Tag: Branch: Tree: e85a802a90

3.4

4.x

5.x

master

next

3.0.0

3.0.0-beta

3.0.0-rc1

3.1.0

3.2.0

3.2.0-rc

3.3.0

3.3.0-rc

3.3.1

3.4.0

3.4.1

3.4.10

3.4.11

3.4.12

3.4.13

3.4.14

3.4.15

3.4.16

3.4.17

3.4.18

3.4.19

3.4.2

3.4.20

3.4.3

3.4.4

3.4.5

3.4.6

3.4.7

3.4.8

3.4.9

4.0.0

4.0.0-alpha

4.0.0-beta

4.0.0-rc

4.0.1

4.1.0

4.1.1

4.1.2

4.10.0

4.11.0

4.2.0

4.3.0

4.4.0

4.5.0

4.5.1

4.5.2

4.5.3

4.5.4

4.5.5

4.6.0

4.7.0

4.8.0

4.8.1

4.9.0

5.0.0-alpha

Branches Tags

${ item.name }

Create tag ${ searchTerm }

Create branch ${ searchTerm }

from 'e85a802a90'

${ noResults }

Commit Graph

1 Commits (e85a802a90afc79fba923b870150c040a574db58)

Author	SHA1	Message	Date
kurnianggoro	e85a802a90	Merge pull request #1257 from kurnianggoro:facelandmark ... GSOC17 - Facemark API (#1257) * Initial commit of facemark API Initial structure of the facemark API and AAM header * make training function as virtual * Add: dataset parser * Bug fix: clear the container before add points * Add: AAM training - procrustes analysis * Add AAM model * Added training function for AAM * Building bot fixes: remove training overload, explicit cast to float for atof * + add dependency: imgcodecs * Build bot fixes: add imgproc.hpp and type casting * Building bot fix: type casting * fixing the AAM training to match with Matlab version fewer model parameters, change the image warp method, change the feature extraction method * add: AAM fitting added several functionalities for fitting * fix warings * Add: transformation for the initial fitting * add sample file for aam implementation * fix warning * Add LFB Header * loadTrainingData: Throw an error message if file not exist * add: LBF prepare training data * add: data augmentation * change to double * add: getMeanShape * shuffling the dataset and parameters initialization * add: initial structure of LBF class * add: getDeltaShapes Difference between the current shape and the desired shape * add: random forest training * generate lbf features * global regression * save training data * fix the parameter initialization * set the default parameters * add: initial version of lbf sample * update the current shape * compute error * add: prediction function * fix some warnings * fitting function the result is mis-aligned, shuould be double checked * add: fitting in the demo * add dependencies * Add: tutorial * add: load model * fixing training * use user defined face detector * Documents, tests, and samples * Allow custom parameters * Cleaning up * Custom parameters for default detector, training, and get custom data * AAM scales * minor fixes , update the opencv_extra files * change path to lbp cascade * face: avoid memory leaks * utilize the filestorage for the model, fixing some minor issues * remove the liblinear dependency * fix the aam test, avoiding to write any files * use RNG and changes the test files	8 years ago