如何将.pfm文件可视化为图像？

Question

如何将.pfm文件可视化为图像？

imageimage-processingcomputer-visiondata-visualization

3

我有一个.pfm文件，它是一个(.PF/.pf)文件。我想可视化它，但我无法做到。通常.pfm文件包含格式的头信息。

PF/pf
宽度高度
比例=1

但我的文件具有以下头信息。因为无法将其作为图像进行可视化，所以请帮帮我。感谢任何帮助。

Typ=Pic98::TPlane
Lines=750
Columns=1125
FirstLine=0

FirstColumn=0

import re
import numpy as np
file = open("PF file.PF", 'rb')
header = file.readline().rstrip().decode('utf-8')
if header == 'PF':
   raise Exception('Only ONE channel image is supported.')
elif header == 'Typ=Pic98::TPlane<float>':
    color = False
else:
    raise Exception('Not a PFM file.')
dim_match = re.match(r'(^(\w+).(\d+)$)\n(^(\w+).(\d+)\s$)', 
file.readline().decode('ascii'))
if dim_match:
  width, height = map(int, dim_match.groups())
else:
  raise Exception('Malformed PFM header.')
if header == 'Typ=Pic98::TPlane<float>':
  scale =1
  endian = '>'
else:
  scale = -scale
  endian = '<'

npImage = np.reshape(npImage, width,height)
npImage = np.flipud(npImage)

if ret_PIL:
  img = Image.fromarray(npImage, 'F')
  return img
return npImage
file.close()

- Blueman7

我在Windows上制作了一个应用程序，链接为https://github.com/SiliconStudio/PfmViewer。 - v.oddou

2个回答

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- ccj5351 · Answer 1

我在Mac和Ubuntu上使用这个cvkit工具https://github.com/roboception/cvkit。它非常适用于可视化“.pfm”文件（例如，保存为pfm文件的视差或深度图）。

- Mark Setchell · Answer 2

更新的答案

我已经以稍微不同但更清晰的风格重新撰写了下面的答案。

#!/usr/bin/env python3

import re
import cv2
import numpy as np
from PIL import Image

def readPF(filename):
   """Read named PF file into Numpy array"""

   # Slurp entire file into memory as binary 'bytes'
   with open(filename, 'rb') as f:
      data = f.read()

   # Check correct header, return None if incorrect
   if not re.match(b'Typ=Pic98::TPlane<float>', data):
      return None
   
   # Get Lines and Columns, both must be present, else return None
   L = re.search(b'Lines=(\d+)',   data)
   C = re.search(b'Columns=(\d+)', data)
   if not (L and C):
      return None
   height = int(L.groups()[0])
   width  = int(C.groups()[0])
   print(f'DEBUG: Height={height}, width={width}')

   # Take the data from the END of the file in case other header lines added at start
   na = np.frombuffer(data[-4*height*width:], dtype=np.dtype('<f4')).reshape((height,width))

   # Some debug stuff
   min, max, mean = na.min(), na.max(), na.mean()
   print(f'DEBUG: min={min}, max={max}, mean={mean}')

   return na

################################################################################
# Main
################################################################################
na = readPF('PF file.PF')

################################################################################
# Use either of the following to save the image:
################################################################################
# Save with OpenCV as scaled PNG
u16 = (65535*(na - np.min(na))/np.ptp(na)).astype(np.uint16)  
cv2.imwrite('OpenCV.png', u16)

# Convert to PIL Image and save as TIFF
pi = Image.fromarray(na, mode='F')
pi.save('PIL.tif')

原始回答

不太确定我应该期望什么样的图像，但是这里有一个大概的想法：

#!/usr/bin/env python3

import re
import cv2
import numpy as np
from PIL import Image

file = open("PF file.PF", 'rb')
header = file.readline().rstrip().decode('utf-8')
if header == 'PF':
   raise Exception('Only ONE channel image is supported.')
elif header == 'Typ=Pic98::TPlane<float>':
    color = False
else:
    raise Exception('Not a PFM file.')

while True:
    line = file.readline().decode('ascii')
    match = re.match('(\w+)=(\d+)', line)
    n, v = match.groups()
    if n == 'Lines':
        height = int(v)
        print(f'Height: {height}')
    if n == 'Columns':
        width = int(v)
        print(f'Width: {width}')
        break

# Seek backwards from the end of the file in case any clown has added something to the header
file.seek(-height*width*4,2)

# Read remainder of file into Numpy array of floats and reshape
na = np.fromfile(file, dtype=np.float32).reshape((height,width))

# Some debug stuff
min, max, mean = na.min(), na.max(), na.mean()
print(f'DEBUG: min={min}, max={max}, mean={mean}')

################################################################################
# Use either of the following to save the image:
################################################################################
# Save with OpenCV as scaled PNG
u16 = (65535*(na - np.min(na))/np.ptp(na)).astype(np.uint16)  
cv2.imwrite('OpenCV.png', u16)

# Convert to PIL Image and save as TIFF
pi = Image.fromarray(na, mode='F')
pi.save('PIL.tif')

输出结果如下：

Height: 750
Width: 1125
DEBUG: min=0.0, max=127881704.0, mean=1618343.625

另一种可能性是使用ImageMagick将其转换为PNG格式，我得到了以下结果，ImageMagick默认为小端序，因此如果这是正确的话，您的图像就是小端序的。

magick -define quantum:format=floating-point -depth 32 -size 1125x750+80 gray:"PF file.pf"  -auto-level image.png

关键词: Python, ImageMagick, 图像处理, 浮点数, float32, Numpy, PFM