def save(pyramid, keys, root):
sizes, octave = pyramid[0]
octave = filters.norm(octave, 5, 5, 0, 255)
key_levels = binby(keys, lambda x: int(x.octave))
for l, level in enumerate(octave):
drawn = level
if l in key_levels:
drawn = keypoints.draw(level, key_levels[l])
save(drawn, pyfs.join(root, "%f.png" % sizes[l]), norm=False)
def mesa(image, start=2.0, stop=None, levels=10, ring=1.05, psize=1, edge_threshold=2, threshold=1.0):
stop = stop or min(image.shape) / 4
print("mesa finding image particles:")
print(" image dimensions:", image.shape)
print(" from %f to %f" % (start, stop))
print(" over %d levels" % (levels))
print(" peak neighbor size: %d" % (psize))
image = filters.norm(image, 5, 5, 0.0, 1.0)
pyramid = mkpyramid(image, start, stop, levels, ring)
features = find_features(pyramid, threshold, edge_threshold, psize)
return features
def load(path, norm=False, supress=False):
with open(path, "rb") as fd:
header = readHeader(fd)
fd.seek(int(header["LABBYT"]))
rows = int(header["NX"])
cols = int(header["NY"])
if int(header["NZ"]) != 1:
raise ValueError("spider volumes not supported")
if int(header["ISTACK"]) != 0:
raise ValueError("spider stacks not supported")
data = np.fromfile(fd, dtype="f4")
if data.size != rows * cols:
raise ValueError("spider image has bad/incomplete data")
if supress:
data = filters.supress(data, *supress)
if norm:
data = filters.norm(data, *norm)
return data.reshape([cols, rows])
def load(path, supress=False, norm=False):
endian = '<'
with open(path, "rb") as fd:
header = np.fromfile(fd, dtype=MRCHeader, count=1)[0]
header = header.newbyteorder(endian)
# memory map using copy on write mode
# with offset starting after the header
# and reverse dimensions from header
if header["mode"] not in MRCModes:
endian = '>'
header = header.newbyteorder(endian)
data = np.memmap(fd,
mode="c",
offset=MRCHeader.itemsize + header['extended_header'],
dtype=MRCModes[header["mode"]],
shape=tuple(header["dims"][::-1]))
data = data.newbyteorder(endian)
if supress:
data = filters.supress(data, *supress)
if norm:
data = filters.norm(data, *norm)
return data
def save(image, path, norm=(0.01, 0.01, 0, 255)):
if norm:
image = filters.norm(image, *norm)
with pyfs.shadow(path):
cv2.imwrite(path, image.astype('uint8'))
return path
def save(image, keys, root):
image = filters.norm(image, 5, 5, 0, 255)
key_sizes = binby(keys, lambda x: int(x.size))
for size in key_sizes:
drawn = keypoints.draw(image, key_sizes[size])
save(drawn, pyfs.join(root, "%f.png"%size))
def save_octave(radii, octave, root):
levels = filters.norm(octave, 1, 1, 0, 255)
for size, level in zip(radii, levels):
save(level, pyfs.join(root, "%2.2f.png"%(size)), norm=False)