问题是因为有 2 个 ImageWriter 对象，一个在 imgw = ImageWriter() 中创建，另一个在 QML 中，您可以通过在 .qml 中的 .py 中添加打印来组合它：
*.py
def get_frames(app):
cap = cv2.VideoCapture(0)
num = 0
imgw = ImageWriter()
print("Python:", imgw)
...
*.qml
...
Component.onCompleted: console.log("QML:", imageWriter)
...
输出：
qml: >>>> ImageWriter(0x55bf2927e770)
Python: <__main__.ImageWriter object at 0x7fce8e4ff798>
如您所见，有 2 个对象指向不同的内存地址，因此一种可能的解决方案是使用 this library 创建一个单例：
from OpenGL import GL
import sys
from PyQt5 import QtCore, QtGui, QtQml, QtQuick
import cv2
try: from PyQt5.QtCore import pyqtWrapperType
except ImportError:
from sip import wrappertype as pyqtWrapperType
class Singleton(pyqtWrapperType, type):
def __init__(cls, name, bases, dict):
super().__init__(name, bases, dict)
cls.instance=None
def __call__(cls,*args,**kw):
if cls.instance is None:
cls.instance=super().__call__(*args, **kw)
return cls.instance
class ImageWriter(QtQuick.QQuickPaintedItem, metaclass=Singleton):
def __init__(self, *args, **kwargs):
super(ImageWriter, self).__init__(*args, **kwargs)
self.setRenderTarget(QtQuick.QQuickPaintedItem.FramebufferObject)
self.cam_frame = QtGui.QImage()
def paint(self, painter):
painter.drawImage(0, 0, self.cam_frame)
def update_frame(self,frame):
frame = cv2.resize(frame, (700, 500), cv2.INTER_AREA)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)
frame = QtGui.QImage(frame, frame.shape[1], frame.shape[0], 17)
self.cam_frame = frame.copy()
self.update()
def get_frames(app):
cap = cv2.VideoCapture(0)
num = 0
imgw = ImageWriter()
while True:
while num != 30:
_ , bgframe = cap.read()
num += 1
ret, frame = cap.read()
if ret:
imgw.update_frame(frame)
#print("get frames")
app.processEvents()
if __name__ == '__main__':
app = QtGui.QGuiApplication(sys.argv)
QtQml.qmlRegisterType(ImageWriter, "imageWriter", 1, 0, "ImageWriter")
view = QtQuick.QQuickView()
view.setSource(QtCore.QUrl('test.qml'))
rootObject = view.rootObject()
view.show()
get_frames(app)
sys.exit(app.exec_())
有了上面应该可以工作的图像采集我认为有更好的方法，稍后我会展示一个更好的选择。
使用my previous answer 作为基础，我创建了一个模块，该模块使用opencv 实现相机的处理程序，此外还有一个查看器和一个允许添加过滤器的通用类，为此项目必须具有以下结构
├── main.py
├── main.qml
└── PyCVQML
├── cvcapture.py
├── cvitem.py
└── __init__.py
PyCVQML/cvcapture.py
import numpy as np
import threading
import cv2
from PyQt5 import QtCore, QtGui, QtQml
gray_color_table = [QtGui.qRgb(i, i, i) for i in range(256)]
class CVAbstractFilter(QtCore.QObject):
def process_image(self, src):
dst = src
return dst
class CVCapture(QtCore.QObject):
started = QtCore.pyqtSignal()
imageReady = QtCore.pyqtSignal()
indexChanged = QtCore.pyqtSignal()
def __init__(self, parent=None):
super(CVCapture, self).__init__(parent)
self._image = QtGui.QImage()
self._index = 0
self.m_videoCapture = cv2.VideoCapture()
self.m_timer = QtCore.QBasicTimer()
self.m_filters = []
self.m_busy = False
@QtCore.pyqtSlot()
@QtCore.pyqtSlot(int)
def start(self, *args):
if args:
self.setIndex(args[0])
self.m_videoCapture.release()
self.m_videoCapture = cv2.VideoCapture(self._index)
if self.m_videoCapture.isOpened():
self.m_timer.start(0, self)
self.started.emit()
@QtCore.pyqtSlot()
def stop(self):
self.m_timer.stop()
def timerEvent(self, e):
if e.timerId() != self.m_timer.timerId(): return
ret, frame = self.m_videoCapture.read()
if not ret:
self.m_timer.stop()
return
if not self.m_busy:
threading.Thread(target=self.process_image, args=(np.copy(frame),)).start()
@QtCore.pyqtSlot(np.ndarray)
def process_image(self, frame):
self.m_busy = True
for f in self.m_filters:
frame = f.process_image(frame)
image = CVCapture.ToQImage(frame)
self.m_busy = False
QtCore.QMetaObject.invokeMethod(self,
"setImage",
QtCore.Qt.QueuedConnection,
QtCore.Q_ARG(QtGui.QImage, image))
@staticmethod
def ToQImage(im):
if im is None:
return QtGui.QImage()
if im.dtype == np.uint8:
if len(im.shape) == 2:
qim = QtGui.QImage(im.data, im.shape[1], im.shape[0], im.strides[0], QtGui.QImage.Format_Indexed8)
qim.setColorTable(gray_color_table)
return qim.copy()
elif len(im.shape) == 3:
if im.shape[2] == 3:
w, h, _ = im.shape
rgb_image = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
flip_image = cv2.flip(rgb_image, 1)
qim = QtGui.QImage(flip_image.data, h, w, QtGui.QImage.Format_RGB888)
return qim.copy()
return QtGui.QImage()
def image(self):
return self._image
@QtCore.pyqtSlot(QtGui.QImage)
def setImage(self, image):
if self._image == image: return
self._image = image
self.imageReady.emit()
def index(self):
return self._index
def setIndex(self, index):
if self._index == index: return
self._index = index
self.indexChanged.emit()
@QtCore.pyqtProperty(QtQml.QQmlListProperty)
def filters(self):
return QtQml.QQmlListProperty(CVAbstractFilter, self, self.m_filters)
image = QtCore.pyqtProperty(QtGui.QImage, fget=image, notify=imageReady)
index = QtCore.pyqtProperty(int, fget=index, fset=setIndex, notify=indexChanged)
PyCVQML/cvitem.py
from PyQt5 import QtCore, QtGui, QtQuick
class CVItem(QtQuick.QQuickPaintedItem):
imageChanged = QtCore.pyqtSignal()
def __init__(self, parent=None):
super(CVItem, self).__init__(parent)
# self.setRenderTarget(QtQuick.QQuickPaintedItem.FramebufferObject)
self.m_image = QtGui.QImage()
def paint(self, painter):
if self.m_image.isNull(): return
image = self.m_image.scaled(self.size().toSize())
painter.drawImage(QtCore.QPoint(), image)
def image(self):
return self.m_image
def setImage(self, image):
if self.m_image == image: return
self.m_image = image
self.imageChanged.emit()
self.update()
image = QtCore.pyqtProperty(QtGui.QImage, fget=image, fset=setImage, notify=imageChanged)
PyCVQML/__init__.py
from PyQt5 import QtQml
from .cvcapture import CVCapture, CVAbstractFilter
from .cvitem import CVItem
def registerTypes(uri = "PyCVQML"):
QtQml.qmlRegisterType(CVCapture, uri, 1, 0, "CVCapture")
QtQml.qmlRegisterType(CVItem, uri, 1, 0, "CVItem")
然后你在main.py中使用它，我添加了2个示例过滤器，因为这个CVCapture具有过滤器传递给它的过滤器属性，它们将按照它们建立的顺序执行。要实现新的过滤器，您必须从 CVAbstractFilter 继承并覆盖以np.ndarray 形式接收图像的process_image() 方法，并且应该在过滤器之后返回结果。
main.py
import cv2
import numpy as np
from PyQt5 import QtGui, QtCore, QtQuick, QtQml
import PyCVQML
def max_rgb_filter(image):
# split the image into its BGR components
(B, G, R) = cv2.split(image)
# find the maximum pixel intensity values for each
# (x, y)-coordinate,, then set all pixel values less
# than M to zero
M = np.maximum(np.maximum(R, G), B)
R[R < M] = 0
G[G < M] = 0
B[B < M] = 0
# merge the channels back together and return the image
return cv2.merge([B, G, R])
def rgb_to_gray(image):
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
return gray
class MaxRGBFilter(PyCVQML.CVAbstractFilter):
def process_image(self, src):
return max_rgb_filter(src)
class GrayFilter(PyCVQML.CVAbstractFilter):
def process_image(self, src):
return rgb_to_gray(src)
if __name__ == '__main__':
import os
import sys
app = QtGui.QGuiApplication(sys.argv)
PyCVQML.registerTypes()
QtQml.qmlRegisterType(MaxRGBFilter, "Filters", 1, 0, "MaxRGBFilter")
QtQml.qmlRegisterType(GrayFilter, "Filters", 1, 0, "GrayFilter")
view = QtQuick.QQuickView()
view.setTitle("PyCVQML Example")
dir_path = os.path.dirname(os.path.realpath(__file__)
view.setSource(QtCore.QUrl.fromLocalFile(QtCore.QDir(dir_path).absoluteFilePath("main.qml")))
view.show()
sys.exit(app.exec_())
main.qml
import QtQuick 2.0
import PyCVQML 1.0
import Filters 1.0
Item {
width: 800
height: 600
CVItem {
id: imageWriter
anchors.fill: parent
image: capture.image
}
MaxRGBFilter{
id: max_rgb_filter
}
GrayFilter{
id: gray_filter
}
CVCapture{
id: capture
index: 0
filters: [max_rgb_filter, gray_filter]
Component.onCompleted: capture.start()
}
}