View Source Evision.FaceRecognizerSF (Evision v0.1.8)
Link to this section Summary
cv
Aligning image to put face on the standard position
Aligning image to put face on the standard position
Creates an instance of this class with given parameters
Creates an instance of this class with given parameters
Extracting face feature from aligned image
Extracting face feature from aligned image
Calculating the distance between two face features
Calculating the distance between two face features
Functions
Raising version of alignCrop/3
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Raising version of alignCrop/4
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Raising version of create/2
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Raising version of create/3
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Raising version of feature/2
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Raising version of feature/3
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Raising version of match/3
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Raising version of match/4
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Link to this section cv
Aligning image to put face on the standard position
Positional Arguments
src_img:
Evision.Mat
.input image
face_box:
Evision.Mat
.the detection result used for indicate face in input image
Return
aligned_img:
Evision.Mat
.output aligned image
Python prototype (for reference):
alignCrop(src_img, face_box[, aligned_img]) -> aligned_img
Aligning image to put face on the standard position
Positional Arguments
src_img:
Evision.Mat
.input image
face_box:
Evision.Mat
.the detection result used for indicate face in input image
Return
aligned_img:
Evision.Mat
.output aligned image
Python prototype (for reference):
alignCrop(src_img, face_box[, aligned_img]) -> aligned_img
Creates an instance of this class with given parameters
Positional Arguments
model:
String
.the path of the onnx model used for face recognition
config:
String
.the path to the config file for compability, which is not requested for ONNX models
Keyword Arguments
backend_id:
int
.the id of backend
target_id:
int
.the id of target device
Python prototype (for reference):
create(model, config[, backend_id[, target_id]]) -> retval
Creates an instance of this class with given parameters
Positional Arguments
model:
String
.the path of the onnx model used for face recognition
config:
String
.the path to the config file for compability, which is not requested for ONNX models
Keyword Arguments
backend_id:
int
.the id of backend
target_id:
int
.the id of target device
Python prototype (for reference):
create(model, config[, backend_id[, target_id]]) -> retval
Extracting face feature from aligned image
Positional Arguments
aligned_img:
Evision.Mat
.input aligned image
Return
face_feature:
Evision.Mat
.output face feature
Python prototype (for reference):
feature(aligned_img[, face_feature]) -> face_feature
Extracting face feature from aligned image
Positional Arguments
aligned_img:
Evision.Mat
.input aligned image
Return
face_feature:
Evision.Mat
.output face feature
Python prototype (for reference):
feature(aligned_img[, face_feature]) -> face_feature
Calculating the distance between two face features
Positional Arguments
face_feature1:
Evision.Mat
.the first input feature
face_feature2:
Evision.Mat
.the second input feature of the same size and the same type as face_feature1
Keyword Arguments
dis_type:
int
.defining the similarity with optional values "FR_OSINE" or "FR_NORM_L2"
Python prototype (for reference):
match(face_feature1, face_feature2[, dis_type]) -> retval
Calculating the distance between two face features
Positional Arguments
face_feature1:
Evision.Mat
.the first input feature
face_feature2:
Evision.Mat
.the second input feature of the same size and the same type as face_feature1
Keyword Arguments
dis_type:
int
.defining the similarity with optional values "FR_OSINE" or "FR_NORM_L2"
Python prototype (for reference):
match(face_feature1, face_feature2[, dis_type]) -> retval
Link to this section Functions
Raising version of alignCrop/3
.
Raising version of alignCrop/4
.
Raising version of create/2
.
Raising version of create/3
.
Raising version of feature/2
.
Raising version of feature/3
.
Raising version of match/3
.
Raising version of match/4
.