thomasjungblut

from bayes_opt import BayesianOptimization
from sklearn.cross_validation import KFold
import xgboost as xgb

def xgbCv(train, features, numRounds, eta, gamma, maxDepth, minChildWeight, subsample, colSample):   
   # prepare xgb parameters 
   params = {
            "objective": "reg:linear",
            "booster" : "gbtree",
            "eval_metric": "mae",            

farrajota

function mpii_convert_json(  )
% convert mpii annotations .mat file to .json


%% load annotation file
fprintf('Load annotations... ')
data = load('/media/HDD2/Datasets/Human_Pose/mpii/mpii_human_pose_v1_u12_2/mpii_human_pose_v1_u12_1.mat');
fprintf('Done.\n')
%% open file
fprintf('Open file mpii_human_pose_annotations.json\n')