Description of Vision Results#
本文档的中文版本参考视觉模型预测结果说明
ClassifyResult#
The code of ClassifyResult is defined in fastdeploy/vision/common/result.h
and is used to indicate the classification label result and confidence the image.
API: fastdeploy.vision.ClassifyResult
, The ClassifyResult will return:
label_ids(list of int):Member variables that represent the classification label results of a single image, the number of which is determined by the
topk
passed in when using the classification model. For example, you can return the label results of the Top 5 categories.scores(list of float):Member variables that indicate the confidence level of a single image on the corresponding classification result, the number of which is determined by the
topk
passed in when using the classification model, e.g. the confidence level of a Top 5 classification can be returned.
SegmentationResult#
The code of SegmentationResult is defined in fastdeploy/vision/common/result.h
and is used to indicate the segmentation category predicted for each pixel in the image and the probability of the segmentation category.
API: fastdeploy.vision.SegmentationResult
, The SegmentationResult will return:
label_ids(list of int):Member variable indicating the segmentation category for each pixel of a single image.
score_map(list of float):Member variable, the predicted probability value of the segmentation category corresponding to
label_map
(specified when exporting the model--output_op argmax
) or the probability value normalized by softmax (specified when exporting the model--output_op softmax
or when exporting the model--output_op none
and set the model class member attributeapply_softmax=true
when initializing the model).shape(list of int):Member variable indicating the shape of the output image, as
H*W
.
DetectionResult#
The code of DetectionResult is defined in fastdeploy/vision/common/result.h
and is used to indicate the target location (detection box), target class and target confidence level detected by the image.
API: fastdeploy.vision.DetectionResult
, The DetectionResult will return:
boxes(list of list(float)):Member variable, represents the coordinates of all target boxes detected by a single image. boxes is a list, each element of which is a list of length 4, representing a box with 4 float values in order of xmin, ymin, xmax, ymax, i.e. the coordinates of the top left and bottom right corners.
scores(list of float):Member variable indicating the confidence of all targets detected by a single image.
label_ids(list of int):Member variable indicating all target categories detected for a single image.
masks:Member variable that represents all instances of mask detected from a single image, with the same number of elements and shape size as boxes.
contain_masks:Member variable indicating whether the detection result contains the instance mask, the result of the instance segmentation model is generally set to
True
.
API: fastdeploy.vision.Mask
, The Mask will return:
data:Member variable indicating a detected mask.
shape:Member variable representing the shape of the mask, e.g.
(H,W)
.
FaceDetectionResult#
The FaceDetectionResult code is defined in fastdeploy/vision/common/result.h
and is used to indicate the target frames detected by face detection, face landmarks, target confidence and the number of landmarks per face.
API: fastdeploy.vision.FaceDetectionResult
, The FaceDetectionResult will return:
data(list of list(float)):Member variables that represent the coordinates of all target boxes detected by a single image. boxes is a list, each element of which is a list of length 4, representing a box with 4 float values in order of xmin, ymin, xmax, ymax, i.e. the coordinates of the top left and bottom right corners.
scores(list of float):Member variable indicating the confidence of all targets detected by a single image.
landmarks(list of list(float)): Member variables that represent the key points of all faces detected by a single image.
landmarks_per_face(int):Member variable indicating the number of key points in each face frame.
KeyPointDetectionResult#
The KeyPointDetectionResult code is defined in fastdeploy/vision/common/result.h
and is used to indicate the coordinates and confidence of each keypoint of the target behavior in the image.
API:fastdeploy.vision.KeyPointDetectionResult
, The KeyPointDetectionResult will return:
keypoints(list of list(float)): Member variable, representing the key point coordinates of the identified target behavior.
keypoints.size()= N * J
,N
: number of objects in the pictureJ
: num_joints(number of keypoints for a target)
scores(list of float): Member variable, representing the confidence of the keypoint coordinates of the recognized target behavior.
scores.size()= N * J
N
: number of objects in the pictureJ
: num_joints(number of keypoints for a target)
num_joints(int): Member variable, representing the number of keypoints for a target
FaceRecognitionResult#
The FaceRecognitionResult code is defined in fastdeploy/vision/common/result.h
and is used to indicate the embedding of the image features by the face recognition model.
API: fastdeploy.vision.FaceRecognitionResult
, The FaceRecognitionResult will return:
landmarks_per_face(list of float):Member variables, which indicate the final extracted features embedding of the face recognition model, can be used to calculate the feature similarity between faces.
MattingResult#
The MattingResult code is defined in fastdeploy/vision/common/result.h
and is used to indicate the value of alpha transparency predicted by the model, the predicted outlook, etc.
API:fastdeploy.vision.MattingResult
, The MattingResult will return:
alpha(list of float):This is a one-dimensional vector of predicted alpha transparency values in the range
[0.,1.]
, with lengthH*W
, H,W being the height and width of the input image.foreground(list of float):This is a one-dimensional vector for the predicted foreground, the value domain is
[0.,255.]
, the length isH*W*C
, H,W is the height and width of the input image, C is generally 3, foreground is not necessarily there, only if the model itself predicts the foreground, this property will be valid.contain_foreground(bool):Indicates whether the predicted outcome includes the foreground.
shape(list of int): When
contain_foreground
is false, the shape only contains(H,W)
, whencontain_foreground
istrue,
the shape contains(H,W,C)
, C is generally 3.
OCRResult#
The OCRResult code is defined in fastdeploy/vision/common/result.h
and is used to indicate the text box detected in the image, the text box orientation classification, and the text content recognized inside the text box.
API:fastdeploy.vision.OCRResult
, The OCRResult will return:
boxes(list of list(int)): Member variable, indicates the coordinates of all target boxes detected in a single image,
boxes.size()
indicates the number of boxes detected in a single image, each box is represented by 8 int values in order of the 4 coordinate points of the box, the order is lower left, lower right, upper right, upper left.text(list of string):Member variable indicating the content of the recognized text in multiple text boxes, with the same number of elements as
boxes.size()
.rec_scores(list of float):Member variable indicating the confidence level of the text identified in the box, the number of elements is the same as
boxes.size()
.cls_scores(list of float):Member variable indicating the confidence level of the classification result of the text box, with the same number of elements as
boxes.size()
.cls_labels(list of int):Member variable indicating the orientation category of the text box, the number of elements is the same as
boxes.size()
.
FaceAlignmentResult#
The code of FaceAlignmentResult is defined in fastdeploy/vision/common/result.h
and is used to indicate the key points of the face.
API: fastdeploy.vision.FaceAlignmentResult
, The FaceAlignmentResult will return:
landmarks(list of list(float)):Member variables that represent the all key points detected from a single face image.
HeadPoseResult#
The code of HeadPoseResult is defined in fastdeploy/vision/common/result.h
and is used to indicate the head pose result.
API: fastdeploy.vision.HeadPoseResult
, The HeadPoseResult will return:
euler_angles(list of float):Member variables that represent the Euler angle predicted by a single face image. The storage order is (yaw, pitch, roll), yaw represents the horizontal angle, pitch represents the vertical angle, roll represents the roll angle, and the value range is [-90, +90] Spend.