Spaces:
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on
A10G
Running
on
A10G
import numpy as np | |
from PIL import Image | |
from os.path import * | |
import re | |
import cv2 | |
TAG_CHAR = np.array([202021.25], np.float32) | |
def readFlow(fn): | |
""" Read .flo file in Middlebury format""" | |
# Code adapted from: | |
# http://stackoverflow.com/questions/28013200/reading-middlebury-flow-files-with-python-bytes-array-numpy | |
# WARNING: this will work on little-endian architectures (eg Intel x86) only! | |
# print 'fn = %s'%(fn) | |
with open(fn, 'rb') as f: | |
magic = np.fromfile(f, np.float32, count=1) | |
if 202021.25 != magic: | |
print('Magic number incorrect. Invalid .flo file') | |
return None | |
else: | |
w = np.fromfile(f, np.int32, count=1) | |
h = np.fromfile(f, np.int32, count=1) | |
# print 'Reading %d x %d flo file\n' % (w, h) | |
data = np.fromfile(f, np.float32, count=2 * int(w) * int(h)) | |
# Reshape testdata into 3D array (columns, rows, bands) | |
# The reshape here is for visualization, the original code is (w,h,2) | |
return np.resize(data, (int(h), int(w), 2)) | |
def readPFM(file): | |
file = open(file, 'rb') | |
color = None | |
width = None | |
height = None | |
scale = None | |
endian = None | |
header = file.readline().rstrip() | |
if header == b'PF': | |
color = True | |
elif header == b'Pf': | |
color = False | |
else: | |
raise Exception('Not a PFM file.') | |
dim_match = re.match(rb'^(\d+)\s(\d+)\s$', file.readline()) | |
if dim_match: | |
width, height = map(int, dim_match.groups()) | |
else: | |
raise Exception('Malformed PFM header.') | |
scale = float(file.readline().rstrip()) | |
if scale < 0: # little-endian | |
endian = '<' | |
scale = -scale | |
else: | |
endian = '>' # big-endian | |
data = np.fromfile(file, endian + 'f') | |
shape = (height, width, 3) if color else (height, width) | |
data = np.reshape(data, shape) | |
data = np.flipud(data) | |
return data | |
def writeFlow(filename, uv, v=None): | |
""" Write optical flow to file. | |
If v is None, uv is assumed to contain both u and v channels, | |
stacked in depth. | |
Original code by Deqing Sun, adapted from Daniel Scharstein. | |
""" | |
nBands = 2 | |
if v is None: | |
assert (uv.ndim == 3) | |
assert (uv.shape[2] == 2) | |
u = uv[:, :, 0] | |
v = uv[:, :, 1] | |
else: | |
u = uv | |
assert (u.shape == v.shape) | |
height, width = u.shape | |
f = open(filename, 'wb') | |
# write the header | |
f.write(TAG_CHAR) | |
np.array(width).astype(np.int32).tofile(f) | |
np.array(height).astype(np.int32).tofile(f) | |
# arrange into matrix form | |
tmp = np.zeros((height, width * nBands)) | |
tmp[:, np.arange(width) * 2] = u | |
tmp[:, np.arange(width) * 2 + 1] = v | |
tmp.astype(np.float32).tofile(f) | |
f.close() | |
def readFlowKITTI(filename): | |
flow = cv2.imread(filename, cv2.IMREAD_ANYDEPTH | cv2.IMREAD_COLOR) | |
flow = flow[:, :, ::-1].astype(np.float32) | |
flow, valid = flow[:, :, :2], flow[:, :, 2] | |
flow = (flow - 2 ** 15) / 64.0 | |
return flow, valid | |
def writeFlowKITTI(filename, uv): | |
uv = 64.0 * uv + 2 ** 15 | |
valid = np.ones([uv.shape[0], uv.shape[1], 1]) | |
uv = np.concatenate([uv, valid], axis=-1).astype(np.uint16) | |
cv2.imwrite(filename, uv[..., ::-1]) | |
def read_gen(file_name, pil=False): | |
ext = splitext(file_name)[-1] | |
if ext == '.png' or ext == '.jpeg' or ext == '.ppm' or ext == '.jpg': | |
return Image.open(file_name) | |
elif ext == '.bin' or ext == '.raw': | |
return np.load(file_name) | |
elif ext == '.flo': | |
return readFlow(file_name).astype(np.float32) | |
elif ext == '.pfm': | |
flow = readPFM(file_name).astype(np.float32) | |
if len(flow.shape) == 2: | |
return flow | |
else: | |
return flow[:, :, :-1] | |
return [] | |