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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 readDispKITTI(filename):
disp = cv2.imread(filename, cv2.IMREAD_ANYDEPTH) / 256.0
valid = disp > 0.0
flow = np.stack([-disp, np.zeros_like(disp)], -1)
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 []
def read_vkitti2_flow(filename):
# In R, flow along x-axis normalized by image width and quantized to [0;2^16 – 1]
# In G, flow along x-axis normalized by image width and quantized to [0;2^16 – 1]
# B = 0 for invalid flow (e.g., sky pixels)
bgr = cv2.imread(filename, cv2.IMREAD_ANYCOLOR | cv2.IMREAD_ANYDEPTH)
h, w, _c = bgr.shape
assert bgr.dtype == np.uint16 and _c == 3
# b == invalid flow flag == 0 for sky or other invalid flow
invalid = bgr[:, :, 0] == 0
# g,r == flow_y,x normalized by height,width and scaled to [0;2**16 – 1]
out_flow = 2.0 / (2 ** 16 - 1.0) * bgr[:, :, 2:0:-1].astype('f4') - 1 # [H, W, 2]
out_flow[..., 0] *= (w - 1)
out_flow[..., 1] *= (h - 1)
out_flow[invalid] = 0.000001 # invalid as very small value to add supervison on the sky
valid = (np.logical_or(invalid, ~invalid)).astype(np.float32)
return out_flow, valid
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