How to get the auc

[HelloRicky123]

Hi Mr.Zhang,
I trained the model 30 epoches and used the code in https://github.com/bilylee/tracker_benchmark you provide to produce the result on OTB100, and I got aveCoverage and aveErrCenter. The following is my result. But I don't know how to get the auc. I saved the predicted boxes and groundtruth boxes and calculate the auc myself and get 0.62+, but I think it's a little too high. So I wanna if the code you provide can produce auc?
Thanks a lot!
All.json
{"name": "ALL", "desc": "All attributes", "tracker": "SiameseFC", "evalType": "OPE", "seqs": ["Basketball", "Biker", "Bird1", "Bird2", "BlurBody", "BlurCar1", "BlurCar2", "BlurCar3", "BlurCar4", "BlurFace", "BlurOwl", "Board", "Bolt", "Bolt2", "Box", "Boy", "Car1", "Car2", "Car24", "Car4", "CarDark", "CarScale", "ClifBar", "Coke", "Couple", "Coupon", "Crossing", "Crowds", "Dancer", "Dancer2", "David", "David2", "David3", "Deer", "Diving", "Dog", "Dog1", "Doll", "DragonBaby", "Dudek", "FaceOcc1", "FaceOcc2", "Fish", "FleetFace", "Football", "Football1", "Freeman1", "Freeman3", "Freeman4", "Girl", "Girl2", "Gym", "Human2", "Human3", "Human4-2", "Human5", "Human6", "Human7", "Human8", "Human9", "Ironman", "Jogging-1", "Jogging-2", "Jump", "Jumping", "KiteSurf", "Lemming", "Liquor", "Man", "Matrix", "Mhyang", "MotorRolling", "MountainBike", "Panda", "RedTeam", "Rubik", "Shaking", "Singer1", "Singer2", "Skater", "Skater2", "Skating1", "Skating2-1", "Skating2-2", "Skiing", "Soccer", "Subway", "Surfer", "Suv", "Sylvester", "Tiger1", "Tiger2", "Toy", "Trans", "Trellis", "Twinnings", "Vase", "Walking", "Walking2", "Woman"], "overlap": 66.20537032522891, "error": 2.833591675153366, "overlapScores": [0.5926672927432785, 0.6744523158948802, 0.4758998916413733, 0.7696486706086082, 0.6853726089480511, 0.8345670514668277, 0.844032160931591, 0.8213972449066869, 0.8405619493081518, 0.8062361033658137, 0.8204389268634588, 0.44990766176914604, 0.5834594717187838, 0.5628299575581555, 0.6798351199956547, 0.7882560429522064, 0.805657077100189, 0.866769542199004, 0.8205198622192008, 0.846973290787438, 0.8637282909664755, 0.6275478765070535, 0.5131748615738081, 0.5803322245017029, 0.7265976675636683, 0.7794657551593479, 0.739760754058129, 0.6790682336800818, 0.7631618448786447, 0.742207866456886, 0.6405737645381154, 0.7975168491398508, 0.5263560801177612, 0.7363679925157307, 0.2904404740180546, 0.46867412460127506, 0.8303155589968413, 0.752400038255508, 0.6498460887560017, 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0.8286922892630049, 0.7472081492641974, 0.5316698896855354, 0.4845309321917454, 0.5754776107639107, 0.574880852519549, 0.6305495126856653, 0.6732596158125619, 0.5628371975785968, 0.7222802154172178, 0.6133800988493966, 0.4453594267695019], "errorNum": [5.1448275862068975, 5.352112676056338, 8.480392156862745, 0.6060606060606061, 0.14970059880239522, 0.013477088948787063, 0.0, 0.0, 0.0, 0.0, 0.03169572107765452, 8.753581661891118, 9.857142857142858, 5.665529010238908, 1.8776916451335057, 0.016611295681063124, 0.0, 0.0, 0.06211180124223602, 0.0, 3.0279898218829517, 2.9365079365079367, 5.148305084745762, 2.027491408934708, 0.07142857142857142, 6.146788990825688, 0.08333333333333333, 1.1527377521613833, 0.0, 0.06666666666666667, 3.1210191082802545, 0.148975791433892, 5.515873015873016, 0.0, 8.883720930232558, 6.062992125984252, 0.0, 0.1472107438016529, 1.858407079646018, 0.7074235807860262, 0.0, 1.958128078817734, 0.14705882352941177, 2.446958981612447, 6.961325966850829, 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[StrangerZhang]

Just caculate the mean of successRateList