def find_BIH (self, empty_board_frame): """ PRIVATE: find_BIH ----------------- given a frame containing the empty board, this function finds the homography relating board coordinates to image coordinates. (sets self.BIH) """ assert self.corner_classifier self.BIH = CVAnalysis.find_board_image_homography (empty_board_frame, self.corner_classifier)
def find_BIH(self, empty_board_frame):
"""
PRIVATE: find_BIH
-----------------
given a frame containing the empty board, this function
finds the homography relating board coordinates to
image coordinates. (sets self.BIH)
"""
assert self.corner_classifier
self.BIH = CVAnalysis.find_board_image_homography(
empty_board_frame, self.corner_classifier)
import pickle
import numpy as np
import cv2
import CVAnalysis
if __name__ == "__main__":
#=====[ Step 1: switch to directory ]=====
os.chdir ('../data/toy_images')
filenames = [
'random1.jpg',
'random2.jpg',
'random3.jpg',
'random4.jpg',
'random5.jpg',
'random6.jpg',
'random7.jpg',
]
images = [cv2.imread (f) for f in filenames]
sift_desc = []
for image in images:
hc = CVAnalysis.get_harris_corners (image)
desc = CVAnalysis.get_sift_descriptors (image, hc)
sift_desc.append (desc)
features = np.concatenate (sift_desc, 0)
points_grid[line_index].append(corner)
#=====[ Step 3: sort each one by y coordinate ]=====
for i in range(len(points_grid)):
points_grid[i].sort(key=lambda x: x[0])
return points_grid
if __name__ == '__main__':
#=====[ Step 1: read in image ]=====
image = cv2.imread('../data/p2/1.jpg')
#=====[ Step 2: get harris corners ]=====
hc = CVAnalysis.get_harris_corners(image)
#=====[ Step 3: classify them ]=====
sd = CVAnalysis.get_sift_descriptors(image, hc)
clf = pickle.load(open('../data/classifiers/corner_classifier.clf', 'r'))
predictions = clf.predict(sd)
idx = (predictions == 1)
corners = [c for c, i in zip(hc, idx) if i]
corners = avg_close_points(corners)
#=====[ Step 3: get black image, fill in corners ]=====
corners_img = np.zeros(image.shape[:2], dtype=np.uint8)
for corner in corners:
corners_img[int(corner[1])][int(corner[0])] = 255
#=====[ Step 4: apply hough transform to get lines ]=====
#==========[ Step 1: sanitize input ]==========
if not len(sys.argv) == 2:
filename = '../data/micahboard/1.jpg'
else:
filename = sys.argv[1]
image_name = os.path.split(filename)[1]
if not os.path.isfile(filename):
raise StandardError("Couldn't find the file you passed in: " +
image_name)
#==========[ Step 2: get/convert image ]==========
image = cv2.imread(filename)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
#==========[ Step 3: get corners ]==========
harris_corners = CVAnalysis.get_harris_corners(image)
disp_image = cv2.drawKeypoints(image, harris_corners, color=(0, 0, 255))
#==========[ Step 4: draw image ]==========
cv2.namedWindow('DISPLAY')
cv.SetMouseCallback('DISPLAY', on_mouse, param=harris_corners)
#==========[ Step 4: have user mark keypoints ]==========
while True:
disp_image = cv2.drawKeypoints(image,
harris_corners,
color=(0, 0, 255))
disp_image = cv2.drawKeypoints(disp_image,
corner_keypoints,
color=(255, 0, 0))
if not len(sys.argv) == 2:
filename = '../data/micahboard/1.jpg'
else:
filename = sys.argv[1]
image_name = os.path.split (filename)[1]
if not os.path.isfile (filename):
raise StandardError ("Couldn't find the file you passed in: " + image_name)
#==========[ Step 2: get/convert image ]==========
image = cv2.imread(filename)
gray = cv2.cvtColor (image, cv2.COLOR_BGR2GRAY)
#==========[ Step 3: get corners ]==========
harris_corners = CVAnalysis.get_harris_corners (image)
disp_image = cv2.drawKeypoints (image, harris_corners, color=(0, 0, 255))
#==========[ Step 4: draw image ]==========
cv2.namedWindow ('DISPLAY')
cv.SetMouseCallback ('DISPLAY', on_mouse, param=harris_corners)
#==========[ Step 4: have user mark keypoints ]==========
while True:
disp_image = cv2.drawKeypoints (image, harris_corners, color=(0, 0, 255))
disp_image = cv2.drawKeypoints (disp_image, corner_keypoints, color=(255, 0, 0))
cv2.imshow ('DISPLAY', disp_image)
