def precornerdetect(image):
# assume that the image is floating-point
corners = cv.CloneMat(image)
cv.PreCornerDetect(image, corners, 3)
dilated_corners = cv.CloneMat(image)
cv.Dilate(corners, dilated_corners, None, 1)
corner_mask = cv.CreateMat(image.rows, image.cols, cv.CV_8UC1)
cv.Sub(corners, dilated_corners, corners)
cv.CmpS(corners, 0, corner_mask, cv.CV_CMP_GE)
return (corners, corner_mask)
py_img = 255 * (py_img / np.max(py_img))
img = cv.fromarray(py_img.astype(np.uint8))
rgb_img = cv.CreateImage((img.cols, img.rows), 8, 4)
"""Creating RGB img"""
img_r = cv.CloneMat(img)
img_g = cv.CreateImage((img.cols, img.rows), 8, 1)
img_b = cv.CreateImage((img.cols, img.rows), 8, 1)
img_a = cv.CreateImage((img.cols, img.rows), 8, 1)
cv.Set(img_g, 10)
cv.Set(img_b, 100)
cv.Set(img_a, 100)
cv.Merge(img_b, img_g, img_r, img_a, rgb_img)
"""Precorner detect"""
corners = cv.CreateMat(float_img.rows, float_img.cols, float_img.type)
cv.PreCornerDetect(float_img, corners, 3)
"""Canny"""
edges = cv.CreateImage((img.cols, img.rows), 8, 1)
print img.rows, img.cols, edges.height
cv.Canny(img, edges, 20.0, 160.0)
disp2 = edges
"""Good features to track"""
eig_image = cv.CreateMat(img.rows, img.cols, cv.CV_32FC1)
temp_image = cv.CreateMat(img.rows, img.cols, cv.CV_32FC1)
features_x_y_vector = cv.GoodFeaturesToTrack(img,
eig_image,
temp_image,
10,
0.002,
1.0,
useHarris=True)