"""
MIT License
Copyright (c) 2018 Zhaoyang Lv
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
"""
import ast
import configparser
import numpy as np
import re, os
from scipy.misc import imsave, imread
from PIL import Image, ImageDraw, ImageFont
# Check for endianness, based on Daniel Scharstein's optical flow code.
# Using little-endian architecture, these two should be equal.
TAG_FLOAT = 202021.25
TAG_CHAR = 'PIEH'.encode()
def create_directory(filename):
target_dir = os.path.dirname(filename)
if not os.path.isdir(target_dir):
os.makedirs(target_dir)
def load_file(filename='config', section='SYNTH_DATA'):
# returns dictionary with all params
# Import configuration
config = configparser.ConfigParser()
res = config.read(filename)
if len(res) == 0:
print("ERROR: couldn't load 'config' file. To fix, copy 'config.sample' to 'config' (and do not version this file)")
exit(1)
params = {}
options = config.options(section)
for option in options:
try:
params[option] = ast.literal_eval(config.get(section, option))
if params[option] == -1:
print("skip: %s" % option)
except:
print(" CONFIG PARSING EXCEPTION on %s" % option)
params[option] = None
raise
return params
def image_write(filename, image):
create_directory(filename)
imsave(filename, image)
def pngdepth_read(filename):
return imread(filename).astype(np.float32) / 1000.0
def pngdepth_write(filename, depth):
# this is specifically for writing depth in 16-bit png
from cv2 import imwrite as depth_write
create_directory(filename)
# we need to save it as uint16
depth_write(filename, (depth.copy() * 1e3).astype(np.uint16))
def readPFM(file):
""" read the file in pfm format
Original code from the Scene Flow Dataset (CVPR 2016), Freiburg
"""
file = open(file, 'rb')
color = None
width = None
height = None
scale = None
endian = None
header = file.readline().rstrip()
if header == 'PF':
color = True
elif header == 'Pf':
color = False
else:
raise Exception('Not a PFM file.')
dim_match = re.match(r'^(\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, scale
def writePFM(file, image, scale=1):
""" write the file in pfm format
Original code from the Scene Flow Dataset (CVPR 2016), Freiburg
"""
create_directory(file)
file = open(file, 'wb')
color = None
if image.dtype.name != 'float32':
raise Exception('Image dtype must be float32.')
image = np.flipud(image)
if len(image.shape) == 3 and image.shape[2] == 3: # color image
color = True
elif len(image.shape) == 2 or len(image.shape) == 3 and image.shape[2] == 1: # greyscale
color = False
else:
raise Exception('Image must have H x W x 3, H x W x 1 or H x W dimensions.')
file.write('PF\n' if color else 'Pf\n')
file.write('%d %d\n' % (image.shape[1], image.shape[0]))
endian = image.dtype.byteorder
if endian == '<' or endian == '=' and sys.byteorder == 'little':
scale = -scale
file.write('%f\n' % scale)
image.tofile(file)
def flow_visualize(flow, max_range = 1e3):
""" Original code from SINTEL toolbox, by Jonas Wulff.
"""
import matplotlib.colors as colors
du = flow[:, :, 0]
dv = flow[:, :, 1]
[h,w] = du.shape
max_flow = min(max_range, np.max(np.sqrt(du * du + dv * dv)))
img = np.ones((h, w, 3), dtype=np.float64)
# angle layer
img[:, :, 0] = (np.arctan2(dv, du) / (2 * np.pi) + 1) % 1.0
# magnitude layer, normalized to 1
img[:, :, 1] = np.sqrt(du * du + dv * dv) / (max_flow + 1e-8)
# phase layer
#img[:, :, 2] = valid
# convert to rgb
img = colors.hsv_to_rgb(img)
# remove invalid point
img[:, :, 0] = img[:, :, 0]
img[:, :, 1] = img[:, :, 1]
img[:, :, 2] = img[:, :, 2]
return img
def flow_read_from_flo(filename):
""" Read optical flow from file, return (U,V) tuple.
Original code by Deqing Sun, adapted from Daniel Scharstein.
"""
f = open(filename,'rb')
check = np.fromfile(f,dtype=np.float32,count=1)[0]
assert check == TAG_FLOAT, ' flow_read:: Wrong tag in flow file (should be: {0}, is: {1}). Big-endian machine? '.format(TAG_FLOAT,check)
width = np.fromfile(f,dtype=np.int32,count=1)[0]
height = np.fromfile(f,dtype=np.int32,count=1)[0]
size = width*height
assert width > 0 and height > 0 and size > 1 and size < 100000000, ' flow_read:: Wrong input size (width = {0}, height = {1}).'.format(width,height)
tmp = np.fromfile(f,dtype=np.float32,count=-1).reshape((height,width*2))
u = tmp[:,np.arange(width)*2]
v = tmp[:,np.arange(width)*2 + 1]
return u,v
def flow_write(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.
"""
create_directory(filename)
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()
