我正在使用 ctypes 访问来自 National Instruments (NI-IMAQ) 的图像采集 API。其中，有一个名为 imgBayerColorDecode() 的函数，我在从 imgSnap() 函数返回的拜耳编码图像上使用它。我想将解码后的输出(即 RGB 图像)与我将根据原始数据创建的一些 numpy ndarray 进行比较，这是 imgSnap 返回的内容。
但是，有2个问题。
第一个很简单:将 imgSnap 返回的 imgbuffer 传递到一个 numpy 数组中。现在首先有一个问题:如果你的机器是 64 位的并且你有超过 3GB 的内存，你不能用 numpy 创建数组并将它作为指针传递给 imgSnap。这就是为什么你必须实现一个解决方法，这在 NI 的论坛 (NI ref - first 2 posts) 上有描述:禁用错误消息(下面附加代码中的第 125 行:imaq.niimaquDisable32bitPhysMemLimitEnforcement)并确保它是 IMAQ 库创建图像所需的内存( imaq.imgCreateBuffer )。之后，this recipe on SO 应该能够再次将缓冲区转换为 numpy 数组。但我不确定我是否对数据类型进行了正确的更改:相机有 1020x1368 像素，每个像素强度以 10 位精度记录。它通过 CameraLink 返回图像，我假设它以每像素 2 个字节的方式返回图像，以便于数据传输。这是否意味着我必须调整另一个 SO 问题中给出的配方:
buffer = numpy.core.multiarray.int_asbuffer(ctypes.addressof(y.contents), 8*array_length)
a = numpy.frombuffer(buffer, float)
对此:
bufsize = 1020*1368*2
buffer = numpy.core.multiarray.int_asbuffer(ctypes.addressof(y.contents), bufsize)
a = numpy.frombuffer(buffer, numpy.int16)
第二个问题是 imgBayerColorDecode() 没有给我我期待的输出。
下面是两张图片，第一张是 imgSnap 的输出，用
imgSessionSaveBufferEx() 保存。第二个是imgSnap经过imgBayerColorDecode()去马赛克后的输出。如您所见，拜耳解码后的图像仍然是灰度图像，而且它与原始图像不同(这里有一点要注意，图像已缩放以使用 imagemagick 上传)。原始图像是在一些面具前用红色滤色镜拍摄的。从它(和其他 2 个滤色器)，我知道拜耳滤色器在左上角看起来像这样:
BGBG
GRGR
我相信我在将正确类型的指针传递给 imgBayerDecode 时做错了，我的代码附加在下面。
#!/usr/bin/env python
from __future__ import division
import ctypes as C
import ctypes.util as Cutil
import time
# useful references:
# location of the niimaq.h: C:\Program Files (x86)\National Instruments\NI-IMAQ\Include
# location of the camera files: C:\Users\Public\Documents\National Instruments\NI-IMAQ\Data
# check it C:\Users\Public\Documents\National Instruments\NI-IMAQ\Examples\MSVC\Color\BayerDecode
class IMAQError(Exception):
"""A class for errors produced during the calling of National Intrument's IMAQ functions.
It will also produce the textual error message that corresponds to a specific code."""
def __init__(self, code):
self.code = code
text = C.c_char_p('')
imaq.imgShowError(code, text)
self.message = "{}: {}".format(self.code, text.value)
# Call the base class constructor with the parameters it needs
Exception.__init__(self, self.message)
def imaq_error_handler(code):
"""Print the textual error message that is associated with the error code."""
if code < 0:
raise IMAQError(code)
free_associated_resources = 1
imaq.imgSessionStopAcquisition(sid)
imaq.imgClose(sid, free_associated_resources)
imaq.imgClose(iid, free_associated_resources)
else:
return code
if __name__ == '__main__':
imaqlib_path = Cutil.find_library('imaq')
imaq = C.windll.LoadLibrary(imaqlib_path)
imaq_function_list = [ # this is not an exhaustive list, merely the ones used in this program
imaq.imgGetAttribute,
imaq.imgInterfaceOpen,
imaq.imgSessionOpen,
imaq.niimaquDisable32bitPhysMemLimitEnforcement, # because we're running on a 64-bit machine with over 3GB of RAM
imaq.imgCreateBufList,
imaq.imgCreateBuffer,
imaq.imgSetBufferElement,
imaq.imgSnap,
imaq.imgSessionSaveBufferEx,
imaq.imgSessionStopAcquisition,
imaq.imgClose,
imaq.imgCalculateBayerColorLUT,
imaq.imgBayerColorDecode ]
# for all imaq functions we're going to call, we should specify that if they
# produce an error (a number), we want to see the error message (textually)
for func in imaq_function_list:
func.restype = imaq_error_handler
INTERFACE_ID = C.c_uint32
SESSION_ID = C.c_uint32
BUFLIST_ID = C.c_uint32
iid = INTERFACE_ID(0)
sid = SESSION_ID(0)
bid = BUFLIST_ID(0)
array_16bit = 2**16 * C.c_uint32
redLUT, greenLUT, blueLUT = [ array_16bit() for _ in range(3) ]
red_gain, blue_gain, green_gain = [ C.c_double(val) for val in (1., 1., 1.) ]
# OPEN A COMMUNICATION CHANNEL WITH THE CAMERA
# our camera has been given its proper name in Measurement & Automation Explorer (MAX)
lcp_cam = 'JAI CV-M7+CL'
imaq.imgInterfaceOpen(lcp_cam, C.byref(iid))
imaq.imgSessionOpen(iid, C.byref(sid));
# START C MACROS DEFINITIONS
# define some C preprocessor macros (these are all defined in the niimaq.h file)
_IMG_BASE = 0x3FF60000
IMG_BUFF_ADDRESS = _IMG_BASE + 0x007E # void *
IMG_BUFF_COMMAND = _IMG_BASE + 0x007F # uInt32
IMG_BUFF_SIZE = _IMG_BASE + 0x0082 #uInt32
IMG_CMD_STOP = 0x08 # single shot acquisition
IMG_ATTR_ROI_WIDTH = _IMG_BASE + 0x01A6
IMG_ATTR_ROI_HEIGHT = _IMG_BASE + 0x01A7
IMG_ATTR_BYTESPERPIXEL = _IMG_BASE + 0x0067
IMG_ATTR_COLOR = _IMG_BASE + 0x0003 # true = supports color
IMG_ATTR_PIXDEPTH = _IMG_BASE + 0x0002 # pix depth in bits
IMG_ATTR_BITSPERPIXEL = _IMG_BASE + 0x0066 # aka the bit depth
IMG_BAYER_PATTERN_GBGB_RGRG = 0
IMG_BAYER_PATTERN_GRGR_BGBG = 1
IMG_BAYER_PATTERN_BGBG_GRGR = 2
IMG_BAYER_PATTERN_RGRG_GBGB = 3
# END C MACROS DEFINITIONS
width, height = C.c_uint32(), C.c_uint32()
has_color, pixdepth, bitsperpixel, bytes_per_pixel = [ C.c_uint8() for _ in range(4) ]
# poll the camera (or is it the camera file (icd)?) for these attributes and store them in the variables
for var, macro in [ (width, IMG_ATTR_ROI_WIDTH),
(height, IMG_ATTR_ROI_HEIGHT),
(bytes_per_pixel, IMG_ATTR_BYTESPERPIXEL),
(pixdepth, IMG_ATTR_PIXDEPTH),
(has_color, IMG_ATTR_COLOR),
(bitsperpixel, IMG_ATTR_BITSPERPIXEL) ]:
imaq.imgGetAttribute(sid, macro, C.byref(var))
print("Image ROI size: {} x {}".format(width.value, height.value))
print("Pixel depth: {}\nBits per pixel: {} -> {} bytes per pixel".format(
pixdepth.value,
bitsperpixel.value,
bytes_per_pixel.value))
bufsize = width.value*height.value*bytes_per_pixel.value
imaq.niimaquDisable32bitPhysMemLimitEnforcement(sid)
# create the buffer (in a list)
imaq.imgCreateBufList(1, C.byref(bid)) # Creates a buffer list with one buffer
# CONFIGURE THE PROPERTIES OF THE BUFFER
imgbuffer = C.POINTER(C.c_uint16)() # create a null pointer
RGBbuffer = C.POINTER(C.c_uint32)() # placeholder for the Bayer decoded imgbuffer (i.e. demosaiced imgbuffer)
imaq.imgCreateBuffer(sid, 0, bufsize, C.byref(imgbuffer)) # allocate memory (the buffer) on the host machine (param2==0)
imaq.imgCreateBuffer(sid, 0, width.value*height.value * 4, C.byref(RGBbuffer))
imaq.imgSetBufferElement(bid, 0, IMG_BUFF_ADDRESS, C.cast(imgbuffer, C.POINTER(C.c_uint32))) # my guess is that the cast to an uint32 is necessary to prevent 64-bit callable memory addresses
imaq.imgSetBufferElement(bid, 0, IMG_BUFF_SIZE, bufsize)
imaq.imgSetBufferElement(bid, 0, IMG_BUFF_COMMAND, IMG_CMD_STOP)
# CALCULATE THE LOOKUP TABLES TO CONVERT THE BAYER ENCODED IMAGE TO RGB (=DEMOSAICING)
imaq.imgCalculateBayerColorLUT(red_gain, green_gain, blue_gain, redLUT, greenLUT, blueLUT, bitsperpixel)
# CAPTURE THE RAW DATA
imgbuffer_vpp = C.cast(C.byref(imgbuffer), C.POINTER(C.c_void_p))
imaq.imgSnap(sid, imgbuffer_vpp)
#imaq.imgSnap(sid, imgbuffer) # <- doesn't work (img produced is entirely black). The above 2 lines are required
imaq.imgSessionSaveBufferEx(sid, imgbuffer,"bayer_mosaic.png")
print('1 taken')
imaq.imgBayerColorDecode(RGBbuffer, imgbuffer, height, width, width, width, redLUT, greenLUT, blueLUT, IMG_BAYER_PATTERN_BGBG_GRGR, bitsperpixel, 0)
imaq.imgSessionSaveBufferEx(sid,RGBbuffer,"snapshot_decoded.png");
free_associated_resources = 1
imaq.imgSessionStopAcquisition(sid)
imaq.imgClose(sid, free_associated_resources )
imaq.imgClose(iid, free_associated_resources )
print "Finished"
后续:在与 NI representative 讨论后，我确信第二个问题是由于 imgBayerColorDecode 在 2012 年发布之前被限制为 8 位输入图像(我们正在 2010 年工作)。但是，我想确认这一点:如果我将 10 位图像转换为 8 位图像，仅保留最重要的字节，并将此转换版本传递给 imgBayerColorDecode，我希望看到 RGB 图像。
为此，我将 imgbuffer 转换为 numpy 数组并将 10 位数据移动 2 位:
np_buffer = np.core.multiarray.int_asbuffer(
ctypes.addressof(imgbuffer.contents), bufsize)
flat_data = np.frombuffer(np_buffer, np.uint16)
# from 10 bit to 8 bit, keeping only the non-empty bytes
Z = (flat_data>>2).view(dtype='uint8')[::2]
Z2 = Z.copy() # just in case
现在我将 ndarray Z2 传递给 imgBayerColorDecode:
bitsperpixel = 8
imaq.imgBayerColorDecode(RGBbuffer, Z2.ctypes.data_as(
ctypes.POINTER(ctypes.c_uint8)), height, width,
width, width, redLUT, greenLUT, blueLUT,
IMG_BAYER_PATTERN_BGBG_GRGR, bitsperpixel, 0)
请注意，原始代码(如上所示)已略有改动，例如 redLUt、greenLUT 和 blueLUT 现在只有 256 个元素数组。
最后我调用
imaq.imgSessionSaveBufferEx(sid,RGBbuffer, save_path) 。但它仍然是灰度并且没有保留 img 形状，所以我仍然在做一些非常错误的事情。有任何想法吗？ 最佳答案
经过一番尝试后，结果证明提到的 RGBbuffer 必须保存正确的数据，但 imgSessionSaveBufferEx 在这一点上做了一些奇怪的事情。
当我将数据从 RGBbuffer 传递回 numpy 时，将此一维数组重塑为图像的维度，然后通过屏蔽和使用位移操作(例如 red_channel = (np_RGB & 0XFF000000)>>16 )将其拆分为颜色 channel ，然后我可以将其保存为漂亮的彩色图像使用 PIL 或 pypng 的 png 格式。
我还没有发现为什么 imgSessionSaveBufferEx 的行为很奇怪，但上面的解决方案有效(即使速度方面它确实效率低下)。
关于python - 将哪种类型的 ctype 指针传递给 NI IMAQ 的 imgBayerColorDecode？，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/17095359/