diff --git a/PythonAPI/pycocotools/cocoeval.py b/PythonAPI/pycocotools/cocoeval.py
index 7a4b4ad..d573a51 100644
--- a/PythonAPI/pycocotools/cocoeval.py
+++ b/PythonAPI/pycocotools/cocoeval.py
@@ -68,7 +68,6 @@ def __init__(self, cocoGt=None, cocoDt=None, iouType='segm'):
             print('iouType not specified. use default iouType segm')
         self.cocoGt   = cocoGt              # ground truth COCO API
         self.cocoDt   = cocoDt              # detections COCO API
-        self.params   = {}                  # evaluation parameters
         self.evalImgs = defaultdict(list)   # per-image per-category evaluation results [KxAxI] elements
         self.eval     = {}                  # accumulated evaluation results
         self._gts = defaultdict(list)       # gt for evaluation
@@ -203,7 +202,7 @@ def computeOks(self, imgId, catId):
         if len(gts) == 0 or len(dts) == 0:
             return []
         ious = np.zeros((len(dts), len(gts)))
-        sigmas = np.array([.26, .25, .25, .35, .35, .79, .79, .72, .72, .62,.62, 1.07, 1.07, .87, .87, .89, .89])/10.0
+        sigmas = p.kpt_oks_sigmas
         vars = (sigmas * 2)**2
         k = len(sigmas)
         # compute oks between each detection and ground truth object
@@ -521,6 +520,7 @@ def setKpParams(self):
         self.areaRng = [[0 ** 2, 1e5 ** 2], [32 ** 2, 96 ** 2], [96 ** 2, 1e5 ** 2]]
         self.areaRngLbl = ['all', 'medium', 'large']
         self.useCats = 1
+        self.kpt_oks_sigmas = np.array([.26, .25, .25, .35, .35, .79, .79, .72, .72, .62,.62, 1.07, 1.07, .87, .87, .89, .89])/10.0
 
     def __init__(self, iouType='segm'):
         if iouType == 'segm' or iouType == 'bbox':