FIx misc. source and comment typos

Found via `codespell -q 3 -S ./3rdparty,./modules -L amin,ang,atleast,dof,endwhile,hist,uint`

backporting of commit: 32aba5e64b

samples/cpp/stitching_detailed.cpp

@@ -581,7 +581,7 @@ int main(int argc, char* argv[])
     vector<Size> sizes(num_images);
     vector<UMat> masks(num_images);
 
-    // Preapre images masks
+    // Prepare images masks
     for (int i = 0; i < num_images; ++i)
     {
         masks[i].create(images[i].size(), CV_8U);

samples/cpp/videocapture_gphoto2_autofocus.cpp

@@ -41,7 +41,7 @@ const int MAX_FOCUS_STEP = 32767;
 const int FOCUS_DIRECTION_INFTY = 1;
 const int DEFAULT_BREAK_LIMIT = 5;
 const int DEFAULT_OUTPUT_FPS = 20;
-const double epsylon = 0.0005; // compression, noice, etc.
+const double epsylon = 0.0005; // compression, noise, etc.
 
 struct Args_t
 {

samples/directx/d3d11_interop.cpp

@@ -83,7 +83,7 @@ public:
         r = m_pD3D11SwapChain->GetBuffer(0, __uuidof(ID3D11Texture2D), (LPVOID*)&m_pBackBuffer);
         if (FAILED(r))
         {
-            throw std::runtime_error("GetBufer() failed!");
+            throw std::runtime_error("GetBuffer() failed!");
         }
 
         r = m_pD3D11Dev->CreateRenderTargetView(m_pBackBuffer, NULL, &m_pRenderTarget);

samples/dnn/face_detector/how_to_train_face_detector.txt

@@ -67,7 +67,7 @@ You need to prepare 2 LMDB databases: one for training images, one for validatio
 
 3. Train your detector
 For training you need to have 3 files: train.prototxt, test.prototxt and solver.prototxt. You can find these files in the same directory as for this readme.
-Also you need to edit train.prototxt and test.prototxt to replace paths for your LMDB databases to actual databases you've crated in step 2.
+Also you need to edit train.prototxt and test.prototxt to replace paths for your LMDB databases to actual databases you've created in step 2.
 
 Now all is done for launch training process.
 Execute next lines in Terminal:

samples/dnn/openpose.py

@@ -88,7 +88,7 @@ while cv.waitKey(1) < 0:
 
     points = []
     for i in range(len(BODY_PARTS)):
-        # Slice heatmap of corresponging body's part.
+        # Slice heatmap of corresponding body's part.
         heatMap = out[0, i, :, :]
 
         # Originally, we try to find all the local maximums. To simplify a sample

samples/opencl/opencl-opencv-interop.cpp

@@ -703,7 +703,7 @@ int App::process_frame_with_open_cl(cv::Mat& frame, bool use_buffer, cl_mem* mem
     if (0 == mem || 0 == m_img_src)
     {
         // allocate/delete cl memory objects every frame for the simplicity.
-        // in real applicaton more efficient pipeline can be built.
+        // in real application more efficient pipeline can be built.
 
         if (use_buffer)
         {

samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py

@@ -66,7 +66,7 @@ def on_high_V_thresh_trackbar(val):
     cv.setTrackbarPos(high_V_name, window_detection_name, high_V)
 
 parser = argparse.ArgumentParser(description='Code for Thresholding Operations using inRange tutorial.')
-parser.add_argument('--camera', help='Camera devide number.', default=0, type=int)
+parser.add_argument('--camera', help='Camera divide number.', default=0, type=int)
 args = parser.parse_args()
 
 ## [cap]

samples/python/tutorial_code/objectDetection/cascade_classifier/objectDetection.py

@@ -25,7 +25,7 @@ def detectAndDisplay(frame):
 parser = argparse.ArgumentParser(description='Code for Cascade Classifier tutorial.')
 parser.add_argument('--face_cascade', help='Path to face cascade.', default='data/haarcascades/haarcascade_frontalface_alt.xml')
 parser.add_argument('--eyes_cascade', help='Path to eyes cascade.', default='data/haarcascades/haarcascade_eye_tree_eyeglasses.xml')
-parser.add_argument('--camera', help='Camera devide number.', type=int, default=0)
+parser.add_argument('--camera', help='Camera divide number.', type=int, default=0)
 args = parser.parse_args()
 
 face_cascade_name = args.face_cascade