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Zero
File size: 5,215 Bytes
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import numpy as np
from PIL import Image
from os.path import splitext
from os.path import *
import re
import h5py
import cv2
cv2.setNumThreads(0)
cv2.ocl.setUseOpenCL(False)
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 data 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 readFlo5Flow(filename):
with h5py.File(filename, "r") as f:
if "flow" not in f.keys():
raise IOError(
f"File {filename} does not have a 'flow' key. Is this a valid flo5 file?"
)
return f["flow"][()]
def writeFlo5File(flow, filename):
with h5py.File(filename, "w") as f:
f.create_dataset("flow", data=flow, compression="gzip", compression_opts=5)
def readDsp5Disp(filename):
with h5py.File(filename, "r") as f:
if "disparity" not in f.keys():
raise IOError(
f"File {filename} does not have a 'disparity' key. Is this a valid dsp5 file?"
)
return f["disparity"][()]
def writeDsp5File(disp, filename):
with h5py.File(filename, "w") as f:
f.create_dataset("disparity", data=disp, compression="gzip", compression_opts=5)
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 np.stack([flow, np.zeros_like(flow)], axis=-1)
else:
return flow[:, :, :-1]
elif ext == ".flo5":
return readFlo5Flow(file_name)
elif ext == ".dsp5":
res = readDsp5Disp(file_name)
res2 = np.zeros((*res.shape, 2))
res2[:, :, 0] = res
return res2
return []
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