def process(raw_msg, model, out, flags):
'''
Given an original image message (sensor_msgs/Image), fill in the out ImageSet with the
processed (debayered, rectified, grayscaled) images (in numpy format) based on the flags.
@param raw_msg: sensor_msgs/Image original image message to process
@param model: image_geometry.PinholeCameraModel object used to rectify images if RECT or RECT_COLOR flag is set.
Can just pass in None if you aren't using RECT or RECT_COLOR
@param out: an ImageSet object. The requested images will be set in out based on the flags bitmask
@param flags: an integer bitmask inticating which processed images you want in out.
ex: process(msg, model, out, ImageProc.RECT_COLOR | ImageProc.RECT)
will fill the raw, rect_color, and rect images in out.
'''
# always set raw
out.raw = ImageProc.bridge.imgmsg_to_cv2(raw_msg)
if not bool(flags & ImageProc.ALL):
return
mono = ImageProc.MONO | ImageProc.RECT
color = ImageProc.COLOR | ImageProc.RECT_COLOR
# Check that camera model is set if we are rectifying an image
rect = bool(ImageProc.RECT | ImageProc.RECT_COLOR)
if rect and not isinstance(model, PinholeCameraModel):
raise Exception(
'camera model is not a PinholeCameraModel instance')
raw_encoding = raw_msg.encoding
# convert bayer to color and mono as needed
if raw_encoding.find('bayer') != -1:
if color:
out.color = cvtColor2(out.raw, raw_encoding, 'bgr8')
out.color_encoding = 'bgr8'
if mono:
out.mono = cvtColor2(out.raw, raw_encoding, 'mono8')
elif raw_encoding.find('mono') != -1:
if mono:
out.mono = out.raw
if color:
raise Exception('cant get color from mono image')
else: # Otherwise assume color
if mono:
out.mono = cvtColor2(out.raw, raw_encoding, 'mono8')
if color:
out.color = out.raw
out.color_encoding = raw_encoding
if flags & ImageProc.RECT:
if out.rect is None:
out.rect = np.zeros(out.mono.shape)
model.rectifyImage(out.mono, out.rect)
if flags & ImageProc.RECT_COLOR:
if out.rect_color is None:
out.rect_color = np.zeros(out.color.shape, out.color.dtype)
model.rectifyImage(out.color, out.rect_color)
def process(raw_msg, model, out, flags):
'''
Given an original image message (sensor_msgs/Image), fill in the out ImageSet with the
processed (debayered, rectified, grayscaled) images (in numpy format) based on the flags.
@param raw_msg: sensor_msgs/Image original image message to process
@param model: image_geometry.PinholeCameraModel object used to rectify images if RECT or RECT_COLOR flag is set.
Can just pass in None if you aren't using RECT or RECT_COLOR
@param out: an ImageSet object. The requested images will be set in out based on the flags bitmask
@param flags: an integer bitmask inticating which processed images you want in out.
ex: process(msg, model, out, ImageProc.RECT_COLOR | ImageProc.RECT)
will fill the raw, rect_color, and rect images in out.
'''
# always set raw
out.raw = ImageProc.bridge.imgmsg_to_cv2(raw_msg)
if not bool(flags & ImageProc.ALL):
return
mono = ImageProc.MONO | ImageProc.RECT
color = ImageProc.COLOR | ImageProc.RECT_COLOR
# Check that camera model is set if we are rectifying an image
rect = bool(ImageProc.RECT | ImageProc.RECT_COLOR)
if rect and not isinstance(model, PinholeCameraModel):
raise Exception('camera model is not a PinholeCameraModel instance')
raw_encoding = raw_msg.encoding
# convert bayer to color and mono as needed
if raw_encoding.find('bayer') != -1:
if color:
out.color = cvtColor2(out.raw, raw_encoding, 'bgr8')
out.color_encoding = 'bgr8'
if mono:
out.mono = cvtColor2(out.raw, raw_encoding, 'mono8')
elif raw_encoding.find('mono') != -1:
if mono:
out.mono = out.raw
if color:
raise Exception('cant get color from mono image')
else: # Otherwise assume color
if mono:
out.mono = cvtColor2(out.raw, raw_encoding, 'mono8')
if color:
out.color = out.raw
out.color_encoding = raw_encoding
if flags & ImageProc.RECT:
if out.rect is None:
out.rect = np.zeros(out.mono.shape)
model.rectifyImage(out.mono, out.rect)
if flags & ImageProc.RECT_COLOR:
if out.rect_color is None:
out.rect_color = np.zeros(out.color.shape, out.color.dtype)
model.rectifyImage(out.color, out.rect_color)
def imgmsg_to_cv2(self, img_msg, desired_encoding = "passthrough"):
"""
Convert a sensor_msgs::Image message to an OpenCV :ctype:`cv::Mat`.
:param img_msg: A sensor_msgs::Image message
:param desired_encoding: The encoding of the image data, one of the following strings:
* ``"passthrough"``
* one of the standard strings in sensor_msgs/image_encodings.h
:rtype: :ctype:`cv::Mat`
:raises CvBridgeError: when conversion is not possible.
If desired_encoding is ``"passthrough"``, then the returned image has the same format as img_msg.
Otherwise desired_encoding must be one of the standard image encodings
This function returns an OpenCV :ctype:`cv::Mat` message on success, or raises :exc:`cv_bridge.CvBridgeError` on failure.
"""
import cv2
import numpy as np
dtype, n_channels = self.encoding_to_dtype_with_channels(img_msg.encoding)
im = np.ndarray(shape=(img_msg.height, img_msg.width, n_channels),
dtype=dtype, buffer=img_msg.data)
if desired_encoding == "passthrough":
return im
from cv_bridge.boost.cv_bridge_boost import cvtColor2
try:
res = cvtColor2(im, img_msg.encoding, desired_encoding)
except RuntimeError as e:
raise CvBridgeError(e)
return res
def compressed_imgmsg_to_cv2(cmprs_img_msg, desired_encoding="passthrough"):
"""
Convert a sensor_msgs::CompressedImage message to an OpenCV :cpp:type:`cv::Mat`.
:param cmprs_img_msg: A :cpp:type:`sensor_msgs::CompressedImage` message
:param desired_encoding: The encoding of the image data, one of the following strings:
* ``"passthrough"``
* one of the standard strings in sensor_msgs/image_encodings.h
:rtype: :cpp:type:`cv::Mat`
:raises CvBridgeError: when conversion is not possible.
If desired_encoding is ``"passthrough"``, then the returned image has the same format as img_msg.
Otherwise desired_encoding must be one of the standard image encodings
This function returns an OpenCV :cpp:type:`cv::Mat` message on success, or raises :exc:`cv_bridge.CvBridgeError` on failure.
If the image only has one channel, the shape has size 2 (width and height)
"""
str_msg = cmprs_img_msg.data
buf = np.ndarray(shape=(1, len(str_msg)),
dtype=np.uint8,
buffer=cmprs_img_msg.data)
im = cv2.imdecode(buf, cv2.IMREAD_ANYCOLOR)
if desired_encoding == "passthrough":
return im
try:
res = cvtColor2(im, "bgr8", desired_encoding)
except RuntimeError as e:
raise CvBridgeError(e)
return res
def process(self, args, images):
dir = Path(args.dir)
image_bridge = CvBridge()
idx = 0
dir.mkdir(parents=True, exist_ok=True)
for topic, img_msg, t in images:
img = image_bridge.imgmsg_to_cv2(img_msg)
if args.encoding != 'passthrough':
if img_msg.encoding.startswith('bayer_') and args.demosaicing:
# use custom debayering
# cvtColor2 unfortunately doesn't expose a demosaicing algorithm parameter
conv_code = conversion_code(
img_msg.encoding, args.encoding, args.demosaicing)
img = cv.cvtColor(img, conv_code)
else:
try:
img = cvtColor2(img, img_msg.encoding, args.encoding)
except RuntimeError as e:
raise CvBridgeError(e)
tpc_path = topic.lstrip('/').replace('/', '_')
filename = args.name.replace('%tpc', tpc_path)
filename = filename.replace('%t', str(t))
filename = filename.replace('%i', str(idx).zfill(8))
img_path = dir / filename
cv.imwrite(str(img_path), img)
idx += 1
def imgmsg_to_cv2(self, img_msg, desired_encoding="passthrough"):
"""
Convert a sensor_msgs::Image message to an OpenCV :cpp:type:`cv::Mat`.
:param img_msg: A :cpp:type:`sensor_msgs::Image` message
:param desired_encoding: The encoding of the image data, one of the following strings:
* ``"passthrough"``
* one of the standard strings in sensor_msgs/image_encodings.h
:rtype: :cpp:type:`cv::Mat`
:raises CvBridgeError: when conversion is not possible.
If desired_encoding is ``"passthrough"``, then the returned image has the same format as img_msg.
Otherwise desired_encoding must be one of the standard image encodings
This function returns an OpenCV :cpp:type:`cv::Mat` message on success, or raises :exc:`cv_bridge.CvBridgeError` on failure.
If the image only has one channel, the shape has size 2 (width and height)
"""
import cv2
import numpy as np
if img_msg.encoding == '32FC1':
dtype = 'float32'
n_channels = 1
elif img_msg.encoding == '32FC4':
dtype = 'float32'
n_channels = 4
elif img_msg.encoding == '8UC4':
dtype = 'uint8'
n_channels = 4
else:
dtype, n_channels = self.encoding_to_dtype_with_channels(
img_msg.encoding)
dtype = np.dtype(dtype)
dtype = dtype.newbyteorder('>' if img_msg.is_bigendian else '<')
if n_channels == 1:
im = np.ndarray(shape=(img_msg.height, img_msg.width),
dtype=dtype,
buffer=img_msg.data)
else:
im = np.ndarray(shape=(img_msg.height, img_msg.width, n_channels),
dtype=dtype,
buffer=img_msg.data)
# If the byt order is different between the message and the system.
if img_msg.is_bigendian == (sys.byteorder == 'little'):
im = im.byteswap().newbyteorder()
if desired_encoding == "passthrough":
return im
from cv_bridge.boost.cv_bridge_boost import cvtColor2
try:
res = cvtColor2(im, img_msg.encoding, desired_encoding)
except RuntimeError as e:
raise CvBridgeError(e)
return res
def imgmsg_to_cv2(self, img_msg, desired_encoding = "passthrough"):
"""
Convert a sensor_msgs::Image message to an OpenCV :cpp:type:`cv::Mat`.
:param img_msg: A :cpp:type:`sensor_msgs::Image` message
:param desired_encoding: The encoding of the image data, one of the following strings:
* ``"passthrough"``
* one of the standard strings in sensor_msgs/image_encodings.h
:rtype: :cpp:type:`cv::Mat`
:raises CvBridgeError: when conversion is not possible.
If desired_encoding is ``"passthrough"``, then the returned image has the same format as img_msg.
Otherwise desired_encoding must be one of the standard image encodings
This function returns an OpenCV :cpp:type:`cv::Mat` message on success, or raises :exc:`cv_bridge.CvBridgeError` on failure.
If the image only has one channel, the shape has size 2 (width and height)
"""
import cv2
import numpy as np
dtype, n_channels = self.encoding_to_dtype_with_channels(img_msg.encoding)
dtype = np.dtype(dtype)
dtype = dtype.newbyteorder('>' if img_msg.is_bigendian else '<')
if n_channels == 1:
im = np.ndarray(shape=(img_msg.height, img_msg.width),
dtype=dtype, buffer=img_msg.data)
else:
im = np.ndarray(shape=(img_msg.height, img_msg.width, n_channels),
dtype=dtype, buffer=img_msg.data)
# If the byt order is different between the message and the system.
if img_msg.is_bigendian == (sys.byteorder == 'little'):
im = im.byteswap().newbyteorder()
if desired_encoding == "passthrough":
return im
from cv_bridge.boost.cv_bridge_boost import cvtColor2
try:
res = cvtColor2(im, img_msg.encoding, desired_encoding)
except RuntimeError as e:
raise CvBridgeError(e)
return res
def compressed_imgmsg_to_cv2(self, cmprs_img_msg, desired_encoding = "passthrough"):
"""
Convert a sensor_msgs::CompressedImage message to an OpenCV :cpp:type:`cv::Mat`.
:param cmprs_img_msg: A :cpp:type:`sensor_msgs::CompressedImage` message
:param desired_encoding: The encoding of the image data, one of the following strings:
* ``"passthrough"``
* one of the standard strings in sensor_msgs/image_encodings.h
:rtype: :cpp:type:`cv::Mat`
:raises CvBridgeError: when conversion is not possible.
If desired_encoding is ``"passthrough"``, then the returned image has the same format as img_msg.
Otherwise desired_encoding must be one of the standard image encodings
This function returns an OpenCV :cpp:type:`cv::Mat` message on success, or raises :exc:`cv_bridge.CvBridgeError` on failure.
If the image only has one channel, the shape has size 2 (width and height)
"""
import cv2
import numpy as np
str_msg = cmprs_img_msg.data
buf = np.ndarray(shape=(1, len(str_msg)),
dtype=np.uint8, buffer=cmprs_img_msg.data)
im = cv2.imdecode(buf, cv2.IMREAD_ANYCOLOR)
if desired_encoding == "passthrough":
return im
from cv_bridge.boost.cv_bridge_boost import cvtColor2
try:
res = cvtColor2(im, "bgr8", desired_encoding)
except RuntimeError as e:
raise CvBridgeError(e)
return res
