ml/python: fix digits samples(3.4)

samples/python/digits.py

@@ -70,13 +70,8 @@ def deskew(img):
     img = cv.warpAffine(img, M, (SZ, SZ), flags=cv.WARP_INVERSE_MAP | cv.INTER_LINEAR)
     return img
 
-class StatModel(object):
-    def load(self, fn):
-        self.model.load(fn)  # Known bug: https://github.com/opencv/opencv/issues/4969
-    def save(self, fn):
-        self.model.save(fn)
 
-class KNearest(StatModel):
+class KNearest(object):
     def __init__(self, k = 3):
         self.k = k
         self.model = cv.ml.KNearest_create()
@@ -88,7 +83,13 @@ class KNearest(StatModel):
         _retval, results, _neigh_resp, _dists = self.model.findNearest(samples, self.k)
         return results.ravel()
 
-class SVM(StatModel):
+    def load(self, fn):
+        self.model = cv.ml.KNearest_load(fn)
+
+    def save(self, fn):
+        self.model.save(fn)
+
+class SVM(object):
     def __init__(self, C = 1, gamma = 0.5):
         self.model = cv.ml.SVM_create()
         self.model.setGamma(gamma)
@@ -102,6 +103,11 @@ class SVM(StatModel):
     def predict(self, samples):
         return self.model.predict(samples)[1].ravel()
 
+    def load(self, fn):
+        self.model = cv.ml.SVM_load(fn)
+
+    def save(self, fn):
+        self.model.save(fn)
 
 def evaluate_model(model, digits, samples, labels):
     resp = model.predict(samples)

samples/python/digits_video.py

@@ -1,4 +1,12 @@
 #!/usr/bin/env python
+'''
+Digit recognition from video.
+
+Run digits.py before, to train and save the SVM.
+
+Usage:
+  digits_video.py [{camera_id|video_file}]
+'''
 
 # Python 2/3 compatibility
 from __future__ import print_function
@@ -28,11 +36,7 @@ def main():
         print('"%s" not found, run digits.py first' % classifier_fn)
         return
 
-    if True:
     model = cv.ml.SVM_load(classifier_fn)
-    else:
-        model = cv.ml.SVM_create()
-        model.load_(classifier_fn) #Known bug: https://github.com/opencv/opencv/issues/4969
 
     while True:
         _ret, frame = cap.read()