def extract_features_hahog(image, config):
t = time.time()
points, desc = csfm.hahog(
image.astype(np.float32) /
255, # VlFeat expects pixel values between 0, 1
peak_threshold=config.get('hahog_peak_threshold', 0.003),
edge_threshold=config.get('hahog_edge_threshold', 10))
print 'Found {0} points in {1}s'.format(len(points), time.time() - t)
if config.get('feature_root', False): desc = root_feature(desc)
return mask_and_normalize_features(points, desc, image.shape[1],
image.shape[0], config)
def extract_features_hahog(image, config):
t = time.time()
points, desc = csfm.hahog(image.astype(np.float32) / 255, # VlFeat expects pixel values between 0, 1
peak_threshold = config.get('hahog_peak_threshold', 0.003),
edge_threshold = config.get('hahog_edge_threshold', 10),
target_num_features = config.get('feature_min_frames', 0),
use_adaptive_suppression = config.get('feature_use_adaptive_suppression', False))
if config.get('feature_root', False):
desc = np.sqrt(desc)
uchar_scaling = 362 # x * 512 < 256 => sqrt(x) * 362 < 256
else:
uchar_scaling = 512
if config.get('hahog_normalize_to_uchar', False):
desc = (uchar_scaling * desc).clip(0, 255).round()
logger.debug('Found {0} points in {1}s'.format( len(points), time.time()-t ))
return points, desc
def extract_features_hahog(image, config):
t = time.time()
points, desc = csfm.hahog(image.astype(np.float32) / 255, # VlFeat expects pixel values between 0, 1
peak_threshold = config.get('hahog_peak_threshold', 0.003),
edge_threshold = config.get('hahog_edge_threshold', 10),
target_num_features = config.get('feature_min_frames', 0),
use_adaptive_suppression = config.get('feature_use_adaptive_suppression', False))
if config.get('feature_root', False):
desc = np.sqrt(desc)
uchar_scaling = 362 # x * 512 < 256 => sqrt(x) * 362 < 256
else:
uchar_scaling = 512
if config.get('hahog_normalize_to_uchar', False):
desc = (uchar_scaling * desc).clip(0, 255).round()
print 'Found {0} points in {1}s'.format( len(points), time.time()-t )
return points, desc
import cv2
import csfm
import numpy as np
image = cv2.imread("test.png", cv2.CV_LOAD_IMAGE_COLOR)
img = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
points, desc = csfm.hahog(img.astype(np.float32) / 255, 0, False, True)
imgFloat = img.astype(np.float32) / 255
for x in imgFloat[0, 0:10]:
print "{:10.4f}".format(x)
points, desc = csfm.hahog(img.astype(np.float32) / 255, 0.01, 10, 0, False, True)
cv.imshow("dst_rt", img)
cv.waitKey(0)
cv.destroyAllWindows()
