n\005alpha\030\016 \001(\002:\0011\022\022\n\004beta\030\017 \001(\002:\0040."
- "75\022\014\n\001k\030\026 \001(\002:\0011\022\016\n\006source\030\020 \001(\t\022\020\n\005scal"
- "e\030\021 \001(\002:\0011\022\020\n\010meanfile\030\022 \001(\t\022\021\n\tbatchsiz"
- "e\030\023 \001(\r\022\023\n\010cropsize\030\024 \001(\r:\0010\022\025\n\006mirror\030\025"
- " \001(\010:\005false\022&\n\005blobs\0302 \003(\0132\027.opencv_caff"
- "e.BlobProto\022\020\n\010blobs_lr\0303 \003(\002\022\024\n\014weight_"
- "decay\0304 \003(\002\022\024\n\trand_skip\0305 \001(\r:\0010\022\035\n\020det"
- "_fg_threshold\0306 \001(\002:\0030.5\022\035\n\020det_bg_thres"
- "hold\0307 \001(\002:\0030.5\022\035\n\017det_fg_fraction\0308 \001(\002"
- ":\0040.25\022\032\n\017det_context_pad\030: \001(\r:\0010\022\033\n\rde"
- "t_crop_mode\030; \001(\t:\004warp\022\022\n\007new_num\030< \001(\005"
- ":\0010\022\027\n\014new_channels\030= \001(\005:\0010\022\025\n\nnew_heig"
- "ht\030> \001(\005:\0010\022\024\n\tnew_width\030\? \001(\005:\0010\022\035\n\016shu"
- "ffle_images\030@ \001(\010:\005false\022\025\n\nconcat_dim\030A"
- " \001(\r:\0011\022=\n\021hdf5_output_param\030\351\007 \001(\0132!.op"
- "encv_caffe.HDF5OutputParameter\".\n\nPoolMe"
- "thod\022\007\n\003MAX\020\000\022\007\n\003AVE\020\001\022\016\n\nSTOCHASTIC\020\002\"^"
- "\n\016PReLUParameter\022-\n\006filler\030\001 \001(\0132\035.openc"
- "v_caffe.FillerParameter\022\035\n\016channel_share"
- "d\030\002 \001(\010:\005false\"\207\001\n\016NormalizedBBox\022\014\n\004xmi"
- "n\030\001 \001(\002\022\014\n\004ymin\030\002 \001(\002\022\014\n\004xmax\030\003 \001(\002\022\014\n\004y"
- "max\030\004 \001(\002\022\r\n\005label\030\005 \001(\005\022\021\n\tdifficult\030\006 "
- "\001(\010\022\r\n\005score\030\007 \001(\002\022\014\n\004size\030\010 \001(\002\"Y\n\023ROIP"
- "oolingParameter\022\023\n\010pooled_h\030\001 \001(\r:\0010\022\023\n\010"
- "pooled_w\030\002 \001(\r:\0010\022\030\n\rspatial_scale\030\003 \001(\002"
- ":\0011\"\310\001\n\021ProposalParameter\022\027\n\013feat_stride"
- "\030\001 \001(\r:\00216\022\025\n\tbase_size\030\002 \001(\r:\00216\022\024\n\010min"
- "_size\030\003 \001(\r:\00216\022\r\n\005ratio\030\004 \003(\002\022\r\n\005scale\030"
- "\005 \003(\002\022\032\n\014pre_nms_topn\030\006 \001(\r:\0046000\022\032\n\rpos"
- "t_nms_topn\030\007 \001(\r:\003300\022\027\n\nnms_thresh\030\010 \001("
- "\002:\0030.7*=\n\004Type\022\n\n\006DOUBLE\020\000\022\t\n\005FLOAT\020\001\022\013\n"
- "\007FLOAT16\020\002\022\007\n\003INT\020\003\022\010\n\004UINT\020\004*\034\n\005Phase\022\t"
- "\n\005TRAIN\020\000\022\010\n\004TEST\020\001", 18619);
+ "\001(\002\022\035\n\017normalized_bbox\030\n \001(\010:\004true\"\201\001\n\005D"
+ "atum\022\020\n\010channels\030\001 \001(\005\022\016\n\006height\030\002 \001(\005\022\r"
+ "\n\005width\030\003 \001(\005\022\014\n\004data\030\004 \001(\014\022\r\n\005label\030\005 \001"
+ "(\005\022\022\n\nfloat_data\030\006 \003(\002\022\026\n\007encoded\030\007 \001(\010:"
+ "\005false\"\221\002\n\017FillerParameter\022\026\n\004type\030\001 \001(\t"
+ ":\010constant\022\020\n\005value\030\002 \001(\002:\0010\022\016\n\003min\030\003 \001("
+ "\002:\0010\022\016\n\003max\030\004 \001(\002:\0011\022\017\n\004mean\030\005 \001(\002:\0010\022\016\n"
+ "\003std\030\006 \001(\002:\0011\022\022\n\006sparse\030\007 \001(\005:\002-1\022I\n\rvar"
+ "iance_norm\030\010 \001(\0162*.opencv_caffe.FillerPa"
+ "rameter.VarianceNorm:\006FAN_IN\"4\n\014Variance"
+ "Norm\022\n\n\006FAN_IN\020\000\022\013\n\007FAN_OUT\020\001\022\013\n\007AVERAGE"
+ "\020\002\"\252\002\n\014NetParameter\022\014\n\004name\030\001 \001(\t\022\r\n\005inp"
+ "ut\030\003 \003(\t\022,\n\013input_shape\030\010 \003(\0132\027.opencv_c"
+ "affe.BlobShape\022\021\n\tinput_dim\030\004 \003(\005\022\035\n\016for"
+ "ce_backward\030\005 \001(\010:\005false\022%\n\005state\030\006 \001(\0132"
+ "\026.opencv_caffe.NetState\022\031\n\ndebug_info\030\007 "
+ "\001(\010:\005false\022+\n\005layer\030d \003(\0132\034.opencv_caffe"
+ ".LayerParameter\022.\n\006layers\030\002 \003(\0132\036.opencv"
+ "_caffe.V1LayerParameter\"\332\n\n\017SolverParame"
+ "ter\022\013\n\003net\030\030 \001(\t\022-\n\tnet_param\030\031 \001(\0132\032.op"
+ "encv_caffe.NetParameter\022\021\n\ttrain_net\030\001 \001"
+ "(\t\022\020\n\010test_net\030\002 \003(\t\0223\n\017train_net_param\030"
+ "\025 \001(\0132\032.opencv_caffe.NetParameter\0222\n\016tes"
+ "t_net_param\030\026 \003(\0132\032.opencv_caffe.NetPara"
+ "meter\022+\n\013train_state\030\032 \001(\0132\026.opencv_caff"
+ "e.NetState\022*\n\ntest_state\030\033 \003(\0132\026.opencv_"
+ "caffe.NetState\022\021\n\ttest_iter\030\003 \003(\005\022\030\n\rtes"
+ "t_interval\030\004 \001(\005:\0010\022 \n\021test_compute_loss"
+ "\030\023 \001(\010:\005false\022!\n\023test_initialization\030 \001"
+ "(\010:\004true\022\017\n\007base_lr\030\005 \001(\002\022\017\n\007display\030\006 \001"
+ "(\005\022\027\n\014average_loss\030! \001(\005:\0011\022\020\n\010max_iter\030"
+ "\007 \001(\005\022\024\n\titer_size\030$ \001(\005:\0011\022\021\n\tlr_policy"
+ "\030\010 \001(\t\022\r\n\005gamma\030\t \001(\002\022\r\n\005power\030\n \001(\002\022\020\n\010"
+ "momentum\030\013 \001(\002\022\024\n\014weight_decay\030\014 \001(\002\022\037\n\023"
+ "regularization_type\030\035 \001(\t:\002L2\022\020\n\010stepsiz"
+ "e\030\r \001(\005\022\021\n\tstepvalue\030\" \003(\005\022\032\n\016clip_gradi"
+ "ents\030# \001(\002:\002-1\022\023\n\010snapshot\030\016 \001(\005:\0010\022\027\n\017s"
+ "napshot_prefix\030\017 \001(\t\022\034\n\rsnapshot_diff\030\020 "
+ "\001(\010:\005false\022R\n\017snapshot_format\030% \001(\0162,.op"
+ "encv_caffe.SolverParameter.SnapshotForma"
+ "t:\013BINARYPROTO\022B\n\013solver_mode\030\021 \001(\0162(.op"
+ "encv_caffe.SolverParameter.SolverMode:\003G"
+ "PU\022\024\n\tdevice_id\030\022 \001(\005:\0010\022\027\n\013random_seed\030"
+ "\024 \001(\003:\002-1\022\021\n\004type\030( \001(\t:\003SGD\022\024\n\005delta\030\037 "
+ "\001(\002:\0051e-08\022\030\n\tmomentum2\030\' \001(\002:\0050.999\022\027\n\t"
+ "rms_decay\030& \001(\002:\0040.99\022\031\n\ndebug_info\030\027 \001("
+ "\010:\005false\022\"\n\024snapshot_after_train\030\034 \001(\010:\004"
+ "true\022B\n\013solver_type\030\036 \001(\0162(.opencv_caffe"
+ ".SolverParameter.SolverType:\003SGD\"+\n\016Snap"
+ "shotFormat\022\010\n\004HDF5\020\000\022\017\n\013BINARYPROTO\020\001\"\036\n"
+ "\nSolverMode\022\007\n\003CPU\020\000\022\007\n\003GPU\020\001\"U\n\nSolverT"
+ "ype\022\007\n\003SGD\020\000\022\014\n\010NESTEROV\020\001\022\013\n\007ADAGRAD\020\002\022"
+ "\013\n\007RMSPROP\020\003\022\014\n\010ADADELTA\020\004\022\010\n\004ADAM\020\005\"s\n\013"
+ "SolverState\022\014\n\004iter\030\001 \001(\005\022\023\n\013learned_net"
+ "\030\002 \001(\t\022(\n\007history\030\003 \003(\0132\027.opencv_caffe.B"
+ "lobProto\022\027\n\014current_step\030\004 \001(\005:\0010\"U\n\010Net"
+ "State\022(\n\005phase\030\001 \001(\0162\023.opencv_caffe.Phas"
+ "e:\004TEST\022\020\n\005level\030\002 \001(\005:\0010\022\r\n\005stage\030\003 \003(\t"
+ "\"z\n\014NetStateRule\022\"\n\005phase\030\001 \001(\0162\023.opencv"
+ "_caffe.Phase\022\021\n\tmin_level\030\002 \001(\005\022\021\n\tmax_l"
+ "evel\030\003 \001(\005\022\r\n\005stage\030\004 \003(\t\022\021\n\tnot_stage\030\005"
+ " \003(\t\"\252\001\n\tParamSpec\022\014\n\004name\030\001 \001(\t\0228\n\nshar"
+ "e_mode\030\002 \001(\0162$.opencv_caffe.ParamSpec.Di"
+ "mCheckMode\022\022\n\007lr_mult\030\003 \001(\002:\0011\022\025\n\ndecay_"
+ "mult\030\004 \001(\002:\0011\"*\n\014DimCheckMode\022\n\n\006STRICT\020"
+ "\000\022\016\n\nPERMISSIVE\020\001\"\243\032\n\016LayerParameter\022\014\n\004"
+ "name\030\001 \001(\t\022\014\n\004type\030\002 \001(\t\022\016\n\006bottom\030\003 \003(\t"
+ "\022\013\n\003top\030\004 \003(\t\022\"\n\005phase\030\n \001(\0162\023.opencv_ca"
+ "ffe.Phase\022\023\n\013loss_weight\030\005 \003(\002\022&\n\005param\030"
+ "\006 \003(\0132\027.opencv_caffe.ParamSpec\022&\n\005blobs\030"
+ "\007 \003(\0132\027.opencv_caffe.BlobProto\022\026\n\016propag"
+ "ate_down\030\013 \003(\010\022+\n\007include\030\010 \003(\0132\032.opencv"
+ "_caffe.NetStateRule\022+\n\007exclude\030\t \003(\0132\032.o"
+ "pencv_caffe.NetStateRule\022>\n\017transform_pa"
+ "ram\030d \001(\0132%.opencv_caffe.TransformationP"
+ "arameter\022/\n\nloss_param\030e \001(\0132\033.opencv_ca"
+ "ffe.LossParameter\0227\n\016accuracy_param\030f \001("
+ "\0132\037.opencv_caffe.AccuracyParameter\0223\n\014ar"
+ "gmax_param\030g \001(\0132\035.opencv_caffe.ArgMaxPa"
+ "rameter\022;\n\020batch_norm_param\030\213\001 \001(\0132 .ope"
+ "ncv_caffe.BatchNormParameter\0220\n\nbias_par"
+ "am\030\215\001 \001(\0132\033.opencv_caffe.BiasParameter\0223"
+ "\n\014concat_param\030h \001(\0132\035.opencv_caffe.Conc"
+ "atParameter\022F\n\026contrastive_loss_param\030i "
+ "\001(\0132&.opencv_caffe.ContrastiveLossParame"
+ "ter\022=\n\021convolution_param\030j \001(\0132\".opencv_"
+ "caffe.ConvolutionParameter\0220\n\ncrop_param"
+ "\030\220\001 \001(\0132\033.opencv_caffe.CropParameter\022/\n\n"
+ "data_param\030k \001(\0132\033.opencv_caffe.DataPara"
+ "meter\022G\n\026detection_output_param\030\223\001 \001(\0132&"
+ ".opencv_caffe.DetectionOutputParameter\0225"
+ "\n\rdropout_param\030l \001(\0132\036.opencv_caffe.Dro"
+ "poutParameter\022:\n\020dummy_data_param\030m \001(\0132"
+ " .opencv_caffe.DummyDataParameter\0225\n\relt"
+ "wise_param\030n \001(\0132\036.opencv_caffe.EltwiseP"
+ "arameter\022.\n\telu_param\030\214\001 \001(\0132\032.opencv_ca"
+ "ffe.ELUParameter\0222\n\013embed_param\030\211\001 \001(\0132\034"
+ ".opencv_caffe.EmbedParameter\022-\n\texp_para"
+ "m\030o \001(\0132\032.opencv_caffe.ExpParameter\0226\n\rf"
+ "latten_param\030\207\001 \001(\0132\036.opencv_caffe.Flatt"
+ "enParameter\0228\n\017hdf5_data_param\030p \001(\0132\037.o"
+ "pencv_caffe.HDF5DataParameter\022<\n\021hdf5_ou"
+ "tput_param\030q \001(\0132!.opencv_caffe.HDF5Outp"
+ "utParameter\022:\n\020hinge_loss_param\030r \001(\0132 ."
+ "opencv_caffe.HingeLossParameter\022:\n\020image"
+ "_data_param\030s \001(\0132 .opencv_caffe.ImageDa"
+ "taParameter\022@\n\023infogain_loss_param\030t \001(\013"
+ "2#.opencv_caffe.InfogainLossParameter\022@\n"
+ "\023inner_product_param\030u \001(\0132#.opencv_caff"
+ "e.InnerProductParameter\0222\n\013input_param\030\217"
+ "\001 \001(\0132\034.opencv_caffe.InputParameter\022.\n\tl"
+ "og_param\030\206\001 \001(\0132\032.opencv_caffe.LogParame"
+ "ter\022-\n\tlrn_param\030v \001(\0132\032.opencv_caffe.LR"
+ "NParameter\022<\n\021memory_data_param\030w \001(\0132!."
+ "opencv_caffe.MemoryDataParameter\022-\n\tmvn_"
+ "param\030x \001(\0132\032.opencv_caffe.MVNParameter\022"
+ "9\n\nnorm_param\030\225\001 \001(\0132$.opencv_caffe.Norm"
+ "alizeBBoxParameter\0226\n\rpermute_param\030\224\001 \001"
+ "(\0132\036.opencv_caffe.PermuteParameter\022:\n\017pa"
+ "rameter_param\030\221\001 \001(\0132 .opencv_caffe.Para"
+ "meterParameter\0225\n\rpooling_param\030y \001(\0132\036."
+ "opencv_caffe.PoolingParameter\0221\n\013power_p"
+ "aram\030z \001(\0132\034.opencv_caffe.PowerParameter"
+ "\0222\n\013prelu_param\030\203\001 \001(\0132\034.opencv_caffe.PR"
+ "eLUParameter\0229\n\017prior_box_param\030\226\001 \001(\0132\037"
+ ".opencv_caffe.PriorBoxParameter\0228\n\016propo"
+ "sal_param\030\311\001 \001(\0132\037.opencv_caffe.Proposal"
+ "Parameter\022A\n\023psroi_pooling_param\030\221N \001(\0132"
+ "#.opencv_caffe.PSROIPoolingParameter\0224\n\014"
+ "python_param\030\202\001 \001(\0132\035.opencv_caffe.Pytho"
+ "nParameter\022:\n\017recurrent_param\030\222\001 \001(\0132 .o"
+ "pencv_caffe.RecurrentParameter\022:\n\017reduct"
+ "ion_param\030\210\001 \001(\0132 .opencv_caffe.Reductio"
+ "nParameter\022/\n\nrelu_param\030{ \001(\0132\033.opencv_"
+ "caffe.ReLUParameter\0226\n\rreshape_param\030\205\001 "
+ "\001(\0132\036.opencv_caffe.ReshapeParameter\022\?\n\021r"
+ "oi_pooling_param\030\327\307\370\003 \001(\0132!.opencv_caffe"
+ ".ROIPoolingParameter\0222\n\013scale_param\030\216\001 \001"
+ "(\0132\034.opencv_caffe.ScaleParameter\0225\n\rsigm"
+ "oid_param\030| \001(\0132\036.opencv_caffe.SigmoidPa"
+ "rameter\0225\n\rsoftmax_param\030} \001(\0132\036.opencv_"
+ "caffe.SoftmaxParameter\022.\n\tspp_param\030\204\001 \001"
+ "(\0132\032.opencv_caffe.SPPParameter\0221\n\013slice_"
+ "param\030~ \001(\0132\034.opencv_caffe.SliceParamete"
+ "r\022/\n\ntanh_param\030\177 \001(\0132\033.opencv_caffe.Tan"
+ "HParameter\022:\n\017threshold_param\030\200\001 \001(\0132 .o"
+ "pencv_caffe.ThresholdParameter\0220\n\ntile_p"
+ "aram\030\212\001 \001(\0132\033.opencv_caffe.TileParameter"
+ "\022=\n\021window_data_param\030\201\001 \001(\0132!.opencv_ca"
+ "ffe.WindowDataParameter\"\266\001\n\027Transformati"
+ "onParameter\022\020\n\005scale\030\001 \001(\002:\0011\022\025\n\006mirror\030"
+ "\002 \001(\010:\005false\022\024\n\tcrop_size\030\003 \001(\r:\0010\022\021\n\tme"
+ "an_file\030\004 \001(\t\022\022\n\nmean_value\030\005 \003(\002\022\032\n\013for"
+ "ce_color\030\006 \001(\010:\005false\022\031\n\nforce_gray\030\007 \001("
+ "\010:\005false\"\311\001\n\rLossParameter\022\024\n\014ignore_lab"
+ "el\030\001 \001(\005\022K\n\rnormalization\030\003 \001(\0162-.opencv"
+ "_caffe.LossParameter.NormalizationMode:\005"
+ "VALID\022\021\n\tnormalize\030\002 \001(\010\"B\n\021Normalizatio"
+ "nMode\022\010\n\004FULL\020\000\022\t\n\005VALID\020\001\022\016\n\nBATCH_SIZE"
+ "\020\002\022\010\n\004NONE\020\003\"L\n\021AccuracyParameter\022\020\n\005top"
+ "_k\030\001 \001(\r:\0011\022\017\n\004axis\030\002 \001(\005:\0011\022\024\n\014ignore_l"
+ "abel\030\003 \001(\005\"M\n\017ArgMaxParameter\022\032\n\013out_max"
+ "_val\030\001 \001(\010:\005false\022\020\n\005top_k\030\002 \001(\r:\0011\022\014\n\004a"
+ "xis\030\003 \001(\005\"9\n\017ConcatParameter\022\017\n\004axis\030\002 \001"
+ "(\005:\0011\022\025\n\nconcat_dim\030\001 \001(\r:\0011\"j\n\022BatchNor"
+ "mParameter\022\030\n\020use_global_stats\030\001 \001(\010\022&\n\027"
+ "moving_average_fraction\030\002 \001(\002:\0050.999\022\022\n\003"
+ "eps\030\003 \001(\002:\0051e-05\"d\n\rBiasParameter\022\017\n\004axi"
+ "s\030\001 \001(\005:\0011\022\023\n\010num_axes\030\002 \001(\005:\0011\022-\n\006fille"
+ "r\030\003 \001(\0132\035.opencv_caffe.FillerParameter\"L"
+ "\n\030ContrastiveLossParameter\022\021\n\006margin\030\001 \001"
+ "(\002:\0011\022\035\n\016legacy_version\030\002 \001(\010:\005false\"\221\004\n"
+ "\024ConvolutionParameter\022\022\n\nnum_output\030\001 \001("
+ "\r\022\027\n\tbias_term\030\002 \001(\010:\004true\022\013\n\003pad\030\003 \003(\r\022"
+ "\023\n\013kernel_size\030\004 \003(\r\022\016\n\006stride\030\006 \003(\r\022\020\n\010"
+ "dilation\030\022 \003(\r\022\020\n\005pad_h\030\t \001(\r:\0010\022\020\n\005pad_"
+ "w\030\n \001(\r:\0010\022\020\n\010kernel_h\030\013 \001(\r\022\020\n\010kernel_w"
+ "\030\014 \001(\r\022\020\n\010stride_h\030\r \001(\r\022\020\n\010stride_w\030\016 \001"
+ "(\r\022\020\n\005group\030\005 \001(\r:\0011\0224\n\rweight_filler\030\007 "
+ "\001(\0132\035.opencv_caffe.FillerParameter\0222\n\013bi"
+ "as_filler\030\010 \001(\0132\035.opencv_caffe.FillerPar"
+ "ameter\022B\n\006engine\030\017 \001(\0162).opencv_caffe.Co"
+ "nvolutionParameter.Engine:\007DEFAULT\022\017\n\004ax"
+ "is\030\020 \001(\005:\0011\022\036\n\017force_nd_im2col\030\021 \001(\010:\005fa"
+ "lse\"+\n\006Engine\022\013\n\007DEFAULT\020\000\022\t\n\005CAFFE\020\001\022\t\n"
+ "\005CUDNN\020\002\"0\n\rCropParameter\022\017\n\004axis\030\001 \001(\005:"
+ "\0012\022\016\n\006offset\030\002 \003(\r\"\253\002\n\rDataParameter\022\016\n\006"
+ "source\030\001 \001(\t\022\022\n\nbatch_size\030\004 \001(\r\022\024\n\trand"
+ "_skip\030\007 \001(\r:\0010\0228\n\007backend\030\010 \001(\0162\036.opencv"
+ "_caffe.DataParameter.DB:\007LEVELDB\022\020\n\005scal"
+ "e\030\002 \001(\002:\0011\022\021\n\tmean_file\030\003 \001(\t\022\024\n\tcrop_si"
+ "ze\030\005 \001(\r:\0010\022\025\n\006mirror\030\006 \001(\010:\005false\022\"\n\023fo"
+ "rce_encoded_color\030\t \001(\010:\005false\022\023\n\010prefet"
+ "ch\030\n \001(\r:\0014\"\033\n\002DB\022\013\n\007LEVELDB\020\000\022\010\n\004LMDB\020\001"
+ "\"[\n\036NonMaximumSuppressionParameter\022\032\n\rnm"
+ "s_threshold\030\001 \001(\002:\0030.3\022\r\n\005top_k\030\002 \001(\005\022\016\n"
+ "\003eta\030\003 \001(\002:\0011\"\252\001\n\023SaveOutputParameter\022\030\n"
+ "\020output_directory\030\001 \001(\t\022\032\n\022output_name_p"
+ "refix\030\002 \001(\t\022\025\n\routput_format\030\003 \001(\t\022\026\n\016la"
+ "bel_map_file\030\004 \001(\t\022\026\n\016name_size_file\030\005 \001"
+ "(\t\022\026\n\016num_test_image\030\006 \001(\r\"I\n\020DropoutPar"
+ "ameter\022\032\n\rdropout_ratio\030\001 \001(\002:\0030.5\022\031\n\013sc"
+ "ale_train\030\002 \001(\010:\004true\"\256\001\n\022DummyDataParam"
+ "eter\0222\n\013data_filler\030\001 \003(\0132\035.opencv_caffe"
+ ".FillerParameter\022&\n\005shape\030\006 \003(\0132\027.opencv"
+ "_caffe.BlobShape\022\013\n\003num\030\002 \003(\r\022\020\n\010channel"
+ "s\030\003 \003(\r\022\016\n\006height\030\004 \003(\r\022\r\n\005width\030\005 \003(\r\"\254"
+ "\001\n\020EltwiseParameter\022@\n\toperation\030\001 \001(\0162("
+ ".opencv_caffe.EltwiseParameter.EltwiseOp"
+ ":\003SUM\022\r\n\005coeff\030\002 \003(\002\022\036\n\020stable_prod_grad"
+ "\030\003 \001(\010:\004true\"\'\n\tEltwiseOp\022\010\n\004PROD\020\000\022\007\n\003S"
+ "UM\020\001\022\007\n\003MAX\020\002\" \n\014ELUParameter\022\020\n\005alpha\030\001"
+ " \001(\002:\0011\"\272\001\n\016EmbedParameter\022\022\n\nnum_output"
+ "\030\001 \001(\r\022\021\n\tinput_dim\030\002 \001(\r\022\027\n\tbias_term\030\003"
+ " \001(\010:\004true\0224\n\rweight_filler\030\004 \001(\0132\035.open"
+ "cv_caffe.FillerParameter\0222\n\013bias_filler\030"
+ "\005 \001(\0132\035.opencv_caffe.FillerParameter\"D\n\014"
+ "ExpParameter\022\020\n\004base\030\001 \001(\002:\002-1\022\020\n\005scale\030"
+ "\002 \001(\002:\0011\022\020\n\005shift\030\003 \001(\002:\0010\"9\n\020FlattenPar"
+ "ameter\022\017\n\004axis\030\001 \001(\005:\0011\022\024\n\010end_axis\030\002 \001("
+ "\005:\002-1\"O\n\021HDF5DataParameter\022\016\n\006source\030\001 \001"
+ "(\t\022\022\n\nbatch_size\030\002 \001(\r\022\026\n\007shuffle\030\003 \001(\010:"
+ "\005false\"(\n\023HDF5OutputParameter\022\021\n\tfile_na"
+ "me\030\001 \001(\t\"e\n\022HingeLossParameter\0227\n\004norm\030\001"
+ " \001(\0162%.opencv_caffe.HingeLossParameter.N"
+ "orm:\002L1\"\026\n\004Norm\022\006\n\002L1\020\001\022\006\n\002L2\020\002\"\227\002\n\022Imag"
+ "eDataParameter\022\016\n\006source\030\001 \001(\t\022\025\n\nbatch_"
+ "size\030\004 \001(\r:\0011\022\024\n\trand_skip\030\007 \001(\r:\0010\022\026\n\007s"
+ "huffle\030\010 \001(\010:\005false\022\025\n\nnew_height\030\t \001(\r:"
+ "\0010\022\024\n\tnew_width\030\n \001(\r:\0010\022\026\n\010is_color\030\013 \001"
+ "(\010:\004true\022\020\n\005scale\030\002 \001(\002:\0011\022\021\n\tmean_file\030"
+ "\003 \001(\t\022\024\n\tcrop_size\030\005 \001(\r:\0010\022\025\n\006mirror\030\006 "
+ "\001(\010:\005false\022\025\n\013root_folder\030\014 \001(\t:\000\"\'\n\025Inf"
+ "ogainLossParameter\022\016\n\006source\030\001 \001(\t\"\331\001\n\025I"
+ "nnerProductParameter\022\022\n\nnum_output\030\001 \001(\r"
+ "\022\027\n\tbias_term\030\002 \001(\010:\004true\0224\n\rweight_fill"
+ "er\030\003 \001(\0132\035.opencv_caffe.FillerParameter\022"
+ "2\n\013bias_filler\030\004 \001(\0132\035.opencv_caffe.Fill"
+ "erParameter\022\017\n\004axis\030\005 \001(\005:\0011\022\030\n\ttranspos"
+ "e\030\006 \001(\010:\005false\"8\n\016InputParameter\022&\n\005shap"
+ "e\030\001 \003(\0132\027.opencv_caffe.BlobShape\"D\n\014LogP"
+ "arameter\022\020\n\004base\030\001 \001(\002:\002-1\022\020\n\005scale\030\002 \001("
+ "\002:\0011\022\020\n\005shift\030\003 \001(\002:\0010\"\306\002\n\014LRNParameter\022"
+ "\025\n\nlocal_size\030\001 \001(\r:\0015\022\020\n\005alpha\030\002 \001(\002:\0011"
+ "\022\022\n\004beta\030\003 \001(\002:\0040.75\022K\n\013norm_region\030\004 \001("
+ "\0162%.opencv_caffe.LRNParameter.NormRegion"
+ ":\017ACROSS_CHANNELS\022\014\n\001k\030\005 \001(\002:\0011\022:\n\006engin"
+ "e\030\006 \001(\0162!.opencv_caffe.LRNParameter.Engi"
+ "ne:\007DEFAULT\"5\n\nNormRegion\022\023\n\017ACROSS_CHAN"
+ "NELS\020\000\022\022\n\016WITHIN_CHANNEL\020\001\"+\n\006Engine\022\013\n\007"
+ "DEFAULT\020\000\022\t\n\005CAFFE\020\001\022\t\n\005CUDNN\020\002\"Z\n\023Memor"
+ "yDataParameter\022\022\n\nbatch_size\030\001 \001(\r\022\020\n\010ch"
+ "annels\030\002 \001(\r\022\016\n\006height\030\003 \001(\r\022\r\n\005width\030\004 "
+ "\001(\r\"d\n\014MVNParameter\022 \n\022normalize_varianc"
+ "e\030\001 \001(\010:\004true\022\036\n\017across_channels\030\002 \001(\010:\005"
+ "false\022\022\n\003eps\030\003 \001(\002:\0051e-09\"<\n\022ParameterPa"
+ "rameter\022&\n\005shape\030\001 \001(\0132\027.opencv_caffe.Bl"
+ "obShape\"\311\003\n\020PoolingParameter\022<\n\004pool\030\001 \001"
+ "(\0162).opencv_caffe.PoolingParameter.PoolM"
+ "ethod:\003MAX\022\016\n\003pad\030\004 \001(\r:\0010\022\020\n\005pad_h\030\t \001("
+ "\r:\0010\022\020\n\005pad_w\030\n \001(\r:\0010\022\023\n\013kernel_size\030\002 "
+ "\001(\r\022\020\n\010kernel_h\030\005 \001(\r\022\020\n\010kernel_w\030\006 \001(\r\022"
+ "\021\n\006stride\030\003 \001(\r:\0011\022\020\n\010stride_h\030\007 \001(\r\022\020\n\010"
+ "stride_w\030\010 \001(\r\022>\n\006engine\030\013 \001(\0162%.opencv_"
+ "caffe.PoolingParameter.Engine:\007DEFAULT\022\035"
+ "\n\016global_pooling\030\014 \001(\010:\005false\022\027\n\tceil_mo"
+ "de\030\r \001(\010:\004true\".\n\nPoolMethod\022\007\n\003MAX\020\000\022\007\n"
+ "\003AVE\020\001\022\016\n\nSTOCHASTIC\020\002\"+\n\006Engine\022\013\n\007DEFA"
+ "ULT\020\000\022\t\n\005CAFFE\020\001\022\t\n\005CUDNN\020\002\"F\n\016PowerPara"
+ "meter\022\020\n\005power\030\001 \001(\002:\0011\022\020\n\005scale\030\002 \001(\002:\001"
+ "1\022\020\n\005shift\030\003 \001(\002:\0010\"g\n\017PythonParameter\022\016"
+ "\n\006module\030\001 \001(\t\022\r\n\005layer\030\002 \001(\t\022\023\n\tparam_s"
+ "tr\030\003 \001(\t:\000\022 \n\021share_in_parallel\030\004 \001(\010:\005f"
+ "alse\"\316\001\n\022RecurrentParameter\022\025\n\nnum_outpu"
+ "t\030\001 \001(\r:\0010\0224\n\rweight_filler\030\002 \001(\0132\035.open"
+ "cv_caffe.FillerParameter\0222\n\013bias_filler\030"
+ "\003 \001(\0132\035.opencv_caffe.FillerParameter\022\031\n\n"
+ "debug_info\030\004 \001(\010:\005false\022\034\n\rexpose_hidden"
+ "\030\005 \001(\010:\005false\"\264\001\n\022ReductionParameter\022D\n\t"
+ "operation\030\001 \001(\0162,.opencv_caffe.Reduction"
+ "Parameter.ReductionOp:\003SUM\022\017\n\004axis\030\002 \001(\005"
+ ":\0010\022\020\n\005coeff\030\003 \001(\002:\0011\"5\n\013ReductionOp\022\007\n\003"
+ "SUM\020\001\022\010\n\004ASUM\020\002\022\t\n\005SUMSQ\020\003\022\010\n\004MEAN\020\004\"\224\001\n"
+ "\rReLUParameter\022\031\n\016negative_slope\030\001 \001(\002:\001"
+ "0\022;\n\006engine\030\002 \001(\0162\".opencv_caffe.ReLUPar"
+ "ameter.Engine:\007DEFAULT\"+\n\006Engine\022\013\n\007DEFA"
+ "ULT\020\000\022\t\n\005CAFFE\020\001\022\t\n\005CUDNN\020\002\"a\n\020ReshapePa"
+ "rameter\022&\n\005shape\030\001 \001(\0132\027.opencv_caffe.Bl"
+ "obShape\022\017\n\004axis\030\002 \001(\005:\0010\022\024\n\010num_axes\030\003 \001"
+ "(\005:\002-1\"\263\001\n\016ScaleParameter\022\017\n\004axis\030\001 \001(\005:"
+ "\0011\022\023\n\010num_axes\030\002 \001(\005:\0011\022-\n\006filler\030\003 \001(\0132"
+ "\035.opencv_caffe.FillerParameter\022\030\n\tbias_t"
+ "erm\030\004 \001(\010:\005false\0222\n\013bias_filler\030\005 \001(\0132\035."
+ "opencv_caffe.FillerParameter\"\177\n\020SigmoidP"
+ "arameter\022>\n\006engine\030\001 \001(\0162%.opencv_caffe."
+ "SigmoidParameter.Engine:\007DEFAULT\"+\n\006Engi"
+ "ne\022\013\n\007DEFAULT\020\000\022\t\n\005CAFFE\020\001\022\t\n\005CUDNN\020\002\"L\n"
+ "\016SliceParameter\022\017\n\004axis\030\003 \001(\005:\0011\022\023\n\013slic"
+ "e_point\030\002 \003(\r\022\024\n\tslice_dim\030\001 \001(\r:\0011\"\220\001\n\020"
+ "SoftmaxParameter\022>\n\006engine\030\001 \001(\0162%.openc"
+ "v_caffe.SoftmaxParameter.Engine:\007DEFAULT"
+ "\022\017\n\004axis\030\002 \001(\005:\0011\"+\n\006Engine\022\013\n\007DEFAULT\020\000"
+ "\022\t\n\005CAFFE\020\001\022\t\n\005CUDNN\020\002\"y\n\rTanHParameter\022"
+ ";\n\006engine\030\001 \001(\0162\".opencv_caffe.TanHParam"
+ "eter.Engine:\007DEFAULT\"+\n\006Engine\022\013\n\007DEFAUL"
+ "T\020\000\022\t\n\005CAFFE\020\001\022\t\n\005CUDNN\020\002\"/\n\rTileParamet"
+ "er\022\017\n\004axis\030\001 \001(\005:\0011\022\r\n\005tiles\030\002 \001(\005\"*\n\022Th"
+ "resholdParameter\022\024\n\tthreshold\030\001 \001(\002:\0010\"\301"
+ "\002\n\023WindowDataParameter\022\016\n\006source\030\001 \001(\t\022\020"
+ "\n\005scale\030\002 \001(\002:\0011\022\021\n\tmean_file\030\003 \001(\t\022\022\n\nb"
+ "atch_size\030\004 \001(\r\022\024\n\tcrop_size\030\005 \001(\r:\0010\022\025\n"
+ "\006mirror\030\006 \001(\010:\005false\022\031\n\014fg_threshold\030\007 \001"
+ "(\002:\0030.5\022\031\n\014bg_threshold\030\010 \001(\002:\0030.5\022\031\n\013fg"
+ "_fraction\030\t \001(\002:\0040.25\022\026\n\013context_pad\030\n \001"
+ "(\r:\0010\022\027\n\tcrop_mode\030\013 \001(\t:\004warp\022\033\n\014cache_"
+ "images\030\014 \001(\010:\005false\022\025\n\013root_folder\030\r \001(\t"
+ ":\000\"\371\001\n\014SPPParameter\022\026\n\016pyramid_height\030\001 "
+ "\001(\r\0228\n\004pool\030\002 \001(\0162%.opencv_caffe.SPPPara"
+ "meter.PoolMethod:\003MAX\022:\n\006engine\030\006 \001(\0162!."
+ "opencv_caffe.SPPParameter.Engine:\007DEFAUL"
+ "T\".\n\nPoolMethod\022\007\n\003MAX\020\000\022\007\n\003AVE\020\001\022\016\n\nSTO"
+ "CHASTIC\020\002\"+\n\006Engine\022\013\n\007DEFAULT\020\000\022\t\n\005CAFF"
+ "E\020\001\022\t\n\005CUDNN\020\002\"\334\025\n\020V1LayerParameter\022\016\n\006b"
+ "ottom\030\002 \003(\t\022\013\n\003top\030\003 \003(\t\022\014\n\004name\030\004 \001(\t\022+"
+ "\n\007include\030 \003(\0132\032.opencv_caffe.NetStateR"
+ "ule\022+\n\007exclude\030! \003(\0132\032.opencv_caffe.NetS"
+ "tateRule\0226\n\004type\030\005 \001(\0162(.opencv_caffe.V1"
+ "LayerParameter.LayerType\022&\n\005blobs\030\006 \003(\0132"
+ "\027.opencv_caffe.BlobProto\022\016\n\005param\030\351\007 \003(\t"
+ "\022E\n\017blob_share_mode\030\352\007 \003(\0162+.opencv_caff"
+ "e.V1LayerParameter.DimCheckMode\022\020\n\010blobs"
+ "_lr\030\007 \003(\002\022\024\n\014weight_decay\030\010 \003(\002\022\023\n\013loss_"
+ "weight\030# \003(\002\0227\n\016accuracy_param\030\033 \001(\0132\037.o"
+ "pencv_caffe.AccuracyParameter\0223\n\014argmax_"
+ "param\030\027 \001(\0132\035.opencv_caffe.ArgMaxParamet"
+ "er\0223\n\014concat_param\030\t \001(\0132\035.opencv_caffe."
+ "ConcatParameter\022F\n\026contrastive_loss_para"
+ "m\030( \001(\0132&.opencv_caffe.ContrastiveLossPa"
+ "rameter\022=\n\021convolution_param\030\n \001(\0132\".ope"
+ "ncv_caffe.ConvolutionParameter\022/\n\ndata_p"
+ "aram\030\013 \001(\0132\033.opencv_caffe.DataParameter\022"
+ "5\n\rdropout_param\030\014 \001(\0132\036.opencv_caffe.Dr"
+ "opoutParameter\022:\n\020dummy_data_param\030\032 \001(\013"
+ "2 .opencv_caffe.DummyDataParameter\0225\n\rel"
+ "twise_param\030\030 \001(\0132\036.opencv_caffe.Eltwise"
+ "Parameter\022-\n\texp_param\030) \001(\0132\032.opencv_ca"
+ "ffe.ExpParameter\0228\n\017hdf5_data_param\030\r \001("
+ "\0132\037.opencv_caffe.HDF5DataParameter\022<\n\021hd"
+ "f5_output_param\030\016 \001(\0132!.opencv_caffe.HDF"
+ "5OutputParameter\022:\n\020hinge_loss_param\030\035 \001"
+ "(\0132 .opencv_caffe.HingeLossParameter\022:\n\020"
+ "image_data_param\030\017 \001(\0132 .opencv_caffe.Im"
+ "ageDataParameter\022@\n\023infogain_loss_param\030"
+ "\020 \001(\0132#.opencv_caffe.InfogainLossParamet"
+ "er\022@\n\023inner_product_param\030\021 \001(\0132#.opencv"
+ "_caffe.InnerProductParameter\022-\n\tlrn_para"
+ "m\030\022 \001(\0132\032.opencv_caffe.LRNParameter\022<\n\021m"
+ "emory_data_param\030\026 \001(\0132!.opencv_caffe.Me"
+ "moryDataParameter\022-\n\tmvn_param\030\" \001(\0132\032.o"
+ "pencv_caffe.MVNParameter\0225\n\rpooling_para"
+ "m\030\023 \001(\0132\036.opencv_caffe.PoolingParameter\022"
+ "1\n\013power_param\030\025 \001(\0132\034.opencv_caffe.Powe"
+ "rParameter\022/\n\nrelu_param\030\036 \001(\0132\033.opencv_"
+ "caffe.ReLUParameter\0225\n\rsigmoid_param\030& \001"
+ "(\0132\036.opencv_caffe.SigmoidParameter\0225\n\rso"
+ "ftmax_param\030\' \001(\0132\036.opencv_caffe.Softmax"
+ "Parameter\0221\n\013slice_param\030\037 \001(\0132\034.opencv_"
+ "caffe.SliceParameter\022/\n\ntanh_param\030% \001(\013"
+ "2\033.opencv_caffe.TanHParameter\0229\n\017thresho"
+ "ld_param\030\031 \001(\0132 .opencv_caffe.ThresholdP"
+ "arameter\022<\n\021window_data_param\030\024 \001(\0132!.op"
+ "encv_caffe.WindowDataParameter\022>\n\017transf"
+ "orm_param\030$ \001(\0132%.opencv_caffe.Transform"
+ "ationParameter\022/\n\nloss_param\030* \001(\0132\033.ope"
+ "ncv_caffe.LossParameter\022-\n\005layer\030\001 \001(\0132\036"
+ ".opencv_caffe.V0LayerParameter\"\330\004\n\tLayer"
+ "Type\022\010\n\004NONE\020\000\022\n\n\006ABSVAL\020#\022\014\n\010ACCURACY\020\001"
+ "\022\n\n\006ARGMAX\020\036\022\010\n\004BNLL\020\002\022\n\n\006CONCAT\020\003\022\024\n\020CO"
+ "NTRASTIVE_LOSS\020%\022\017\n\013CONVOLUTION\020\004\022\010\n\004DAT"
+ "A\020\005\022\021\n\rDECONVOLUTION\020\'\022\013\n\007DROPOUT\020\006\022\016\n\nD"
+ "UMMY_DATA\020 \022\022\n\016EUCLIDEAN_LOSS\020\007\022\013\n\007ELTWI"
+ "SE\020\031\022\007\n\003EXP\020&\022\013\n\007FLATTEN\020\010\022\r\n\tHDF5_DATA\020"
+ "\t\022\017\n\013HDF5_OUTPUT\020\n\022\016\n\nHINGE_LOSS\020\034\022\n\n\006IM"
+ "2COL\020\013\022\016\n\nIMAGE_DATA\020\014\022\021\n\rINFOGAIN_LOSS\020"
+ "\r\022\021\n\rINNER_PRODUCT\020\016\022\007\n\003LRN\020\017\022\017\n\013MEMORY_"
+ "DATA\020\035\022\035\n\031MULTINOMIAL_LOGISTIC_LOSS\020\020\022\007\n"
+ "\003MVN\020\"\022\013\n\007POOLING\020\021\022\t\n\005POWER\020\032\022\010\n\004RELU\020\022"
+ "\022\013\n\007SIGMOID\020\023\022\036\n\032SIGMOID_CROSS_ENTROPY_L"
+ "OSS\020\033\022\013\n\007SILENCE\020$\022\013\n\007SOFTMAX\020\024\022\020\n\014SOFTM"
+ "AX_LOSS\020\025\022\t\n\005SPLIT\020\026\022\t\n\005SLICE\020!\022\010\n\004TANH\020"
+ "\027\022\017\n\013WINDOW_DATA\020\030\022\r\n\tTHRESHOLD\020\037\"*\n\014Dim"
+ "CheckMode\022\n\n\006STRICT\020\000\022\016\n\nPERMISSIVE\020\001\"\240\010"
+ "\n\020V0LayerParameter\022\014\n\004name\030\001 \001(\t\022\014\n\004type"
+ "\030\002 \001(\t\022\022\n\nnum_output\030\003 \001(\r\022\026\n\010biasterm\030\004"
+ " \001(\010:\004true\0224\n\rweight_filler\030\005 \001(\0132\035.open"
+ "cv_caffe.FillerParameter\0222\n\013bias_filler\030"
+ "\006 \001(\0132\035.opencv_caffe.FillerParameter\022\016\n\003"
+ "pad\030\007 \001(\r:\0010\022\022\n\nkernelsize\030\010 \001(\r\022\020\n\005grou"
+ "p\030\t \001(\r:\0011\022\021\n\006stride\030\n \001(\r:\0011\022<\n\004pool\030\013 "
+ "\001(\0162).opencv_caffe.V0LayerParameter.Pool"
+ "Method:\003MAX\022\032\n\rdropout_ratio\030\014 \001(\002:\0030.5\022"
+ "\025\n\nlocal_size\030\r \001(\r:\0015\022\020\n\005alpha\030\016 \001(\002:\0011"
+ "\022\022\n\004beta\030\017 \001(\002:\0040.75\022\014\n\001k\030\026 \001(\002:\0011\022\016\n\006so"
+ "urce\030\020 \001(\t\022\020\n\005scale\030\021 \001(\002:\0011\022\020\n\010meanfile"
+ "\030\022 \001(\t\022\021\n\tbatchsize\030\023 \001(\r\022\023\n\010cropsize\030\024 "
+ "\001(\r:\0010\022\025\n\006mirror\030\025 \001(\010:\005false\022&\n\005blobs\0302"
+ " \003(\0132\027.opencv_caffe.BlobProto\022\020\n\010blobs_l"
+ "r\0303 \003(\002\022\024\n\014weight_decay\0304 \003(\002\022\024\n\trand_sk"
+ "ip\0305 \001(\r:\0010\022\035\n\020det_fg_threshold\0306 \001(\002:\0030"
+ ".5\022\035\n\020det_bg_threshold\0307 \001(\002:\0030.5\022\035\n\017det"
+ "_fg_fraction\0308 \001(\002:\0040.25\022\032\n\017det_context_"
+ "pad\030: \001(\r:\0010\022\033\n\rdet_crop_mode\030; \001(\t:\004war"
+ "p\022\022\n\007new_num\030< \001(\005:\0010\022\027\n\014new_channels\030= "
+ "\001(\005:\0010\022\025\n\nnew_height\030> \001(\005:\0010\022\024\n\tnew_wid"
+ "th\030\? \001(\005:\0010\022\035\n\016shuffle_images\030@ \001(\010:\005fal"
+ "se\022\025\n\nconcat_dim\030A \001(\r:\0011\022=\n\021hdf5_output"
+ "_param\030\351\007 \001(\0132!.opencv_caffe.HDF5OutputP"
+ "arameter\".\n\nPoolMethod\022\007\n\003MAX\020\000\022\007\n\003AVE\020\001"
+ "\022\016\n\nSTOCHASTIC\020\002\"^\n\016PReLUParameter\022-\n\006fi"
+ "ller\030\001 \001(\0132\035.opencv_caffe.FillerParamete"
+ "r\022\035\n\016channel_shared\030\002 \001(\010:\005false\"\207\001\n\016Nor"
+ "malizedBBox\022\014\n\004xmin\030\001 \001(\002\022\014\n\004ymin\030\002 \001(\002\022"
+ "\014\n\004xmax\030\003 \001(\002\022\014\n\004ymax\030\004 \001(\002\022\r\n\005label\030\005 \001"
+ "(\005\022\021\n\tdifficult\030\006 \001(\010\022\r\n\005score\030\007 \001(\002\022\014\n\004"
+ "size\030\010 \001(\002\"Y\n\023ROIPoolingParameter\022\023\n\010poo"
+ "led_h\030\001 \001(\r:\0010\022\023\n\010pooled_w\030\002 \001(\r:\0010\022\030\n\rs"
+ "patial_scale\030\003 \001(\002:\0011\"\310\001\n\021ProposalParame"
+ "ter\022\027\n\013feat_stride\030\001 \001(\r:\00216\022\025\n\tbase_siz"
+ "e\030\002 \001(\r:\00216\022\024\n\010min_size\030\003 \001(\r:\00216\022\r\n\005rat"
+ "io\030\004 \003(\002\022\r\n\005scale\030\005 \003(\002\022\032\n\014pre_nms_topn\030"
+ "\006 \001(\r:\0046000\022\032\n\rpost_nms_topn\030\007 \001(\r:\003300\022"
+ "\027\n\nnms_thresh\030\010 \001(\002:\0030.7\"V\n\025PSROIPooling"
+ "Parameter\022\025\n\rspatial_scale\030\001 \002(\002\022\022\n\noutp"
+ "ut_dim\030\002 \002(\005\022\022\n\ngroup_size\030\003 \002(\005*=\n\004Type"
+ "\022\n\n\006DOUBLE\020\000\022\t\n\005FLOAT\020\001\022\013\n\007FLOAT16\020\002\022\007\n\003"
+ "INT\020\003\022\010\n\004UINT\020\004*\034\n\005Phase\022\t\n\005TRAIN\020\000\022\010\n\004T"
+ "EST\020\001", 18805);
::google::protobuf::MessageFactory::InternalRegisterGeneratedFile(
"opencv-caffe.proto", &protobuf_RegisterTypes);
::google::protobuf::internal::OnShutdown(&protobuf_ShutdownFile_opencv_2dcaffe_2eproto);
const int DetectionOutputParameter::kVarianceEncodedInTargetFieldNumber;
const int DetectionOutputParameter::kKeepTopKFieldNumber;
const int DetectionOutputParameter::kConfidenceThresholdFieldNumber;
+const int DetectionOutputParameter::kNormalizedBboxFieldNumber;
#endif // !defined(_MSC_VER) || _MSC_VER >= 1900
DetectionOutputParameter::DetectionOutputParameter()
::memset(&num_classes_, 0, reinterpret_cast<char*>(&confidence_threshold_) -
reinterpret_cast<char*>(&num_classes_) + sizeof(confidence_threshold_));
keep_top_k_ = -1;
- share_location_ = true;
code_type_ = 1;
+ share_location_ = true;
+ normalized_bbox_ = true;
}
DetectionOutputParameter::~DetectionOutputParameter() {
code_type_ = 1;
keep_top_k_ = -1;
}
- confidence_threshold_ = 0;
+ if (_has_bits_[8 / 32] & 768u) {
+ confidence_threshold_ = 0;
+ normalized_bbox_ = true;
+ }
#undef ZR_HELPER_
#undef ZR_
} else {
goto handle_unusual;
}
+ if (input->ExpectTag(80)) goto parse_normalized_bbox;
+ break;
+ }
+
+ // optional bool normalized_bbox = 10 [default = true];
+ case 10: {
+ if (tag == 80) {
+ parse_normalized_bbox:
+ set_has_normalized_bbox();
+ DO_((::google::protobuf::internal::WireFormatLite::ReadPrimitive<
+ bool, ::google::protobuf::internal::WireFormatLite::TYPE_BOOL>(
+ input, &normalized_bbox_)));
+ } else {
+ goto handle_unusual;
+ }
if (input->ExpectAtEnd()) goto success;
break;
}
::google::protobuf::internal::WireFormatLite::WriteFloat(9, this->confidence_threshold(), output);
}
+ // optional bool normalized_bbox = 10 [default = true];
+ if (has_normalized_bbox()) {
+ ::google::protobuf::internal::WireFormatLite::WriteBool(10, this->normalized_bbox(), output);
+ }
+
if (_internal_metadata_.have_unknown_fields()) {
::google::protobuf::internal::WireFormat::SerializeUnknownFields(
unknown_fields(), output);
target = ::google::protobuf::internal::WireFormatLite::WriteFloatToArray(9, this->confidence_threshold(), target);
}
+ // optional bool normalized_bbox = 10 [default = true];
+ if (has_normalized_bbox()) {
+ target = ::google::protobuf::internal::WireFormatLite::WriteBoolToArray(10, this->normalized_bbox(), target);
+ }
+
if (_internal_metadata_.have_unknown_fields()) {
target = ::google::protobuf::internal::WireFormat::SerializeUnknownFieldsToArray(
unknown_fields(), target);
}
}
- // optional float confidence_threshold = 9;
- if (has_confidence_threshold()) {
- total_size += 1 + 4;
- }
+ if (_has_bits_[8 / 32] & 768u) {
+ // optional float confidence_threshold = 9;
+ if (has_confidence_threshold()) {
+ total_size += 1 + 4;
+ }
+ // optional bool normalized_bbox = 10 [default = true];
+ if (has_normalized_bbox()) {
+ total_size += 1 + 1;
+ }
+
+ }
if (_internal_metadata_.have_unknown_fields()) {
total_size +=
::google::protobuf::internal::WireFormat::ComputeUnknownFieldsSize(
if (from.has_confidence_threshold()) {
set_confidence_threshold(from.confidence_threshold());
}
+ if (from.has_normalized_bbox()) {
+ set_normalized_bbox(from.normalized_bbox());
+ }
}
if (from._internal_metadata_.have_unknown_fields()) {
::google::protobuf::UnknownFieldSet::MergeToInternalMetdata(
std::swap(variance_encoded_in_target_, other->variance_encoded_in_target_);
std::swap(keep_top_k_, other->keep_top_k_);
std::swap(confidence_threshold_, other->confidence_threshold_);
+ std::swap(normalized_bbox_, other->normalized_bbox_);
std::swap(_has_bits_[0], other->_has_bits_[0]);
_internal_metadata_.Swap(&other->_internal_metadata_);
std::swap(_cached_size_, other->_cached_size_);
// @@protoc_insertion_point(field_set:opencv_caffe.DetectionOutputParameter.confidence_threshold)
}
+// optional bool normalized_bbox = 10 [default = true];
+bool DetectionOutputParameter::has_normalized_bbox() const {
+ return (_has_bits_[0] & 0x00000200u) != 0;
+}
+void DetectionOutputParameter::set_has_normalized_bbox() {
+ _has_bits_[0] |= 0x00000200u;
+}
+void DetectionOutputParameter::clear_has_normalized_bbox() {
+ _has_bits_[0] &= ~0x00000200u;
+}
+void DetectionOutputParameter::clear_normalized_bbox() {
+ normalized_bbox_ = true;
+ clear_has_normalized_bbox();
+}
+bool DetectionOutputParameter::normalized_bbox() const {
+ // @@protoc_insertion_point(field_get:opencv_caffe.DetectionOutputParameter.normalized_bbox)
+ return normalized_bbox_;
+}
+void DetectionOutputParameter::set_normalized_bbox(bool value) {
+ set_has_normalized_bbox();
+ normalized_bbox_ = value;
+ // @@protoc_insertion_point(field_set:opencv_caffe.DetectionOutputParameter.normalized_bbox)
+}
+
inline const DetectionOutputParameter* DetectionOutputParameter::internal_default_instance() {
return &DetectionOutputParameter_default_instance_.get();
}
bool NetParameter::IsInitialized() const {
+ if (!::google::protobuf::internal::AllAreInitialized(this->layer())) return false;
return true;
}
bool SolverParameter::IsInitialized() const {
+ if (has_net_param()) {
+ if (!this->net_param_->IsInitialized()) return false;
+ }
+ if (has_train_net_param()) {
+ if (!this->train_net_param_->IsInitialized()) return false;
+ }
+ if (!::google::protobuf::internal::AllAreInitialized(this->test_net_param())) return false;
return true;
}
const int LayerParameter::kPreluParamFieldNumber;
const int LayerParameter::kPriorBoxParamFieldNumber;
const int LayerParameter::kProposalParamFieldNumber;
+const int LayerParameter::kPsroiPoolingParamFieldNumber;
const int LayerParameter::kPythonParamFieldNumber;
const int LayerParameter::kRecurrentParamFieldNumber;
const int LayerParameter::kReductionParamFieldNumber;
::opencv_caffe::PriorBoxParameter::internal_default_instance());
proposal_param_ = const_cast< ::opencv_caffe::ProposalParameter*>(
::opencv_caffe::ProposalParameter::internal_default_instance());
+ psroi_pooling_param_ = const_cast< ::opencv_caffe::PSROIPoolingParameter*>(
+ ::opencv_caffe::PSROIPoolingParameter::internal_default_instance());
python_param_ = const_cast< ::opencv_caffe::PythonParameter*>(
::opencv_caffe::PythonParameter::internal_default_instance());
recurrent_param_ = const_cast< ::opencv_caffe::RecurrentParameter*>(
}
void LayerParameter::SharedCtor() {
+ _cached_size_ = 0;
name_.UnsafeSetDefault(&::google::protobuf::internal::GetEmptyStringAlreadyInited());
type_.UnsafeSetDefault(&::google::protobuf::internal::GetEmptyStringAlreadyInited());
transform_param_ = NULL;
prelu_param_ = NULL;
prior_box_param_ = NULL;
proposal_param_ = NULL;
+ psroi_pooling_param_ = NULL;
python_param_ = NULL;
recurrent_param_ = NULL;
reduction_param_ = NULL;
tile_param_ = NULL;
window_data_param_ = NULL;
phase_ = 0;
- _cached_size_ = 0;
}
LayerParameter::~LayerParameter() {
delete prelu_param_;
delete prior_box_param_;
delete proposal_param_;
+ delete psroi_pooling_param_;
delete python_param_;
delete recurrent_param_;
delete reduction_param_;
if (has_proposal_param()) {
if (proposal_param_ != NULL) proposal_param_->::opencv_caffe::ProposalParameter::Clear();
}
+ if (has_psroi_pooling_param()) {
+ if (psroi_pooling_param_ != NULL) psroi_pooling_param_->::opencv_caffe::PSROIPoolingParameter::Clear();
+ }
if (has_python_param()) {
if (python_param_ != NULL) python_param_->::opencv_caffe::PythonParameter::Clear();
}
if (has_roi_pooling_param()) {
if (roi_pooling_param_ != NULL) roi_pooling_param_->::opencv_caffe::ROIPoolingParameter::Clear();
}
+ }
+ if (_has_bits_[56 / 32] & 4278190080u) {
if (has_scale_param()) {
if (scale_param_ != NULL) scale_param_->::opencv_caffe::ScaleParameter::Clear();
}
- }
- if (_has_bits_[56 / 32] & 4278190080u) {
if (has_sigmoid_param()) {
if (sigmoid_param_ != NULL) sigmoid_param_->::opencv_caffe::SigmoidParameter::Clear();
}
if (has_tile_param()) {
if (tile_param_ != NULL) tile_param_->::opencv_caffe::TileParameter::Clear();
}
- if (has_window_data_param()) {
- if (window_data_param_ != NULL) window_data_param_->::opencv_caffe::WindowDataParameter::Clear();
- }
+ }
+ if (has_window_data_param()) {
+ if (window_data_param_ != NULL) window_data_param_->::opencv_caffe::WindowDataParameter::Clear();
}
bottom_.Clear();
top_.Clear();
} else {
goto handle_unusual;
}
+ if (input->ExpectTag(80010)) goto parse_psroi_pooling_param;
+ break;
+ }
+
+ // optional .opencv_caffe.PSROIPoolingParameter psroi_pooling_param = 10001;
+ case 10001: {
+ if (tag == 80010) {
+ parse_psroi_pooling_param:
+ DO_(::google::protobuf::internal::WireFormatLite::ReadMessageNoVirtual(
+ input, mutable_psroi_pooling_param()));
+ } else {
+ goto handle_unusual;
+ }
if (input->ExpectTag(66133690)) goto parse_roi_pooling_param;
break;
}
201, *this->proposal_param_, output);
}
+ // optional .opencv_caffe.PSROIPoolingParameter psroi_pooling_param = 10001;
+ if (has_psroi_pooling_param()) {
+ ::google::protobuf::internal::WireFormatLite::WriteMessageMaybeToArray(
+ 10001, *this->psroi_pooling_param_, output);
+ }
+
// optional .opencv_caffe.ROIPoolingParameter roi_pooling_param = 8266711;
if (has_roi_pooling_param()) {
::google::protobuf::internal::WireFormatLite::WriteMessageMaybeToArray(
201, *this->proposal_param_, false, target);
}
+ // optional .opencv_caffe.PSROIPoolingParameter psroi_pooling_param = 10001;
+ if (has_psroi_pooling_param()) {
+ target = ::google::protobuf::internal::WireFormatLite::
+ InternalWriteMessageNoVirtualToArray(
+ 10001, *this->psroi_pooling_param_, false, target);
+ }
+
// optional .opencv_caffe.ROIPoolingParameter roi_pooling_param = 8266711;
if (has_roi_pooling_param()) {
target = ::google::protobuf::internal::WireFormatLite::
*this->proposal_param_);
}
+ // optional .opencv_caffe.PSROIPoolingParameter psroi_pooling_param = 10001;
+ if (has_psroi_pooling_param()) {
+ total_size += 3 +
+ ::google::protobuf::internal::WireFormatLite::MessageSizeNoVirtual(
+ *this->psroi_pooling_param_);
+ }
+
// optional .opencv_caffe.PythonParameter python_param = 130;
if (has_python_param()) {
total_size += 2 +
*this->roi_pooling_param_);
}
+ }
+ if (_has_bits_[56 / 32] & 4278190080u) {
// optional .opencv_caffe.ScaleParameter scale_param = 142;
if (has_scale_param()) {
total_size += 2 +
*this->scale_param_);
}
- }
- if (_has_bits_[56 / 32] & 4278190080u) {
// optional .opencv_caffe.SigmoidParameter sigmoid_param = 124;
if (has_sigmoid_param()) {
total_size += 2 +
*this->tile_param_);
}
- // optional .opencv_caffe.WindowDataParameter window_data_param = 129;
- if (has_window_data_param()) {
- total_size += 2 +
- ::google::protobuf::internal::WireFormatLite::MessageSizeNoVirtual(
- *this->window_data_param_);
- }
-
}
+ // optional .opencv_caffe.WindowDataParameter window_data_param = 129;
+ if (has_window_data_param()) {
+ total_size += 2 +
+ ::google::protobuf::internal::WireFormatLite::MessageSizeNoVirtual(
+ *this->window_data_param_);
+ }
+
// repeated string bottom = 3;
total_size += 1 *
::google::protobuf::internal::FromIntSize(this->bottom_size());
if (from.has_proposal_param()) {
mutable_proposal_param()->::opencv_caffe::ProposalParameter::MergeFrom(from.proposal_param());
}
+ if (from.has_psroi_pooling_param()) {
+ mutable_psroi_pooling_param()->::opencv_caffe::PSROIPoolingParameter::MergeFrom(from.psroi_pooling_param());
+ }
if (from.has_python_param()) {
mutable_python_param()->::opencv_caffe::PythonParameter::MergeFrom(from.python_param());
}
if (from.has_roi_pooling_param()) {
mutable_roi_pooling_param()->::opencv_caffe::ROIPoolingParameter::MergeFrom(from.roi_pooling_param());
}
+ }
+ if (from._has_bits_[56 / 32] & (0xffu << (56 % 32))) {
if (from.has_scale_param()) {
mutable_scale_param()->::opencv_caffe::ScaleParameter::MergeFrom(from.scale_param());
}
- }
- if (from._has_bits_[56 / 32] & (0xffu << (56 % 32))) {
if (from.has_sigmoid_param()) {
mutable_sigmoid_param()->::opencv_caffe::SigmoidParameter::MergeFrom(from.sigmoid_param());
}
if (from.has_tile_param()) {
mutable_tile_param()->::opencv_caffe::TileParameter::MergeFrom(from.tile_param());
}
+ }
+ if (from._has_bits_[64 / 32] & (0xffu << (64 % 32))) {
if (from.has_window_data_param()) {
mutable_window_data_param()->::opencv_caffe::WindowDataParameter::MergeFrom(from.window_data_param());
}
bool LayerParameter::IsInitialized() const {
+ if (has_psroi_pooling_param()) {
+ if (!this->psroi_pooling_param_->IsInitialized()) return false;
+ }
return true;
}
std::swap(prelu_param_, other->prelu_param_);
std::swap(prior_box_param_, other->prior_box_param_);
std::swap(proposal_param_, other->proposal_param_);
+ std::swap(psroi_pooling_param_, other->psroi_pooling_param_);
std::swap(python_param_, other->python_param_);
std::swap(recurrent_param_, other->recurrent_param_);
std::swap(reduction_param_, other->reduction_param_);
std::swap(window_data_param_, other->window_data_param_);
std::swap(_has_bits_[0], other->_has_bits_[0]);
std::swap(_has_bits_[1], other->_has_bits_[1]);
+ std::swap(_has_bits_[2], other->_has_bits_[2]);
_internal_metadata_.Swap(&other->_internal_metadata_);
std::swap(_cached_size_, other->_cached_size_);
}
// @@protoc_insertion_point(field_set_allocated:opencv_caffe.LayerParameter.proposal_param)
}
+// optional .opencv_caffe.PSROIPoolingParameter psroi_pooling_param = 10001;
+bool LayerParameter::has_psroi_pooling_param() const {
+ return (_has_bits_[1] & 0x00020000u) != 0;
+}
+void LayerParameter::set_has_psroi_pooling_param() {
+ _has_bits_[1] |= 0x00020000u;
+}
+void LayerParameter::clear_has_psroi_pooling_param() {
+ _has_bits_[1] &= ~0x00020000u;
+}
+void LayerParameter::clear_psroi_pooling_param() {
+ if (psroi_pooling_param_ != NULL) psroi_pooling_param_->::opencv_caffe::PSROIPoolingParameter::Clear();
+ clear_has_psroi_pooling_param();
+}
+const ::opencv_caffe::PSROIPoolingParameter& LayerParameter::psroi_pooling_param() const {
+ // @@protoc_insertion_point(field_get:opencv_caffe.LayerParameter.psroi_pooling_param)
+ return psroi_pooling_param_ != NULL ? *psroi_pooling_param_
+ : *::opencv_caffe::PSROIPoolingParameter::internal_default_instance();
+}
+::opencv_caffe::PSROIPoolingParameter* LayerParameter::mutable_psroi_pooling_param() {
+ set_has_psroi_pooling_param();
+ if (psroi_pooling_param_ == NULL) {
+ psroi_pooling_param_ = new ::opencv_caffe::PSROIPoolingParameter;
+ }
+ // @@protoc_insertion_point(field_mutable:opencv_caffe.LayerParameter.psroi_pooling_param)
+ return psroi_pooling_param_;
+}
+::opencv_caffe::PSROIPoolingParameter* LayerParameter::release_psroi_pooling_param() {
+ // @@protoc_insertion_point(field_release:opencv_caffe.LayerParameter.psroi_pooling_param)
+ clear_has_psroi_pooling_param();
+ ::opencv_caffe::PSROIPoolingParameter* temp = psroi_pooling_param_;
+ psroi_pooling_param_ = NULL;
+ return temp;
+}
+void LayerParameter::set_allocated_psroi_pooling_param(::opencv_caffe::PSROIPoolingParameter* psroi_pooling_param) {
+ delete psroi_pooling_param_;
+ psroi_pooling_param_ = psroi_pooling_param;
+ if (psroi_pooling_param) {
+ set_has_psroi_pooling_param();
+ } else {
+ clear_has_psroi_pooling_param();
+ }
+ // @@protoc_insertion_point(field_set_allocated:opencv_caffe.LayerParameter.psroi_pooling_param)
+}
+
// optional .opencv_caffe.PythonParameter python_param = 130;
bool LayerParameter::has_python_param() const {
- return (_has_bits_[1] & 0x00020000u) != 0;
+ return (_has_bits_[1] & 0x00040000u) != 0;
}
void LayerParameter::set_has_python_param() {
- _has_bits_[1] |= 0x00020000u;
+ _has_bits_[1] |= 0x00040000u;
}
void LayerParameter::clear_has_python_param() {
- _has_bits_[1] &= ~0x00020000u;
+ _has_bits_[1] &= ~0x00040000u;
}
void LayerParameter::clear_python_param() {
if (python_param_ != NULL) python_param_->::opencv_caffe::PythonParameter::Clear();
// optional .opencv_caffe.RecurrentParameter recurrent_param = 146;
bool LayerParameter::has_recurrent_param() const {
- return (_has_bits_[1] & 0x00040000u) != 0;
+ return (_has_bits_[1] & 0x00080000u) != 0;
}
void LayerParameter::set_has_recurrent_param() {
- _has_bits_[1] |= 0x00040000u;
+ _has_bits_[1] |= 0x00080000u;
}
void LayerParameter::clear_has_recurrent_param() {
- _has_bits_[1] &= ~0x00040000u;
+ _has_bits_[1] &= ~0x00080000u;
}
void LayerParameter::clear_recurrent_param() {
if (recurrent_param_ != NULL) recurrent_param_->::opencv_caffe::RecurrentParameter::Clear();
// optional .opencv_caffe.ReductionParameter reduction_param = 136;
bool LayerParameter::has_reduction_param() const {
- return (_has_bits_[1] & 0x00080000u) != 0;
+ return (_has_bits_[1] & 0x00100000u) != 0;
}
void LayerParameter::set_has_reduction_param() {
- _has_bits_[1] |= 0x00080000u;
+ _has_bits_[1] |= 0x00100000u;
}
void LayerParameter::clear_has_reduction_param() {
- _has_bits_[1] &= ~0x00080000u;
+ _has_bits_[1] &= ~0x00100000u;
}
void LayerParameter::clear_reduction_param() {
if (reduction_param_ != NULL) reduction_param_->::opencv_caffe::ReductionParameter::Clear();
// optional .opencv_caffe.ReLUParameter relu_param = 123;
bool LayerParameter::has_relu_param() const {
- return (_has_bits_[1] & 0x00100000u) != 0;
+ return (_has_bits_[1] & 0x00200000u) != 0;
}
void LayerParameter::set_has_relu_param() {
- _has_bits_[1] |= 0x00100000u;
+ _has_bits_[1] |= 0x00200000u;
}
void LayerParameter::clear_has_relu_param() {
- _has_bits_[1] &= ~0x00100000u;
+ _has_bits_[1] &= ~0x00200000u;
}
void LayerParameter::clear_relu_param() {
if (relu_param_ != NULL) relu_param_->::opencv_caffe::ReLUParameter::Clear();
// optional .opencv_caffe.ReshapeParameter reshape_param = 133;
bool LayerParameter::has_reshape_param() const {
- return (_has_bits_[1] & 0x00200000u) != 0;
+ return (_has_bits_[1] & 0x00400000u) != 0;
}
void LayerParameter::set_has_reshape_param() {
- _has_bits_[1] |= 0x00200000u;
+ _has_bits_[1] |= 0x00400000u;
}
void LayerParameter::clear_has_reshape_param() {
- _has_bits_[1] &= ~0x00200000u;
+ _has_bits_[1] &= ~0x00400000u;
}
void LayerParameter::clear_reshape_param() {
if (reshape_param_ != NULL) reshape_param_->::opencv_caffe::ReshapeParameter::Clear();
// optional .opencv_caffe.ROIPoolingParameter roi_pooling_param = 8266711;
bool LayerParameter::has_roi_pooling_param() const {
- return (_has_bits_[1] & 0x00400000u) != 0;
+ return (_has_bits_[1] & 0x00800000u) != 0;
}
void LayerParameter::set_has_roi_pooling_param() {
- _has_bits_[1] |= 0x00400000u;
+ _has_bits_[1] |= 0x00800000u;
}
void LayerParameter::clear_has_roi_pooling_param() {
- _has_bits_[1] &= ~0x00400000u;
+ _has_bits_[1] &= ~0x00800000u;
}
void LayerParameter::clear_roi_pooling_param() {
if (roi_pooling_param_ != NULL) roi_pooling_param_->::opencv_caffe::ROIPoolingParameter::Clear();
// optional .opencv_caffe.ScaleParameter scale_param = 142;
bool LayerParameter::has_scale_param() const {
- return (_has_bits_[1] & 0x00800000u) != 0;
+ return (_has_bits_[1] & 0x01000000u) != 0;
}
void LayerParameter::set_has_scale_param() {
- _has_bits_[1] |= 0x00800000u;
+ _has_bits_[1] |= 0x01000000u;
}
void LayerParameter::clear_has_scale_param() {
- _has_bits_[1] &= ~0x00800000u;
+ _has_bits_[1] &= ~0x01000000u;
}
void LayerParameter::clear_scale_param() {
if (scale_param_ != NULL) scale_param_->::opencv_caffe::ScaleParameter::Clear();
// optional .opencv_caffe.SigmoidParameter sigmoid_param = 124;
bool LayerParameter::has_sigmoid_param() const {
- return (_has_bits_[1] & 0x01000000u) != 0;
+ return (_has_bits_[1] & 0x02000000u) != 0;
}
void LayerParameter::set_has_sigmoid_param() {
- _has_bits_[1] |= 0x01000000u;
+ _has_bits_[1] |= 0x02000000u;
}
void LayerParameter::clear_has_sigmoid_param() {
- _has_bits_[1] &= ~0x01000000u;
+ _has_bits_[1] &= ~0x02000000u;
}
void LayerParameter::clear_sigmoid_param() {
if (sigmoid_param_ != NULL) sigmoid_param_->::opencv_caffe::SigmoidParameter::Clear();
// optional .opencv_caffe.SoftmaxParameter softmax_param = 125;
bool LayerParameter::has_softmax_param() const {
- return (_has_bits_[1] & 0x02000000u) != 0;
+ return (_has_bits_[1] & 0x04000000u) != 0;
}
void LayerParameter::set_has_softmax_param() {
- _has_bits_[1] |= 0x02000000u;
+ _has_bits_[1] |= 0x04000000u;
}
void LayerParameter::clear_has_softmax_param() {
- _has_bits_[1] &= ~0x02000000u;
+ _has_bits_[1] &= ~0x04000000u;
}
void LayerParameter::clear_softmax_param() {
if (softmax_param_ != NULL) softmax_param_->::opencv_caffe::SoftmaxParameter::Clear();
// optional .opencv_caffe.SPPParameter spp_param = 132;
bool LayerParameter::has_spp_param() const {
- return (_has_bits_[1] & 0x04000000u) != 0;
+ return (_has_bits_[1] & 0x08000000u) != 0;
}
void LayerParameter::set_has_spp_param() {
- _has_bits_[1] |= 0x04000000u;
+ _has_bits_[1] |= 0x08000000u;
}
void LayerParameter::clear_has_spp_param() {
- _has_bits_[1] &= ~0x04000000u;
+ _has_bits_[1] &= ~0x08000000u;
}
void LayerParameter::clear_spp_param() {
if (spp_param_ != NULL) spp_param_->::opencv_caffe::SPPParameter::Clear();
// optional .opencv_caffe.SliceParameter slice_param = 126;
bool LayerParameter::has_slice_param() const {
- return (_has_bits_[1] & 0x08000000u) != 0;
+ return (_has_bits_[1] & 0x10000000u) != 0;
}
void LayerParameter::set_has_slice_param() {
- _has_bits_[1] |= 0x08000000u;
+ _has_bits_[1] |= 0x10000000u;
}
void LayerParameter::clear_has_slice_param() {
- _has_bits_[1] &= ~0x08000000u;
+ _has_bits_[1] &= ~0x10000000u;
}
void LayerParameter::clear_slice_param() {
if (slice_param_ != NULL) slice_param_->::opencv_caffe::SliceParameter::Clear();
// optional .opencv_caffe.TanHParameter tanh_param = 127;
bool LayerParameter::has_tanh_param() const {
- return (_has_bits_[1] & 0x10000000u) != 0;
+ return (_has_bits_[1] & 0x20000000u) != 0;
}
void LayerParameter::set_has_tanh_param() {
- _has_bits_[1] |= 0x10000000u;
+ _has_bits_[1] |= 0x20000000u;
}
void LayerParameter::clear_has_tanh_param() {
- _has_bits_[1] &= ~0x10000000u;
+ _has_bits_[1] &= ~0x20000000u;
}
void LayerParameter::clear_tanh_param() {
if (tanh_param_ != NULL) tanh_param_->::opencv_caffe::TanHParameter::Clear();
// optional .opencv_caffe.ThresholdParameter threshold_param = 128;
bool LayerParameter::has_threshold_param() const {
- return (_has_bits_[1] & 0x20000000u) != 0;
+ return (_has_bits_[1] & 0x40000000u) != 0;
}
void LayerParameter::set_has_threshold_param() {
- _has_bits_[1] |= 0x20000000u;
+ _has_bits_[1] |= 0x40000000u;
}
void LayerParameter::clear_has_threshold_param() {
- _has_bits_[1] &= ~0x20000000u;
+ _has_bits_[1] &= ~0x40000000u;
}
void LayerParameter::clear_threshold_param() {
if (threshold_param_ != NULL) threshold_param_->::opencv_caffe::ThresholdParameter::Clear();
// optional .opencv_caffe.TileParameter tile_param = 138;
bool LayerParameter::has_tile_param() const {
- return (_has_bits_[1] & 0x40000000u) != 0;
+ return (_has_bits_[1] & 0x80000000u) != 0;
}
void LayerParameter::set_has_tile_param() {
- _has_bits_[1] |= 0x40000000u;
+ _has_bits_[1] |= 0x80000000u;
}
void LayerParameter::clear_has_tile_param() {
- _has_bits_[1] &= ~0x40000000u;
+ _has_bits_[1] &= ~0x80000000u;
}
void LayerParameter::clear_tile_param() {
if (tile_param_ != NULL) tile_param_->::opencv_caffe::TileParameter::Clear();
// optional .opencv_caffe.WindowDataParameter window_data_param = 129;
bool LayerParameter::has_window_data_param() const {
- return (_has_bits_[1] & 0x80000000u) != 0;
+ return (_has_bits_[2] & 0x00000001u) != 0;
}
void LayerParameter::set_has_window_data_param() {
- _has_bits_[1] |= 0x80000000u;
+ _has_bits_[2] |= 0x00000001u;
}
void LayerParameter::clear_has_window_data_param() {
- _has_bits_[1] &= ~0x80000000u;
+ _has_bits_[2] &= ~0x00000001u;
}
void LayerParameter::clear_window_data_param() {
if (window_data_param_ != NULL) window_data_param_->::opencv_caffe::WindowDataParameter::Clear();
}
#endif // PROTOBUF_INLINE_NOT_IN_HEADERS
+// ===================================================================
+
+#if !defined(_MSC_VER) || _MSC_VER >= 1900
+const int PSROIPoolingParameter::kSpatialScaleFieldNumber;
+const int PSROIPoolingParameter::kOutputDimFieldNumber;
+const int PSROIPoolingParameter::kGroupSizeFieldNumber;
+#endif // !defined(_MSC_VER) || _MSC_VER >= 1900
+
+PSROIPoolingParameter::PSROIPoolingParameter()
+ : ::google::protobuf::Message(), _internal_metadata_(NULL) {
+ if (this != internal_default_instance()) protobuf_InitDefaults_opencv_2dcaffe_2eproto();
+ SharedCtor();
+ // @@protoc_insertion_point(constructor:opencv_caffe.PSROIPoolingParameter)
+}
+
+void PSROIPoolingParameter::InitAsDefaultInstance() {
+}
+
+PSROIPoolingParameter::PSROIPoolingParameter(const PSROIPoolingParameter& from)
+ : ::google::protobuf::Message(),
+ _internal_metadata_(NULL) {
+ SharedCtor();
+ UnsafeMergeFrom(from);
+ // @@protoc_insertion_point(copy_constructor:opencv_caffe.PSROIPoolingParameter)
+}
+
+void PSROIPoolingParameter::SharedCtor() {
+ _cached_size_ = 0;
+ ::memset(&spatial_scale_, 0, reinterpret_cast<char*>(&group_size_) -
+ reinterpret_cast<char*>(&spatial_scale_) + sizeof(group_size_));
+}
+
+PSROIPoolingParameter::~PSROIPoolingParameter() {
+ // @@protoc_insertion_point(destructor:opencv_caffe.PSROIPoolingParameter)
+ SharedDtor();
+}
+
+void PSROIPoolingParameter::SharedDtor() {
+}
+
+void PSROIPoolingParameter::SetCachedSize(int size) const {
+ GOOGLE_SAFE_CONCURRENT_WRITES_BEGIN();
+ _cached_size_ = size;
+ GOOGLE_SAFE_CONCURRENT_WRITES_END();
+}
+const ::google::protobuf::Descriptor* PSROIPoolingParameter::descriptor() {
+ protobuf_AssignDescriptorsOnce();
+ return PSROIPoolingParameter_descriptor_;
+}
+
+const PSROIPoolingParameter& PSROIPoolingParameter::default_instance() {
+ protobuf_InitDefaults_opencv_2dcaffe_2eproto();
+ return *internal_default_instance();
+}
+
+::google::protobuf::internal::ExplicitlyConstructed<PSROIPoolingParameter> PSROIPoolingParameter_default_instance_;
+
+PSROIPoolingParameter* PSROIPoolingParameter::New(::google::protobuf::Arena* arena) const {
+ PSROIPoolingParameter* n = new PSROIPoolingParameter;
+ if (arena != NULL) {
+ arena->Own(n);
+ }
+ return n;
+}
+
+void PSROIPoolingParameter::Clear() {
+// @@protoc_insertion_point(message_clear_start:opencv_caffe.PSROIPoolingParameter)
+#if defined(__clang__)
+#define ZR_HELPER_(f) \
+ _Pragma("clang diagnostic push") \
+ _Pragma("clang diagnostic ignored \"-Winvalid-offsetof\"") \
+ __builtin_offsetof(PSROIPoolingParameter, f) \
+ _Pragma("clang diagnostic pop")
+#else
+#define ZR_HELPER_(f) reinterpret_cast<char*>(\
+ &reinterpret_cast<PSROIPoolingParameter*>(16)->f)
+#endif
+
+#define ZR_(first, last) do {\
+ ::memset(&(first), 0,\
+ ZR_HELPER_(last) - ZR_HELPER_(first) + sizeof(last));\
+} while (0)
+
+ ZR_(spatial_scale_, group_size_);
+
+#undef ZR_HELPER_
+#undef ZR_
+
+ _has_bits_.Clear();
+ if (_internal_metadata_.have_unknown_fields()) {
+ mutable_unknown_fields()->Clear();
+ }
+}
+
+bool PSROIPoolingParameter::MergePartialFromCodedStream(
+ ::google::protobuf::io::CodedInputStream* input) {
+#define DO_(EXPRESSION) if (!GOOGLE_PREDICT_TRUE(EXPRESSION)) goto failure
+ ::google::protobuf::uint32 tag;
+ // @@protoc_insertion_point(parse_start:opencv_caffe.PSROIPoolingParameter)
+ for (;;) {
+ ::std::pair< ::google::protobuf::uint32, bool> p = input->ReadTagWithCutoff(127);
+ tag = p.first;
+ if (!p.second) goto handle_unusual;
+ switch (::google::protobuf::internal::WireFormatLite::GetTagFieldNumber(tag)) {
+ // required float spatial_scale = 1;
+ case 1: {
+ if (tag == 13) {
+ set_has_spatial_scale();
+ DO_((::google::protobuf::internal::WireFormatLite::ReadPrimitive<
+ float, ::google::protobuf::internal::WireFormatLite::TYPE_FLOAT>(
+ input, &spatial_scale_)));
+ } else {
+ goto handle_unusual;
+ }
+ if (input->ExpectTag(16)) goto parse_output_dim;
+ break;
+ }
+
+ // required int32 output_dim = 2;
+ case 2: {
+ if (tag == 16) {
+ parse_output_dim:
+ set_has_output_dim();
+ DO_((::google::protobuf::internal::WireFormatLite::ReadPrimitive<
+ ::google::protobuf::int32, ::google::protobuf::internal::WireFormatLite::TYPE_INT32>(
+ input, &output_dim_)));
+ } else {
+ goto handle_unusual;
+ }
+ if (input->ExpectTag(24)) goto parse_group_size;
+ break;
+ }
+
+ // required int32 group_size = 3;
+ case 3: {
+ if (tag == 24) {
+ parse_group_size:
+ set_has_group_size();
+ DO_((::google::protobuf::internal::WireFormatLite::ReadPrimitive<
+ ::google::protobuf::int32, ::google::protobuf::internal::WireFormatLite::TYPE_INT32>(
+ input, &group_size_)));
+ } else {
+ goto handle_unusual;
+ }
+ if (input->ExpectAtEnd()) goto success;
+ break;
+ }
+
+ default: {
+ handle_unusual:
+ if (tag == 0 ||
+ ::google::protobuf::internal::WireFormatLite::GetTagWireType(tag) ==
+ ::google::protobuf::internal::WireFormatLite::WIRETYPE_END_GROUP) {
+ goto success;
+ }
+ DO_(::google::protobuf::internal::WireFormat::SkipField(
+ input, tag, mutable_unknown_fields()));
+ break;
+ }
+ }
+ }
+success:
+ // @@protoc_insertion_point(parse_success:opencv_caffe.PSROIPoolingParameter)
+ return true;
+failure:
+ // @@protoc_insertion_point(parse_failure:opencv_caffe.PSROIPoolingParameter)
+ return false;
+#undef DO_
+}
+
+void PSROIPoolingParameter::SerializeWithCachedSizes(
+ ::google::protobuf::io::CodedOutputStream* output) const {
+ // @@protoc_insertion_point(serialize_start:opencv_caffe.PSROIPoolingParameter)
+ // required float spatial_scale = 1;
+ if (has_spatial_scale()) {
+ ::google::protobuf::internal::WireFormatLite::WriteFloat(1, this->spatial_scale(), output);
+ }
+
+ // required int32 output_dim = 2;
+ if (has_output_dim()) {
+ ::google::protobuf::internal::WireFormatLite::WriteInt32(2, this->output_dim(), output);
+ }
+
+ // required int32 group_size = 3;
+ if (has_group_size()) {
+ ::google::protobuf::internal::WireFormatLite::WriteInt32(3, this->group_size(), output);
+ }
+
+ if (_internal_metadata_.have_unknown_fields()) {
+ ::google::protobuf::internal::WireFormat::SerializeUnknownFields(
+ unknown_fields(), output);
+ }
+ // @@protoc_insertion_point(serialize_end:opencv_caffe.PSROIPoolingParameter)
+}
+
+::google::protobuf::uint8* PSROIPoolingParameter::InternalSerializeWithCachedSizesToArray(
+ bool deterministic, ::google::protobuf::uint8* target) const {
+ (void)deterministic; // Unused
+ // @@protoc_insertion_point(serialize_to_array_start:opencv_caffe.PSROIPoolingParameter)
+ // required float spatial_scale = 1;
+ if (has_spatial_scale()) {
+ target = ::google::protobuf::internal::WireFormatLite::WriteFloatToArray(1, this->spatial_scale(), target);
+ }
+
+ // required int32 output_dim = 2;
+ if (has_output_dim()) {
+ target = ::google::protobuf::internal::WireFormatLite::WriteInt32ToArray(2, this->output_dim(), target);
+ }
+
+ // required int32 group_size = 3;
+ if (has_group_size()) {
+ target = ::google::protobuf::internal::WireFormatLite::WriteInt32ToArray(3, this->group_size(), target);
+ }
+
+ if (_internal_metadata_.have_unknown_fields()) {
+ target = ::google::protobuf::internal::WireFormat::SerializeUnknownFieldsToArray(
+ unknown_fields(), target);
+ }
+ // @@protoc_insertion_point(serialize_to_array_end:opencv_caffe.PSROIPoolingParameter)
+ return target;
+}
+
+size_t PSROIPoolingParameter::RequiredFieldsByteSizeFallback() const {
+// @@protoc_insertion_point(required_fields_byte_size_fallback_start:opencv_caffe.PSROIPoolingParameter)
+ size_t total_size = 0;
+
+ if (has_spatial_scale()) {
+ // required float spatial_scale = 1;
+ total_size += 1 + 4;
+ }
+
+ if (has_output_dim()) {
+ // required int32 output_dim = 2;
+ total_size += 1 +
+ ::google::protobuf::internal::WireFormatLite::Int32Size(
+ this->output_dim());
+ }
+
+ if (has_group_size()) {
+ // required int32 group_size = 3;
+ total_size += 1 +
+ ::google::protobuf::internal::WireFormatLite::Int32Size(
+ this->group_size());
+ }
+
+ return total_size;
+}
+size_t PSROIPoolingParameter::ByteSizeLong() const {
+// @@protoc_insertion_point(message_byte_size_start:opencv_caffe.PSROIPoolingParameter)
+ size_t total_size = 0;
+
+ if (((_has_bits_[0] & 0x00000007) ^ 0x00000007) == 0) { // All required fields are present.
+ // required float spatial_scale = 1;
+ total_size += 1 + 4;
+
+ // required int32 output_dim = 2;
+ total_size += 1 +
+ ::google::protobuf::internal::WireFormatLite::Int32Size(
+ this->output_dim());
+
+ // required int32 group_size = 3;
+ total_size += 1 +
+ ::google::protobuf::internal::WireFormatLite::Int32Size(
+ this->group_size());
+
+ } else {
+ total_size += RequiredFieldsByteSizeFallback();
+ }
+ if (_internal_metadata_.have_unknown_fields()) {
+ total_size +=
+ ::google::protobuf::internal::WireFormat::ComputeUnknownFieldsSize(
+ unknown_fields());
+ }
+ int cached_size = ::google::protobuf::internal::ToCachedSize(total_size);
+ GOOGLE_SAFE_CONCURRENT_WRITES_BEGIN();
+ _cached_size_ = cached_size;
+ GOOGLE_SAFE_CONCURRENT_WRITES_END();
+ return total_size;
+}
+
+void PSROIPoolingParameter::MergeFrom(const ::google::protobuf::Message& from) {
+// @@protoc_insertion_point(generalized_merge_from_start:opencv_caffe.PSROIPoolingParameter)
+ if (GOOGLE_PREDICT_FALSE(&from == this)) MergeFromFail(__LINE__);
+ const PSROIPoolingParameter* source =
+ ::google::protobuf::internal::DynamicCastToGenerated<const PSROIPoolingParameter>(
+ &from);
+ if (source == NULL) {
+ // @@protoc_insertion_point(generalized_merge_from_cast_fail:opencv_caffe.PSROIPoolingParameter)
+ ::google::protobuf::internal::ReflectionOps::Merge(from, this);
+ } else {
+ // @@protoc_insertion_point(generalized_merge_from_cast_success:opencv_caffe.PSROIPoolingParameter)
+ UnsafeMergeFrom(*source);
+ }
+}
+
+void PSROIPoolingParameter::MergeFrom(const PSROIPoolingParameter& from) {
+// @@protoc_insertion_point(class_specific_merge_from_start:opencv_caffe.PSROIPoolingParameter)
+ if (GOOGLE_PREDICT_TRUE(&from != this)) {
+ UnsafeMergeFrom(from);
+ } else {
+ MergeFromFail(__LINE__);
+ }
+}
+
+void PSROIPoolingParameter::UnsafeMergeFrom(const PSROIPoolingParameter& from) {
+ GOOGLE_DCHECK(&from != this);
+ if (from._has_bits_[0 / 32] & (0xffu << (0 % 32))) {
+ if (from.has_spatial_scale()) {
+ set_spatial_scale(from.spatial_scale());
+ }
+ if (from.has_output_dim()) {
+ set_output_dim(from.output_dim());
+ }
+ if (from.has_group_size()) {
+ set_group_size(from.group_size());
+ }
+ }
+ if (from._internal_metadata_.have_unknown_fields()) {
+ ::google::protobuf::UnknownFieldSet::MergeToInternalMetdata(
+ from.unknown_fields(), &_internal_metadata_);
+ }
+}
+
+void PSROIPoolingParameter::CopyFrom(const ::google::protobuf::Message& from) {
+// @@protoc_insertion_point(generalized_copy_from_start:opencv_caffe.PSROIPoolingParameter)
+ if (&from == this) return;
+ Clear();
+ MergeFrom(from);
+}
+
+void PSROIPoolingParameter::CopyFrom(const PSROIPoolingParameter& from) {
+// @@protoc_insertion_point(class_specific_copy_from_start:opencv_caffe.PSROIPoolingParameter)
+ if (&from == this) return;
+ Clear();
+ UnsafeMergeFrom(from);
+}
+
+bool PSROIPoolingParameter::IsInitialized() const {
+ if ((_has_bits_[0] & 0x00000007) != 0x00000007) return false;
+
+ return true;
+}
+
+void PSROIPoolingParameter::Swap(PSROIPoolingParameter* other) {
+ if (other == this) return;
+ InternalSwap(other);
+}
+void PSROIPoolingParameter::InternalSwap(PSROIPoolingParameter* other) {
+ std::swap(spatial_scale_, other->spatial_scale_);
+ std::swap(output_dim_, other->output_dim_);
+ std::swap(group_size_, other->group_size_);
+ std::swap(_has_bits_[0], other->_has_bits_[0]);
+ _internal_metadata_.Swap(&other->_internal_metadata_);
+ std::swap(_cached_size_, other->_cached_size_);
+}
+
+::google::protobuf::Metadata PSROIPoolingParameter::GetMetadata() const {
+ protobuf_AssignDescriptorsOnce();
+ ::google::protobuf::Metadata metadata;
+ metadata.descriptor = PSROIPoolingParameter_descriptor_;
+ metadata.reflection = PSROIPoolingParameter_reflection_;
+ return metadata;
+}
+
+#if PROTOBUF_INLINE_NOT_IN_HEADERS
+// PSROIPoolingParameter
+
+// required float spatial_scale = 1;
+bool PSROIPoolingParameter::has_spatial_scale() const {
+ return (_has_bits_[0] & 0x00000001u) != 0;
+}
+void PSROIPoolingParameter::set_has_spatial_scale() {
+ _has_bits_[0] |= 0x00000001u;
+}
+void PSROIPoolingParameter::clear_has_spatial_scale() {
+ _has_bits_[0] &= ~0x00000001u;
+}
+void PSROIPoolingParameter::clear_spatial_scale() {
+ spatial_scale_ = 0;
+ clear_has_spatial_scale();
+}
+float PSROIPoolingParameter::spatial_scale() const {
+ // @@protoc_insertion_point(field_get:opencv_caffe.PSROIPoolingParameter.spatial_scale)
+ return spatial_scale_;
+}
+void PSROIPoolingParameter::set_spatial_scale(float value) {
+ set_has_spatial_scale();
+ spatial_scale_ = value;
+ // @@protoc_insertion_point(field_set:opencv_caffe.PSROIPoolingParameter.spatial_scale)
+}
+
+// required int32 output_dim = 2;
+bool PSROIPoolingParameter::has_output_dim() const {
+ return (_has_bits_[0] & 0x00000002u) != 0;
+}
+void PSROIPoolingParameter::set_has_output_dim() {
+ _has_bits_[0] |= 0x00000002u;
+}
+void PSROIPoolingParameter::clear_has_output_dim() {
+ _has_bits_[0] &= ~0x00000002u;
+}
+void PSROIPoolingParameter::clear_output_dim() {
+ output_dim_ = 0;
+ clear_has_output_dim();
+}
+::google::protobuf::int32 PSROIPoolingParameter::output_dim() const {
+ // @@protoc_insertion_point(field_get:opencv_caffe.PSROIPoolingParameter.output_dim)
+ return output_dim_;
+}
+void PSROIPoolingParameter::set_output_dim(::google::protobuf::int32 value) {
+ set_has_output_dim();
+ output_dim_ = value;
+ // @@protoc_insertion_point(field_set:opencv_caffe.PSROIPoolingParameter.output_dim)
+}
+
+// required int32 group_size = 3;
+bool PSROIPoolingParameter::has_group_size() const {
+ return (_has_bits_[0] & 0x00000004u) != 0;
+}
+void PSROIPoolingParameter::set_has_group_size() {
+ _has_bits_[0] |= 0x00000004u;
+}
+void PSROIPoolingParameter::clear_has_group_size() {
+ _has_bits_[0] &= ~0x00000004u;
+}
+void PSROIPoolingParameter::clear_group_size() {
+ group_size_ = 0;
+ clear_has_group_size();
+}
+::google::protobuf::int32 PSROIPoolingParameter::group_size() const {
+ // @@protoc_insertion_point(field_get:opencv_caffe.PSROIPoolingParameter.group_size)
+ return group_size_;
+}
+void PSROIPoolingParameter::set_group_size(::google::protobuf::int32 value) {
+ set_has_group_size();
+ group_size_ = value;
+ // @@protoc_insertion_point(field_set:opencv_caffe.PSROIPoolingParameter.group_size)
+}
+
+inline const PSROIPoolingParameter* PSROIPoolingParameter::internal_default_instance() {
+ return &PSROIPoolingParameter_default_instance_.get();
+}
+#endif // PROTOBUF_INLINE_NOT_IN_HEADERS
+
// @@protoc_insertion_point(namespace_scope)
} // namespace opencv_caffe
class NormalizeBBoxParameter;
class NormalizedBBox;
class PReLUParameter;
+class PSROIPoolingParameter;
class ParamSpec;
class ParameterParameter;
class PermuteParameter;
float confidence_threshold() const;
void set_confidence_threshold(float value);
+ // optional bool normalized_bbox = 10 [default = true];
+ bool has_normalized_bbox() const;
+ void clear_normalized_bbox();
+ static const int kNormalizedBboxFieldNumber = 10;
+ bool normalized_bbox() const;
+ void set_normalized_bbox(bool value);
+
// @@protoc_insertion_point(class_scope:opencv_caffe.DetectionOutputParameter)
private:
inline void set_has_num_classes();
inline void clear_has_keep_top_k();
inline void set_has_confidence_threshold();
inline void clear_has_confidence_threshold();
+ inline void set_has_normalized_bbox();
+ inline void clear_has_normalized_bbox();
::google::protobuf::internal::InternalMetadataWithArena _internal_metadata_;
::google::protobuf::internal::HasBits<1> _has_bits_;
bool variance_encoded_in_target_;
float confidence_threshold_;
::google::protobuf::int32 keep_top_k_;
- bool share_location_;
int code_type_;
+ bool share_location_;
+ bool normalized_bbox_;
friend void protobuf_InitDefaults_opencv_2dcaffe_2eproto_impl();
friend void protobuf_AddDesc_opencv_2dcaffe_2eproto_impl();
friend void protobuf_AssignDesc_opencv_2dcaffe_2eproto();
::opencv_caffe::ProposalParameter* release_proposal_param();
void set_allocated_proposal_param(::opencv_caffe::ProposalParameter* proposal_param);
+ // optional .opencv_caffe.PSROIPoolingParameter psroi_pooling_param = 10001;
+ bool has_psroi_pooling_param() const;
+ void clear_psroi_pooling_param();
+ static const int kPsroiPoolingParamFieldNumber = 10001;
+ const ::opencv_caffe::PSROIPoolingParameter& psroi_pooling_param() const;
+ ::opencv_caffe::PSROIPoolingParameter* mutable_psroi_pooling_param();
+ ::opencv_caffe::PSROIPoolingParameter* release_psroi_pooling_param();
+ void set_allocated_psroi_pooling_param(::opencv_caffe::PSROIPoolingParameter* psroi_pooling_param);
+
// optional .opencv_caffe.PythonParameter python_param = 130;
bool has_python_param() const;
void clear_python_param();
inline void clear_has_prior_box_param();
inline void set_has_proposal_param();
inline void clear_has_proposal_param();
+ inline void set_has_psroi_pooling_param();
+ inline void clear_has_psroi_pooling_param();
inline void set_has_python_param();
inline void clear_has_python_param();
inline void set_has_recurrent_param();
inline void clear_has_window_data_param();
::google::protobuf::internal::InternalMetadataWithArena _internal_metadata_;
- ::google::protobuf::internal::HasBits<2> _has_bits_;
+ ::google::protobuf::internal::HasBits<3> _has_bits_;
+ mutable int _cached_size_;
::google::protobuf::RepeatedPtrField< ::std::string> bottom_;
::google::protobuf::RepeatedPtrField< ::std::string> top_;
::google::protobuf::RepeatedField< float > loss_weight_;
::opencv_caffe::PReLUParameter* prelu_param_;
::opencv_caffe::PriorBoxParameter* prior_box_param_;
::opencv_caffe::ProposalParameter* proposal_param_;
+ ::opencv_caffe::PSROIPoolingParameter* psroi_pooling_param_;
::opencv_caffe::PythonParameter* python_param_;
::opencv_caffe::RecurrentParameter* recurrent_param_;
::opencv_caffe::ReductionParameter* reduction_param_;
::opencv_caffe::TileParameter* tile_param_;
::opencv_caffe::WindowDataParameter* window_data_param_;
int phase_;
- mutable int _cached_size_;
friend void protobuf_InitDefaults_opencv_2dcaffe_2eproto_impl();
friend void protobuf_AddDesc_opencv_2dcaffe_2eproto_impl();
friend void protobuf_AssignDesc_opencv_2dcaffe_2eproto();
};
extern ::google::protobuf::internal::ExplicitlyConstructed<ProposalParameter> ProposalParameter_default_instance_;
+// -------------------------------------------------------------------
+
+class PSROIPoolingParameter : public ::google::protobuf::Message /* @@protoc_insertion_point(class_definition:opencv_caffe.PSROIPoolingParameter) */ {
+ public:
+ PSROIPoolingParameter();
+ virtual ~PSROIPoolingParameter();
+
+ PSROIPoolingParameter(const PSROIPoolingParameter& from);
+
+ inline PSROIPoolingParameter& operator=(const PSROIPoolingParameter& from) {
+ CopyFrom(from);
+ return *this;
+ }
+
+ inline const ::google::protobuf::UnknownFieldSet& unknown_fields() const {
+ return _internal_metadata_.unknown_fields();
+ }
+
+ inline ::google::protobuf::UnknownFieldSet* mutable_unknown_fields() {
+ return _internal_metadata_.mutable_unknown_fields();
+ }
+
+ static const ::google::protobuf::Descriptor* descriptor();
+ static const PSROIPoolingParameter& default_instance();
+
+ static const PSROIPoolingParameter* internal_default_instance();
+
+ void Swap(PSROIPoolingParameter* other);
+
+ // implements Message ----------------------------------------------
+
+ inline PSROIPoolingParameter* New() const { return New(NULL); }
+
+ PSROIPoolingParameter* New(::google::protobuf::Arena* arena) const;
+ void CopyFrom(const ::google::protobuf::Message& from);
+ void MergeFrom(const ::google::protobuf::Message& from);
+ void CopyFrom(const PSROIPoolingParameter& from);
+ void MergeFrom(const PSROIPoolingParameter& from);
+ void Clear();
+ bool IsInitialized() const;
+
+ size_t ByteSizeLong() const;
+ bool MergePartialFromCodedStream(
+ ::google::protobuf::io::CodedInputStream* input);
+ void SerializeWithCachedSizes(
+ ::google::protobuf::io::CodedOutputStream* output) const;
+ ::google::protobuf::uint8* InternalSerializeWithCachedSizesToArray(
+ bool deterministic, ::google::protobuf::uint8* output) const;
+ ::google::protobuf::uint8* SerializeWithCachedSizesToArray(::google::protobuf::uint8* output) const {
+ return InternalSerializeWithCachedSizesToArray(false, output);
+ }
+ int GetCachedSize() const { return _cached_size_; }
+ private:
+ void SharedCtor();
+ void SharedDtor();
+ void SetCachedSize(int size) const;
+ void InternalSwap(PSROIPoolingParameter* other);
+ void UnsafeMergeFrom(const PSROIPoolingParameter& from);
+ private:
+ inline ::google::protobuf::Arena* GetArenaNoVirtual() const {
+ return _internal_metadata_.arena();
+ }
+ inline void* MaybeArenaPtr() const {
+ return _internal_metadata_.raw_arena_ptr();
+ }
+ public:
+
+ ::google::protobuf::Metadata GetMetadata() const;
+
+ // nested types ----------------------------------------------------
+
+ // accessors -------------------------------------------------------
+
+ // required float spatial_scale = 1;
+ bool has_spatial_scale() const;
+ void clear_spatial_scale();
+ static const int kSpatialScaleFieldNumber = 1;
+ float spatial_scale() const;
+ void set_spatial_scale(float value);
+
+ // required int32 output_dim = 2;
+ bool has_output_dim() const;
+ void clear_output_dim();
+ static const int kOutputDimFieldNumber = 2;
+ ::google::protobuf::int32 output_dim() const;
+ void set_output_dim(::google::protobuf::int32 value);
+
+ // required int32 group_size = 3;
+ bool has_group_size() const;
+ void clear_group_size();
+ static const int kGroupSizeFieldNumber = 3;
+ ::google::protobuf::int32 group_size() const;
+ void set_group_size(::google::protobuf::int32 value);
+
+ // @@protoc_insertion_point(class_scope:opencv_caffe.PSROIPoolingParameter)
+ private:
+ inline void set_has_spatial_scale();
+ inline void clear_has_spatial_scale();
+ inline void set_has_output_dim();
+ inline void clear_has_output_dim();
+ inline void set_has_group_size();
+ inline void clear_has_group_size();
+
+ // helper for ByteSizeLong()
+ size_t RequiredFieldsByteSizeFallback() const;
+
+ ::google::protobuf::internal::InternalMetadataWithArena _internal_metadata_;
+ ::google::protobuf::internal::HasBits<1> _has_bits_;
+ mutable int _cached_size_;
+ float spatial_scale_;
+ ::google::protobuf::int32 output_dim_;
+ ::google::protobuf::int32 group_size_;
+ friend void protobuf_InitDefaults_opencv_2dcaffe_2eproto_impl();
+ friend void protobuf_AddDesc_opencv_2dcaffe_2eproto_impl();
+ friend void protobuf_AssignDesc_opencv_2dcaffe_2eproto();
+ friend void protobuf_ShutdownFile_opencv_2dcaffe_2eproto();
+
+ void InitAsDefaultInstance();
+};
+extern ::google::protobuf::internal::ExplicitlyConstructed<PSROIPoolingParameter> PSROIPoolingParameter_default_instance_;
+
// ===================================================================
// @@protoc_insertion_point(field_set:opencv_caffe.DetectionOutputParameter.confidence_threshold)
}
+// optional bool normalized_bbox = 10 [default = true];
+inline bool DetectionOutputParameter::has_normalized_bbox() const {
+ return (_has_bits_[0] & 0x00000200u) != 0;
+}
+inline void DetectionOutputParameter::set_has_normalized_bbox() {
+ _has_bits_[0] |= 0x00000200u;
+}
+inline void DetectionOutputParameter::clear_has_normalized_bbox() {
+ _has_bits_[0] &= ~0x00000200u;
+}
+inline void DetectionOutputParameter::clear_normalized_bbox() {
+ normalized_bbox_ = true;
+ clear_has_normalized_bbox();
+}
+inline bool DetectionOutputParameter::normalized_bbox() const {
+ // @@protoc_insertion_point(field_get:opencv_caffe.DetectionOutputParameter.normalized_bbox)
+ return normalized_bbox_;
+}
+inline void DetectionOutputParameter::set_normalized_bbox(bool value) {
+ set_has_normalized_bbox();
+ normalized_bbox_ = value;
+ // @@protoc_insertion_point(field_set:opencv_caffe.DetectionOutputParameter.normalized_bbox)
+}
+
inline const DetectionOutputParameter* DetectionOutputParameter::internal_default_instance() {
return &DetectionOutputParameter_default_instance_.get();
}
// @@protoc_insertion_point(field_set_allocated:opencv_caffe.LayerParameter.proposal_param)
}
+// optional .opencv_caffe.PSROIPoolingParameter psroi_pooling_param = 10001;
+inline bool LayerParameter::has_psroi_pooling_param() const {
+ return (_has_bits_[1] & 0x00020000u) != 0;
+}
+inline void LayerParameter::set_has_psroi_pooling_param() {
+ _has_bits_[1] |= 0x00020000u;
+}
+inline void LayerParameter::clear_has_psroi_pooling_param() {
+ _has_bits_[1] &= ~0x00020000u;
+}
+inline void LayerParameter::clear_psroi_pooling_param() {
+ if (psroi_pooling_param_ != NULL) psroi_pooling_param_->::opencv_caffe::PSROIPoolingParameter::Clear();
+ clear_has_psroi_pooling_param();
+}
+inline const ::opencv_caffe::PSROIPoolingParameter& LayerParameter::psroi_pooling_param() const {
+ // @@protoc_insertion_point(field_get:opencv_caffe.LayerParameter.psroi_pooling_param)
+ return psroi_pooling_param_ != NULL ? *psroi_pooling_param_
+ : *::opencv_caffe::PSROIPoolingParameter::internal_default_instance();
+}
+inline ::opencv_caffe::PSROIPoolingParameter* LayerParameter::mutable_psroi_pooling_param() {
+ set_has_psroi_pooling_param();
+ if (psroi_pooling_param_ == NULL) {
+ psroi_pooling_param_ = new ::opencv_caffe::PSROIPoolingParameter;
+ }
+ // @@protoc_insertion_point(field_mutable:opencv_caffe.LayerParameter.psroi_pooling_param)
+ return psroi_pooling_param_;
+}
+inline ::opencv_caffe::PSROIPoolingParameter* LayerParameter::release_psroi_pooling_param() {
+ // @@protoc_insertion_point(field_release:opencv_caffe.LayerParameter.psroi_pooling_param)
+ clear_has_psroi_pooling_param();
+ ::opencv_caffe::PSROIPoolingParameter* temp = psroi_pooling_param_;
+ psroi_pooling_param_ = NULL;
+ return temp;
+}
+inline void LayerParameter::set_allocated_psroi_pooling_param(::opencv_caffe::PSROIPoolingParameter* psroi_pooling_param) {
+ delete psroi_pooling_param_;
+ psroi_pooling_param_ = psroi_pooling_param;
+ if (psroi_pooling_param) {
+ set_has_psroi_pooling_param();
+ } else {
+ clear_has_psroi_pooling_param();
+ }
+ // @@protoc_insertion_point(field_set_allocated:opencv_caffe.LayerParameter.psroi_pooling_param)
+}
+
// optional .opencv_caffe.PythonParameter python_param = 130;
inline bool LayerParameter::has_python_param() const {
- return (_has_bits_[1] & 0x00020000u) != 0;
+ return (_has_bits_[1] & 0x00040000u) != 0;
}
inline void LayerParameter::set_has_python_param() {
- _has_bits_[1] |= 0x00020000u;
+ _has_bits_[1] |= 0x00040000u;
}
inline void LayerParameter::clear_has_python_param() {
- _has_bits_[1] &= ~0x00020000u;
+ _has_bits_[1] &= ~0x00040000u;
}
inline void LayerParameter::clear_python_param() {
if (python_param_ != NULL) python_param_->::opencv_caffe::PythonParameter::Clear();
// optional .opencv_caffe.RecurrentParameter recurrent_param = 146;
inline bool LayerParameter::has_recurrent_param() const {
- return (_has_bits_[1] & 0x00040000u) != 0;
+ return (_has_bits_[1] & 0x00080000u) != 0;
}
inline void LayerParameter::set_has_recurrent_param() {
- _has_bits_[1] |= 0x00040000u;
+ _has_bits_[1] |= 0x00080000u;
}
inline void LayerParameter::clear_has_recurrent_param() {
- _has_bits_[1] &= ~0x00040000u;
+ _has_bits_[1] &= ~0x00080000u;
}
inline void LayerParameter::clear_recurrent_param() {
if (recurrent_param_ != NULL) recurrent_param_->::opencv_caffe::RecurrentParameter::Clear();
// optional .opencv_caffe.ReductionParameter reduction_param = 136;
inline bool LayerParameter::has_reduction_param() const {
- return (_has_bits_[1] & 0x00080000u) != 0;
+ return (_has_bits_[1] & 0x00100000u) != 0;
}
inline void LayerParameter::set_has_reduction_param() {
- _has_bits_[1] |= 0x00080000u;
+ _has_bits_[1] |= 0x00100000u;
}
inline void LayerParameter::clear_has_reduction_param() {
- _has_bits_[1] &= ~0x00080000u;
+ _has_bits_[1] &= ~0x00100000u;
}
inline void LayerParameter::clear_reduction_param() {
if (reduction_param_ != NULL) reduction_param_->::opencv_caffe::ReductionParameter::Clear();
// optional .opencv_caffe.ReLUParameter relu_param = 123;
inline bool LayerParameter::has_relu_param() const {
- return (_has_bits_[1] & 0x00100000u) != 0;
+ return (_has_bits_[1] & 0x00200000u) != 0;
}
inline void LayerParameter::set_has_relu_param() {
- _has_bits_[1] |= 0x00100000u;
+ _has_bits_[1] |= 0x00200000u;
}
inline void LayerParameter::clear_has_relu_param() {
- _has_bits_[1] &= ~0x00100000u;
+ _has_bits_[1] &= ~0x00200000u;
}
inline void LayerParameter::clear_relu_param() {
if (relu_param_ != NULL) relu_param_->::opencv_caffe::ReLUParameter::Clear();
// optional .opencv_caffe.ReshapeParameter reshape_param = 133;
inline bool LayerParameter::has_reshape_param() const {
- return (_has_bits_[1] & 0x00200000u) != 0;
+ return (_has_bits_[1] & 0x00400000u) != 0;
}
inline void LayerParameter::set_has_reshape_param() {
- _has_bits_[1] |= 0x00200000u;
+ _has_bits_[1] |= 0x00400000u;
}
inline void LayerParameter::clear_has_reshape_param() {
- _has_bits_[1] &= ~0x00200000u;
+ _has_bits_[1] &= ~0x00400000u;
}
inline void LayerParameter::clear_reshape_param() {
if (reshape_param_ != NULL) reshape_param_->::opencv_caffe::ReshapeParameter::Clear();
// optional .opencv_caffe.ROIPoolingParameter roi_pooling_param = 8266711;
inline bool LayerParameter::has_roi_pooling_param() const {
- return (_has_bits_[1] & 0x00400000u) != 0;
+ return (_has_bits_[1] & 0x00800000u) != 0;
}
inline void LayerParameter::set_has_roi_pooling_param() {
- _has_bits_[1] |= 0x00400000u;
+ _has_bits_[1] |= 0x00800000u;
}
inline void LayerParameter::clear_has_roi_pooling_param() {
- _has_bits_[1] &= ~0x00400000u;
+ _has_bits_[1] &= ~0x00800000u;
}
inline void LayerParameter::clear_roi_pooling_param() {
if (roi_pooling_param_ != NULL) roi_pooling_param_->::opencv_caffe::ROIPoolingParameter::Clear();
// optional .opencv_caffe.ScaleParameter scale_param = 142;
inline bool LayerParameter::has_scale_param() const {
- return (_has_bits_[1] & 0x00800000u) != 0;
+ return (_has_bits_[1] & 0x01000000u) != 0;
}
inline void LayerParameter::set_has_scale_param() {
- _has_bits_[1] |= 0x00800000u;
+ _has_bits_[1] |= 0x01000000u;
}
inline void LayerParameter::clear_has_scale_param() {
- _has_bits_[1] &= ~0x00800000u;
+ _has_bits_[1] &= ~0x01000000u;
}
inline void LayerParameter::clear_scale_param() {
if (scale_param_ != NULL) scale_param_->::opencv_caffe::ScaleParameter::Clear();
// optional .opencv_caffe.SigmoidParameter sigmoid_param = 124;
inline bool LayerParameter::has_sigmoid_param() const {
- return (_has_bits_[1] & 0x01000000u) != 0;
+ return (_has_bits_[1] & 0x02000000u) != 0;
}
inline void LayerParameter::set_has_sigmoid_param() {
- _has_bits_[1] |= 0x01000000u;
+ _has_bits_[1] |= 0x02000000u;
}
inline void LayerParameter::clear_has_sigmoid_param() {
- _has_bits_[1] &= ~0x01000000u;
+ _has_bits_[1] &= ~0x02000000u;
}
inline void LayerParameter::clear_sigmoid_param() {
if (sigmoid_param_ != NULL) sigmoid_param_->::opencv_caffe::SigmoidParameter::Clear();
// optional .opencv_caffe.SoftmaxParameter softmax_param = 125;
inline bool LayerParameter::has_softmax_param() const {
- return (_has_bits_[1] & 0x02000000u) != 0;
+ return (_has_bits_[1] & 0x04000000u) != 0;
}
inline void LayerParameter::set_has_softmax_param() {
- _has_bits_[1] |= 0x02000000u;
+ _has_bits_[1] |= 0x04000000u;
}
inline void LayerParameter::clear_has_softmax_param() {
- _has_bits_[1] &= ~0x02000000u;
+ _has_bits_[1] &= ~0x04000000u;
}
inline void LayerParameter::clear_softmax_param() {
if (softmax_param_ != NULL) softmax_param_->::opencv_caffe::SoftmaxParameter::Clear();
// optional .opencv_caffe.SPPParameter spp_param = 132;
inline bool LayerParameter::has_spp_param() const {
- return (_has_bits_[1] & 0x04000000u) != 0;
+ return (_has_bits_[1] & 0x08000000u) != 0;
}
inline void LayerParameter::set_has_spp_param() {
- _has_bits_[1] |= 0x04000000u;
+ _has_bits_[1] |= 0x08000000u;
}
inline void LayerParameter::clear_has_spp_param() {
- _has_bits_[1] &= ~0x04000000u;
+ _has_bits_[1] &= ~0x08000000u;
}
inline void LayerParameter::clear_spp_param() {
if (spp_param_ != NULL) spp_param_->::opencv_caffe::SPPParameter::Clear();
// optional .opencv_caffe.SliceParameter slice_param = 126;
inline bool LayerParameter::has_slice_param() const {
- return (_has_bits_[1] & 0x08000000u) != 0;
+ return (_has_bits_[1] & 0x10000000u) != 0;
}
inline void LayerParameter::set_has_slice_param() {
- _has_bits_[1] |= 0x08000000u;
+ _has_bits_[1] |= 0x10000000u;
}
inline void LayerParameter::clear_has_slice_param() {
- _has_bits_[1] &= ~0x08000000u;
+ _has_bits_[1] &= ~0x10000000u;
}
inline void LayerParameter::clear_slice_param() {
if (slice_param_ != NULL) slice_param_->::opencv_caffe::SliceParameter::Clear();
// optional .opencv_caffe.TanHParameter tanh_param = 127;
inline bool LayerParameter::has_tanh_param() const {
- return (_has_bits_[1] & 0x10000000u) != 0;
+ return (_has_bits_[1] & 0x20000000u) != 0;
}
inline void LayerParameter::set_has_tanh_param() {
- _has_bits_[1] |= 0x10000000u;
+ _has_bits_[1] |= 0x20000000u;
}
inline void LayerParameter::clear_has_tanh_param() {
- _has_bits_[1] &= ~0x10000000u;
+ _has_bits_[1] &= ~0x20000000u;
}
inline void LayerParameter::clear_tanh_param() {
if (tanh_param_ != NULL) tanh_param_->::opencv_caffe::TanHParameter::Clear();
// optional .opencv_caffe.ThresholdParameter threshold_param = 128;
inline bool LayerParameter::has_threshold_param() const {
- return (_has_bits_[1] & 0x20000000u) != 0;
+ return (_has_bits_[1] & 0x40000000u) != 0;
}
inline void LayerParameter::set_has_threshold_param() {
- _has_bits_[1] |= 0x20000000u;
+ _has_bits_[1] |= 0x40000000u;
}
inline void LayerParameter::clear_has_threshold_param() {
- _has_bits_[1] &= ~0x20000000u;
+ _has_bits_[1] &= ~0x40000000u;
}
inline void LayerParameter::clear_threshold_param() {
if (threshold_param_ != NULL) threshold_param_->::opencv_caffe::ThresholdParameter::Clear();
// optional .opencv_caffe.TileParameter tile_param = 138;
inline bool LayerParameter::has_tile_param() const {
- return (_has_bits_[1] & 0x40000000u) != 0;
+ return (_has_bits_[1] & 0x80000000u) != 0;
}
inline void LayerParameter::set_has_tile_param() {
- _has_bits_[1] |= 0x40000000u;
+ _has_bits_[1] |= 0x80000000u;
}
inline void LayerParameter::clear_has_tile_param() {
- _has_bits_[1] &= ~0x40000000u;
+ _has_bits_[1] &= ~0x80000000u;
}
inline void LayerParameter::clear_tile_param() {
if (tile_param_ != NULL) tile_param_->::opencv_caffe::TileParameter::Clear();
// optional .opencv_caffe.WindowDataParameter window_data_param = 129;
inline bool LayerParameter::has_window_data_param() const {
- return (_has_bits_[1] & 0x80000000u) != 0;
+ return (_has_bits_[2] & 0x00000001u) != 0;
}
inline void LayerParameter::set_has_window_data_param() {
- _has_bits_[1] |= 0x80000000u;
+ _has_bits_[2] |= 0x00000001u;
}
inline void LayerParameter::clear_has_window_data_param() {
- _has_bits_[1] &= ~0x80000000u;
+ _has_bits_[2] &= ~0x00000001u;
}
inline void LayerParameter::clear_window_data_param() {
if (window_data_param_ != NULL) window_data_param_->::opencv_caffe::WindowDataParameter::Clear();
inline const ProposalParameter* ProposalParameter::internal_default_instance() {
return &ProposalParameter_default_instance_.get();
}
+// -------------------------------------------------------------------
+
+// PSROIPoolingParameter
+
+// required float spatial_scale = 1;
+inline bool PSROIPoolingParameter::has_spatial_scale() const {
+ return (_has_bits_[0] & 0x00000001u) != 0;
+}
+inline void PSROIPoolingParameter::set_has_spatial_scale() {
+ _has_bits_[0] |= 0x00000001u;
+}
+inline void PSROIPoolingParameter::clear_has_spatial_scale() {
+ _has_bits_[0] &= ~0x00000001u;
+}
+inline void PSROIPoolingParameter::clear_spatial_scale() {
+ spatial_scale_ = 0;
+ clear_has_spatial_scale();
+}
+inline float PSROIPoolingParameter::spatial_scale() const {
+ // @@protoc_insertion_point(field_get:opencv_caffe.PSROIPoolingParameter.spatial_scale)
+ return spatial_scale_;
+}
+inline void PSROIPoolingParameter::set_spatial_scale(float value) {
+ set_has_spatial_scale();
+ spatial_scale_ = value;
+ // @@protoc_insertion_point(field_set:opencv_caffe.PSROIPoolingParameter.spatial_scale)
+}
+
+// required int32 output_dim = 2;
+inline bool PSROIPoolingParameter::has_output_dim() const {
+ return (_has_bits_[0] & 0x00000002u) != 0;
+}
+inline void PSROIPoolingParameter::set_has_output_dim() {
+ _has_bits_[0] |= 0x00000002u;
+}
+inline void PSROIPoolingParameter::clear_has_output_dim() {
+ _has_bits_[0] &= ~0x00000002u;
+}
+inline void PSROIPoolingParameter::clear_output_dim() {
+ output_dim_ = 0;
+ clear_has_output_dim();
+}
+inline ::google::protobuf::int32 PSROIPoolingParameter::output_dim() const {
+ // @@protoc_insertion_point(field_get:opencv_caffe.PSROIPoolingParameter.output_dim)
+ return output_dim_;
+}
+inline void PSROIPoolingParameter::set_output_dim(::google::protobuf::int32 value) {
+ set_has_output_dim();
+ output_dim_ = value;
+ // @@protoc_insertion_point(field_set:opencv_caffe.PSROIPoolingParameter.output_dim)
+}
+
+// required int32 group_size = 3;
+inline bool PSROIPoolingParameter::has_group_size() const {
+ return (_has_bits_[0] & 0x00000004u) != 0;
+}
+inline void PSROIPoolingParameter::set_has_group_size() {
+ _has_bits_[0] |= 0x00000004u;
+}
+inline void PSROIPoolingParameter::clear_has_group_size() {
+ _has_bits_[0] &= ~0x00000004u;
+}
+inline void PSROIPoolingParameter::clear_group_size() {
+ group_size_ = 0;
+ clear_has_group_size();
+}
+inline ::google::protobuf::int32 PSROIPoolingParameter::group_size() const {
+ // @@protoc_insertion_point(field_get:opencv_caffe.PSROIPoolingParameter.group_size)
+ return group_size_;
+}
+inline void PSROIPoolingParameter::set_group_size(::google::protobuf::int32 value) {
+ set_has_group_size();
+ group_size_ = value;
+ // @@protoc_insertion_point(field_set:opencv_caffe.PSROIPoolingParameter.group_size)
+}
+
+inline const PSROIPoolingParameter* PSROIPoolingParameter::internal_default_instance() {
+ return &PSROIPoolingParameter_default_instance_.get();
+}
#endif // !PROTOBUF_INLINE_NOT_IN_HEADERS
// -------------------------------------------------------------------
// -------------------------------------------------------------------
+// -------------------------------------------------------------------
+
// @@protoc_insertion_point(namespace_scope)