Merge pull request opencv#19564 from sturkmen72:patch-4

Author: alalek

samples/python/houghcircles.py

@@ -30,6 +30,7 @@ def main():
     circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)
 
     if circles is not None: # Check if circles have been found and only then iterate over these and add them to the image
+        circles = np.uint16(np.around(circles))
         _a, b, _c = circles.shape
         for i in range(b):
             cv.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv.LINE_AA)

samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo1.py

@@ -38,10 +38,10 @@ def Hist_and_Backproj(val):
 
 ## [Read the image]
 parser = argparse.ArgumentParser(description='Code for Back Projection tutorial.')
-parser.add_argument('--input', help='Path to input image.')
+parser.add_argument('--input', help='Path to input image.', default='home.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo2.py

@@ -54,10 +54,10 @@ def Hist_and_Backproj(mask):
 
 # Read the image
 parser = argparse.ArgumentParser(description='Code for Back Projection tutorial.')
-parser.add_argument('--input', help='Path to input image.')
+parser.add_argument('--input', help='Path to input image.', default='home.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/Histograms_Matching/histogram_calculation/calcHist_Demo.py

@@ -53,14 +53,14 @@
 
 ## [Draw for each channel]
 for i in range(1, histSize):
-    cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(b_hist[i-1])) ),
-            ( bin_w*(i), hist_h - int(round(b_hist[i])) ),
+    cv.line(histImage, ( bin_w*(i-1), hist_h - int(b_hist[i-1]) ),
+            ( bin_w*(i), hist_h - int(b_hist[i]) ),
             ( 255, 0, 0), thickness=2)
-    cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(g_hist[i-1])) ),
-            ( bin_w*(i), hist_h - int(round(g_hist[i])) ),
+    cv.line(histImage, ( bin_w*(i-1), hist_h - int(g_hist[i-1]) ),
+            ( bin_w*(i), hist_h - int(g_hist[i]) ),
             ( 0, 255, 0), thickness=2)
-    cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(r_hist[i-1])) ),
-            ( bin_w*(i), hist_h - int(round(r_hist[i])) ),
+    cv.line(histImage, ( bin_w*(i-1), hist_h - int(r_hist[i-1]) ),
+            ( bin_w*(i), hist_h - int(r_hist[i]) ),
             ( 0, 0, 255), thickness=2)
 ## [Draw for each channel]
 

samples/python/tutorial_code/TrackingMotion/corner_subpixels/cornerSubPix_Demo.py

@@ -30,7 +30,7 @@ def goodFeaturesToTrack_Demo(val):
     print('** Number of corners detected:', corners.shape[0])
     radius = 4
     for i in range(corners.shape[0]):
-        cv.circle(copy, (corners[i,0,0], corners[i,0,1]), radius, (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)), cv.FILLED)
+        cv.circle(copy, (int(corners[i,0,0]), int(corners[i,0,1])), radius, (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)), cv.FILLED)
 
     # Show what you got
     cv.namedWindow(source_window)

samples/python/tutorial_code/TrackingMotion/good_features_to_track/goodFeaturesToTrack_Demo.py

@@ -30,7 +30,7 @@ def goodFeaturesToTrack_Demo(val):
     print('** Number of corners detected:', corners.shape[0])
     radius = 4
     for i in range(corners.shape[0]):
-        cv.circle(copy, (corners[i,0,0], corners[i,0,1]), radius, (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)), cv.FILLED)
+        cv.circle(copy, (int(corners[i,0,0]), int(corners[i,0,1])), radius, (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)), cv.FILLED)
 
     # Show what you got
     cv.namedWindow(source_window)

samples/python/tutorial_code/ml/introduction_to_svm/introduction_to_svm.py

@@ -53,7 +53,7 @@
 sv = svm.getUncompressedSupportVectors()
 
 for i in range(sv.shape[0]):
-    cv.circle(image, (sv[i,0], sv[i,1]), 6, (128, 128, 128), thickness)
+    cv.circle(image, (int(sv[i,0]), int(sv[i,1])), 6, (128, 128, 128), thickness)
 ## [show_vectors]
 
 cv.imwrite('result.png', image) # save the image

samples/python/tutorial_code/ml/non_linear_svms/non_linear_svms.py

@@ -94,13 +94,13 @@
 for i in range(NTRAINING_SAMPLES):
     px = trainData[i,0]
     py = trainData[i,1]
-    cv.circle(I, (px, py), 3, (0, 255, 0), thick)
+    cv.circle(I, (int(px), int(py)), 3, (0, 255, 0), thick)
 
 # Class 2
 for i in range(NTRAINING_SAMPLES, 2*NTRAINING_SAMPLES):
     px = trainData[i,0]
     py = trainData[i,1]
-    cv.circle(I, (px, py), 3, (255, 0, 0), thick)
+    cv.circle(I, (int(px), int(py)), 3, (255, 0, 0), thick)
 ## [show_data]
 
 #------------------------- 6. Show support vectors --------------------------------------------
@@ -109,7 +109,7 @@
 sv = svm.getUncompressedSupportVectors()
 
 for i in range(sv.shape[0]):
-    cv.circle(I, (sv[i,0], sv[i,1]), 6, (128, 128, 128), thick)
+    cv.circle(I, (int(sv[i,0]), int(sv[i,1])), 6, (128, 128, 128), thick)
 ## [show_vectors]
 
 cv.imwrite('result.png', I)                      # save the Image

samples/python/tutorial_code/ml/py_svm_opencv/hogsvm.py

@@ -33,7 +33,7 @@ def hog(img):
     return hist
 ## [hog]
 
-img = cv.imread('digits.png',0)
+img = cv.imread(cv.samples.findFile('digits.png'),0)
 if img is None:
     raise Exception("we need the digits.png image from samples/data here !")
 

samples/python/tutorial_code/video/optical_flow/optical_flow.py

@@ -40,15 +40,16 @@
     p1, st, err = cv.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
 
     # Select good points
-    good_new = p1[st==1]
-    good_old = p0[st==1]
+    if p1 is not None:
+        good_new = p1[st==1]
+        good_old = p0[st==1]
 
     # draw the tracks
     for i,(new,old) in enumerate(zip(good_new, good_old)):
         a,b = new.ravel()
         c,d = old.ravel()
-        mask = cv.line(mask, (a,b),(c,d), color[i].tolist(), 2)
-        frame = cv.circle(frame,(a,b),5,color[i].tolist(),-1)
+        mask = cv.line(mask, (int(a),int(b)),(int(c),int(d)), color[i].tolist(), 2)
+        frame = cv.circle(frame,(int(a),int(b)),5,color[i].tolist(),-1)
     img = cv.add(frame,mask)
 
     cv.imshow('frame',img)