Micro Expression
class MicroExpression : GeneratedMessageLite<MessageType, BuilderType> , MetricsProto.MicroExpressionOrBuilder
Represents a detected micro-expression with metadata.
Used for facial expression analysis and emotion detection.
Content copied to clipboard
presage.physiology.MicroExpressionTypes
Link copied to clipboard
class Builder : GeneratedMessageLite.Builder<MessageType, BuilderType> , MetricsProto.MicroExpressionOrBuilder
Represents a detected micro-expression with metadata.
Used for facial expression analysis and emotion detection.
Content copied to clipboard
presage.physiology.MicroExpressionProperties
Functions
Link copied to clipboard
Confidence score for the detection (0.0 to 1.0)
Content copied to clipboard
float confidence = 4;Link copied to clipboard
Link copied to clipboard
String identifier of the detected expression
Content copied to clipboard
string expression = 2;Link copied to clipboard
String identifier of the detected expression
Content copied to clipboard
string expression = 2;Link copied to clipboard
Absolute timestamp at which the micro-expression was detected, in microseconds, since Linux epoch
Content copied to clipboard
int64 timestamp = 5;Link copied to clipboard
Link copied to clipboard
open fun parseDelimitedFrom(input: InputStream, extensionRegistry: ExtensionRegistryLite): MetricsProto.MicroExpression
Link copied to clipboard
open fun parseFrom(data: Array<Byte>, extensionRegistry: ExtensionRegistryLite): MetricsProto.MicroExpression
open fun parseFrom(data: ByteString, extensionRegistry: ExtensionRegistryLite): MetricsProto.MicroExpression
open fun parseFrom(input: CodedInputStream, extensionRegistry: ExtensionRegistryLite): MetricsProto.MicroExpression
open fun parseFrom(input: InputStream, extensionRegistry: ExtensionRegistryLite): MetricsProto.MicroExpression
open fun parseFrom(data: ByteBuffer, extensionRegistry: ExtensionRegistryLite): MetricsProto.MicroExpression
Link copied to clipboard