def match(im):
atlas = feature.im_read('scripts_testing/plate-34.jpg')
if affine:
kp, des = feature.extract_sift(im)
kp2, des2 = feature.extract_sift(atlas)
else:
kp, des = sift.detectAndCompute(im, None)
kp2, des2 = sift.detectAndCompute(atlas, None)
match = feature.match(im, kp, des, atlas, kp2, des2)
print("Matches: ", len(match.matches))
print("Inliers: ", match.inlier_count)
plt.figure(figsize=(10,10))
plt.imshow(match.result)
plt.figure(figsize=(10,10))
plt.imshow(match.result2)
return match.H
filledLength = int(length * iteration // total)
bar = fill * filledLength + '-' * (length - filledLength)
print('\r%s |%s| %s%% %s' % (prefix, bar, percent, suffix), end='\r')
# Print New Line on Complete
if iteration == total:
print()
filename = 'atlas_swanson_regions/Level-34-Region.jpg'
output_filename = 'results/Level-34-range2'
points = 30
disp_range = range(30, 50)
nissl_range = range(1, config.NISSL_COUNT + 1)
print("***** Beginning batch processing")
im = feature.im_read(filename)
csv_filename = output_filename + "-" + str(points) + "pts.csv"
with open(csv_filename, 'w') as csvfile:
fieldnames = ['warp_points', 'warp_disp', 'plate', 'matches', 'inliers']
writer = csv.DictWriter(csvfile,
fieldnames=fieldnames,
delimiter=',',
lineterminator='\n')
writer.writeheader()
for disp in disp_range:
printProgressBar(int(disp / disp[0]), len(disp_range), prefix='Disp: ')
# Warp image
im_warp = feature.warp(im, points, None, None, disp, None)
def cv2_ransac(src_pts, dst_pts):
import cv2
H, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC,
config.RANSAC_REPROJ_TRESHHOLD, None,
config.RANSAC_MAX_ITERS,
config.RANSAC_CONFIDENCE)
return {
"homography": H,
"inlier_mask": mask,
"inlier_count": mask.ravel().sum(),
"original_inlier_mask": None,
"total_error": -1,
"min_error": -1,
"max_error": -1,
'metric': mask.ravel().sum()
}
import sys
logbook.StreamHandler(
sys.stdout, level=logbook.DEBUG,
format_string=config.LOGGER_FORMAT_STRING).push_application()
if __name__ == '__main__':
import feature
im_region = feature.im_read(
'C:/Users/xeroj/Desktop/Local_Programming/Vision-Rat-Brain/scripts_testing/region.jpg'
)
feature.match_region_nissl(im_region, nissl_level=34)
else:
kp, des = sift.detectAndCompute(im, None)
kp2, des2 = sift.detectAndCompute(atlas, None)
match = feature.match(im, kp, des, atlas, kp2, des2)
print("Matches: ", len(match.matches))
print("Inliers: ", match.inlier_count)
plt.figure(figsize=(10,10))
plt.imshow(match.result)
plt.figure(figsize=(10,10))
plt.imshow(match.result2)
return match.H
filename = 'scripts_testing/region-70-HQ.jpg'
im_region = feature.im_read(filename)
im_region_gray = feature.im_read(filename, flags=cv2.IMREAD_GRAYSCALE)
# *************** Resizing
#im_region = misc.imresize(im_region, (170, 310))
im_region = misc.imresize(im_region, 10)
# *************** Convolution
#n = 6
#kernel = np.ones((n,n),np.float32)/(n**2)
#dst = cv2.filter2D(im_region,-1,kernel)
affine = True
draw_kp(feature.im_read('scripts_testing/region-34.jpg'))
draw_kp(im_region)
def refresh_image(self):
im = feature.im_read(self.nissl_filename)
self.canvas_input.imshow(im)