Merge pull request #7549 from StevenPuttemans:add_sample_content

pull/7534/merge
Vadim Pisarevsky 8 years ago
commit b077d6a192
  1. 2
      doc/py_tutorials/py_core/py_basic_ops/py_basic_ops.markdown
  2. 4
      doc/py_tutorials/py_core/py_image_arithmetics/py_image_arithmetics.markdown
  3. 2
      doc/py_tutorials/py_imgproc/py_filtering/py_filtering.markdown
  4. 2
      doc/py_tutorials/py_imgproc/py_geometric_transformations/py_geometric_transformations.markdown
  5. 2
      doc/py_tutorials/py_imgproc/py_houghcircles/py_houghcircles.markdown
  6. 4
      doc/py_tutorials/py_imgproc/py_houghlines/py_houghlines.markdown
  7. 2
      doc/py_tutorials/py_imgproc/py_thresholding/py_thresholding.markdown
  8. 4
      samples/cpp/peopledetect.cpp
  9. BIN
      samples/data/apple.jpg
  10. BIN
      samples/data/gradient.png
  11. BIN
      samples/data/ml.png
  12. BIN
      samples/data/opencv-logo-white.png
  13. BIN
      samples/data/opencv-logo.png
  14. BIN
      samples/data/orange.jpg
  15. BIN
      samples/data/sudoku.png
  16. 0
      samples/data/vtest.avi
  17. 8
      samples/gpu/bgfg_segm.cpp
  18. 4
      samples/gpu/performance/tests.cpp
  19. 10
      samples/tapi/bgfg_segm.cpp
  20. 2
      samples/tapi/hog.cpp

@ -173,7 +173,7 @@ from matplotlib import pyplot as plt
BLUE = [255,0,0]
img1 = cv2.imread('opencv_logo.png')
img1 = cv2.imread('opencv-logo.png')
replicate = cv2.copyMakeBorder(img1,10,10,10,10,cv2.BORDER_REPLICATE)
reflect = cv2.copyMakeBorder(img1,10,10,10,10,cv2.BORDER_REFLECT)

@ -51,7 +51,7 @@ is given 0.3. cv2.addWeighted() applies following equation on the image.
Here \f$\gamma\f$ is taken as zero.
@code{.py}
img1 = cv2.imread('ml.png')
img2 = cv2.imread('opencv_logo.jpg')
img2 = cv2.imread('opencv-logo.png')
dst = cv2.addWeighted(img1,0.7,img2,0.3,0)
@ -77,7 +77,7 @@ bitwise operations as below:
@code{.py}
# Load two images
img1 = cv2.imread('messi5.jpg')
img2 = cv2.imread('opencv_logo.png')
img2 = cv2.imread('opencv-logo.png')
# I want to put logo on top-left corner, So I create a ROI
rows,cols,channels = img2.shape

@ -69,7 +69,7 @@ import cv2
import numpy as np
from matplotlib import pyplot as plt
img = cv2.imread('opencv_logo.png')
img = cv2.imread('opencv-logo-white.png')
blur = cv2.blur(img,(5,5))

@ -135,7 +135,7 @@ matrix.
See the code below:
@code{.py}
img = cv2.imread('sudokusmall.png')
img = cv2.imread('sudoku.png')
rows,cols,ch = img.shape
pts1 = np.float32([[56,65],[368,52],[28,387],[389,390]])

@ -23,7 +23,7 @@ explained in the documentation. So we directly go to the code.
import cv2
import numpy as np
img = cv2.imread('opencv_logo.png',0)
img = cv2.imread('opencv-logo-white.png',0)
img = cv2.medianBlur(img,5)
cimg = cv2.cvtColor(img,cv2.COLOR_GRAY2BGR)

@ -73,7 +73,7 @@ represents the minimum length of line that should be detected.
import cv2
import numpy as np
img = cv2.imread('dave.jpg')
img = cv2.imread('sudoku.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
@ -121,7 +121,7 @@ the parameters of lines, and you had to find all the points. Here, everything is
import cv2
import numpy as np
img = cv2.imread('dave.jpg')
img = cv2.imread('sudoku.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
lines = cv2.HoughLinesP(edges,1,np.pi/180,100,minLineLength=100,maxLineGap=10)

@ -87,7 +87,7 @@ import cv2
import numpy as np
from matplotlib import pyplot as plt
img = cv2.imread('dave.jpg',0)
img = cv2.imread('sudoku.png',0)
img = cv2.medianBlur(img,5)
ret,th1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)

@ -16,7 +16,7 @@ const char* keys =
"{ help h | | print help message }"
"{ image i | | specify input image}"
"{ camera c | | enable camera capturing }"
"{ video v | ../data/768x576.avi | use video as input }"
"{ video v | ../data/vtest.avi | use video as input }"
"{ directory d | | images directory}"
};
@ -79,7 +79,7 @@ int main(int argc, char** argv)
namedWindow("people detector", 1);
string pattern_glob = "";
string video_filename = "../data/768x576.avi";
string video_filename = "../data/vtest.avi";
int camera_id = -1;
if (parser.has("directory"))
{

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@ -23,10 +23,10 @@ enum Method
int main(int argc, const char** argv)
{
cv::CommandLineParser cmd(argc, argv,
"{ c camera | | use camera }"
"{ f file | ../data/768x576.avi | input video file }"
"{ m method | mog | method (mog, mog2, gmg, fgd) }"
"{ h help | | print help message }");
"{ c camera | | use camera }"
"{ f file | ../data/vtest.avi | input video file }"
"{ m method | mog | method (mog, mog2, gmg, fgd) }"
"{ h help | | print help message }");
if (cmd.has("help") || !cmd.check())
{

@ -1191,10 +1191,10 @@ TEST(GoodFeaturesToTrack)
TEST(MOG)
{
const std::string inputFile = abspath("../data/768x576.avi");
const std::string inputFile = abspath("../data/vtest.avi");
cv::VideoCapture cap(inputFile);
if (!cap.isOpened()) throw runtime_error("can't open ../data/768x576.avi");
if (!cap.isOpened()) throw runtime_error("can't open ../data/vtest.avi");
cv::Mat frame;
cap >> frame;

@ -17,11 +17,11 @@ using namespace cv;
int main(int argc, const char** argv)
{
CommandLineParser cmd(argc, argv,
"{ c camera | | use camera }"
"{ f file | ../data/768x576.avi | input video file }"
"{ t type | mog2 | method's type (knn, mog2) }"
"{ h help | | print help message }"
"{ m cpu_mode | false | press 'm' to switch OpenCL<->CPU}");
"{ c camera | | use camera }"
"{ f file | ../data/vtest.avi | input video file }"
"{ t type | mog2 | method's type (knn, mog2) }"
"{ h help | | print help message }"
"{ m cpu_mode | false | press 'm' to switch OpenCL<->CPU}");
if (cmd.has("help"))
{

@ -71,7 +71,7 @@ int main(int argc, char** argv)
"{ h help | | print help message }"
"{ i input | | specify input image}"
"{ c camera | -1 | enable camera capturing }"
"{ v video | ../data/768x576.avi | use video as input }"
"{ v video | ../data/vtest.avi | use video as input }"
"{ g gray | | convert image to gray one or not}"
"{ s scale | 1.0 | resize the image before detect}"
"{ o output | | specify output path when input is images}";

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