import os
from scipy import misc
path = 'your_file_path'
image= misc.imread(os.path.join(path,'image.bmp'), flatten= 0)
## flatten=0 if image is required as it is
## flatten=1 to flatten the color layers into a single gray-scale layer
def read_rows(path):
image_file = open(path, "rb")
# Blindly skip the BMP header.
image_file.seek(54)
# We need to read pixels in as rows to later swap the order
# since BMP stores pixels starting at the bottom left.
rows = []
row = []
pixel_index = 0
while True:
if pixel_index == 1920:
pixel_index = 0
rows.insert(0, row)
if len(row) != 1920 * 3:
raise Exception("Row length is not 1920*3 but " + str(len(row)) + " / 3.0 = " + str(len(row) / 3.0))
row = []
pixel_index += 1
r_string = image_file.read(1)
g_string = image_file.read(1)
b_string = image_file.read(1)
if len(r_string) == 0:
# This is expected to happen when we've read everything.
if len(rows) != 1080:
print "Warning!!! Read to the end of the file at the correct sub-pixel (red) but we've not read 1080 rows!"
break
if len(g_string) == 0:
print "Warning!!! Got 0 length string for green. Breaking."
break
if len(b_string) == 0:
print "Warning!!! Got 0 length string for blue. Breaking."
break
r = ord(r_string)
g = ord(g_string)
b = ord(b_string)
row.append(b)
row.append(g)
row.append(r)
image_file.close()
return rows
def repack_sub_pixels(rows):
print "Repacking pixels..."
sub_pixels = []
for row in rows:
for sub_pixel in row:
sub_pixels.append(sub_pixel)
diff = len(sub_pixels) - 1920 * 1080 * 3
print "Packed", len(sub_pixels), "sub-pixels."
if diff != 0:
print "Error! Number of sub-pixels packed does not match 1920*1080: (" + str(len(sub_pixels)) + " - 1920 * 1080 * 3 = " + str(diff) +")."
return sub_pixels
rows = read_rows("my image.bmp")
# This list is raw sub-pixel values. A red image is for example (255, 0, 0, 255, 0, 0, ...).
sub_pixels = repack_sub_pixels(rows)
def load_Philips30XL_BMP(fname):
"""
Experimental loading of BMPs from Philips30XL microscopes (they have an atypical format which cannot be loaded by imageio)
See https://ide.kaitai.io/ for more information on BMP header.
"""
with open(fname, mode='rb') as file: # first analyze the header
fileContent = file.read()
ofs, w, h, bpp, compr = [int.from_bytes(fileContent[s:e], byteorder='little', signed=False) for s,e in
((0x0a,0x0e),(0x12,0x16),(0x16,0x1a),(0x1c,0x1e),(0x1e,0x22))]
assert bpp == 8, f'monochrome/LUT image assumed (8 bit per pixel); {fname} has {bpp}bpp'
assert compr == 0, 'no decompression algorithm implemented'
return np.fromfile(fname, dtype=np.uint8)[ofs:ofs+w*h].reshape(h,w)[::-1,:] # BMP is "upside down" - flip vertically
9条答案
按热度按时间wi3ka0sx1#
在Python中,它可以简单地读作:
8yparm6h2#
我知道这是一个老问题,但我发现它时,解决这个问题,我自己和我认为,这可能会帮助别人在未来。
实际上,将BMP文件作为二进制数据读取非常容易。当然,这取决于您需要支持的支持范围有多广以及有多少个角落案例。
下面是一个简单的解析器,只适用于1920x1080 24位BMP(如从MS Paint保存的)。但它应该很容易扩展。它将像素值吐出为python列表,例如红色图像的
(255, 0, 0, 255, 0, 0, ...)
。如果你需要更强大的支持,这里有关于如何正确阅读这个问题的答案的信息:How to read bmp file header in python?。使用这些信息,您应该能够扩展下面的简单解析器,使其具有您需要的任何特性。
如果你需要的话,在wikipedia https://en.wikipedia.org/wiki/BMP_file_format上还有更多关于BMP文件格式的信息。
eeq64g8w3#
用枕头做这个。安装后,只需导入
然后你可以加载BMP文件
如果需要图像是numpy数组,请使用
np.array
numpy数组将仅为1D。使用
reshape()
将其变成正确的形状,以防您的图像是RGB。举例来说:fjaof16o4#
使用优秀的matplotlib库
kupeojn65#
我不得不在一个项目上工作,我需要使用Python读取BMP文件,这很有趣,实际上最好的方法是对BMP文件格式(https://en.wikipedia.org/wiki/BMP_file_format)进行审查,然后阅读它作为二进制文件,以提取数据。
您将需要使用structpython库来执行提取
您可以使用本教程来了解它如何进行https://youtu.be/0Kwqdkhgbfw
u59ebvdq6#
这取决于你想实现什么,在哪个平台上?
无论如何,使用C库加载BMP可能会工作,例如。http://code.google.com/p/libbmp/或http://freeimage.sourceforge.net/,C库可以很容易地从python调用,例如。使用ctypes或将其 Package 为python模块。
或者您可以编译此版本的PIL https://github.com/sloonz/pil-py3k
798qvoo87#
如果你在Windows中这样做,这个网站应该允许你在大多数版本的Python中启动和运行PIL(和许多其他流行的包):Unofficial Windows Binaries for Python Extension Packages
42fyovps8#
PIL到Python 3.x的公共端口称为“Pillow”。我也建议Pygame库用于简单的任务。它是一个库,充满了创建游戏的功能-和阅读从一些常见的图像格式是其中之一。Python 3.x也是如此。
xam8gpfp9#
前一段时间,我需要从一个旧的科学软件中读取BMP,它在一些程序中工作,但Python的PIL拒绝打开它。
BMP是一种相当简单的格式,很容易被numpy解析;您可能希望修改以下几行。