fixed digits.py sample to work with opencv 3

samples/python2/digits.py

@@ -74,30 +74,35 @@ class StatModel(object):
 class KNearest(StatModel):
     def __init__(self, k = 3):
         self.k = k
-        self.model = cv2.KNearest()
+        self.model = cv2.ml.KNearest_create()
 
     def train(self, samples, responses):
-        self.model = cv2.KNearest()
-        self.model.train(samples, responses)
+        self.model = cv2.ml.KNearest_create()
+        self.model.train(samples, cv2.ml.ROW_SAMPLE, responses)
 
     def predict(self, samples):
-        retval, results, neigh_resp, dists = self.model.find_nearest(samples, self.k)
+        retval, results, neigh_resp, dists = self.model.findNearest(samples, self.k)
         return results.ravel()
 
 class SVM(StatModel):
     def __init__(self, C = 1, gamma = 0.5):
-        self.params = dict( kernel_type = cv2.SVM_RBF,
-                            svm_type = cv2.SVM_C_SVC,
+        self.params = dict( kernel_type = cv2.ml.SVM_RBF,
+                            svm_type = cv2.ml.SVM_C_SVC,
                             C = C,
                             gamma = gamma )
-        self.model = cv2.SVM()
+        self.model = cv2.ml.SVM_create()
 
     def train(self, samples, responses):
-        self.model = cv2.SVM()
-        self.model.train(samples, responses, params = self.params)
+        self.model = cv2.ml.SVM_create()
+        """ original code """
+        #self.model.train(samples, responses, params = self.params)
+        """ but it's either this """
+        self.model.train(samples, cv2.ml.ROW_SAMPLE, responses)
+        """ or this """
+        #self.model.train(samples, params = self.params)
 
     def predict(self, samples):
-        return self.model.predict_all(samples).ravel()
+        return self.model.predict(samples)[1][0].ravel()
 
 
 def evaluate_model(model, digits, samples, labels):