62 lines
2.3 KiB
Python
62 lines
2.3 KiB
Python
import sys
|
|
import cv
|
|
|
|
def hs_histogram(src):
|
|
# Convert to HSV
|
|
hsv = cv.CreateImage(cv.GetSize(src), 8, 3)
|
|
cv.CvtColor(src, hsv, cv.CV_BGR2HSV)
|
|
|
|
# Extract the H and S planes
|
|
h_plane = cv.CreateMat(src.rows, src.cols, cv.CV_8UC1)
|
|
s_plane = cv.CreateMat(src.rows, src.cols, cv.CV_8UC1)
|
|
cv.Split(hsv, h_plane, s_plane, None, None)
|
|
planes = [h_plane, s_plane]
|
|
|
|
h_bins = 30
|
|
s_bins = 32
|
|
hist_size = [h_bins, s_bins]
|
|
# hue varies from 0 (~0 deg red) to 180 (~360 deg red again */
|
|
h_ranges = [0, 180]
|
|
# saturation varies from 0 (black-gray-white) to
|
|
# 255 (pure spectrum color)
|
|
s_ranges = [0, 255]
|
|
ranges = [h_ranges, s_ranges]
|
|
scale = 10
|
|
hist = cv.CreateHist([h_bins, s_bins], cv.CV_HIST_ARRAY, ranges, 1)
|
|
cv.CalcHist([cv.GetImage(i) for i in planes], hist)
|
|
(_, max_value, _, _) = cv.GetMinMaxHistValue(hist)
|
|
|
|
hist_img = cv.CreateImage((h_bins*scale, s_bins*scale), 8, 3)
|
|
|
|
for h in range(h_bins):
|
|
for s in range(s_bins):
|
|
bin_val = cv.QueryHistValue_2D(hist, h, s)
|
|
intensity = cv.Round(bin_val * 255 / max_value)
|
|
cv.Rectangle(hist_img,
|
|
(h*scale, s*scale),
|
|
((h+1)*scale - 1, (s+1)*scale - 1),
|
|
cv.RGB(intensity, intensity, intensity),
|
|
cv.CV_FILLED)
|
|
return hist_img
|
|
|
|
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)
|
|
|
|
def findstereocorrespondence(image_left, image_right):
|
|
# image_left and image_right are the input 8-bit single-channel images
|
|
# from the left and the right cameras, respectively
|
|
(r, c) = (image_left.rows, image_left.cols)
|
|
disparity_left = cv.CreateMat(r, c, cv.CV_16S)
|
|
disparity_right = cv.CreateMat(r, c, cv.CV_16S)
|
|
state = cv.CreateStereoGCState(16, 2)
|
|
cv.FindStereoCorrespondenceGC(image_left, image_right, disparity_left, disparity_right, state, 0)
|
|
return (disparity_left, disparity_right)
|