Displaying Camera Feed in Software: Guidance on Which Control to Use

[jiangtangaaaa]

@CVHub520 大佬中午好，我又来麻烦您了，希望您不要介意

我想把摄像头的实时影像展示在软件上，我应该怎么操作，或者应该调用哪个控件？
ret, frame = cap.read() self.label.setPixmap(QPixmap.fromImage(frame))
希望您可以指点我一下

[CVHub520]

To display the live feed from a camera in X-AnyLabeling, you would typically use a video capturing library to capture frames from the camera and then display those frames in a suitable widget. In PyQt, you can use the QLabel widget to display the video frames.
Here's a basic outline of the steps you would follow:

1. Capture Frames: Use a library like OpenCV to capture frames from the camera.
2. Convert Frames: Convert the frames to a format that can be displayed in PyQt, such as QImage.
3. Display Frames: Use a QLabel widget to display the frames.
   Your code snippet seems to be on the right track. However, you need to ensure that the frame is converted to a QImage before setting it as a pixmap for the QLabel. Here's a revised version of your code:

import cv2
from PyQt5.QtWidgets import QLabel
from PyQt5.QtGui import QImage, QPixmap
import numpy as np
# Assuming 'cap' is your video capture object
ret, frame = cap.read()
# Convert the frame from BGR to RGB (OpenCV uses BGR, while QImage uses RGB)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# Convert the frame to a QImage
h, w, ch = frame.shape
bytesPerLine = ch * w
qImg = QImage(frame.data, w, h, bytesPerLine, QImage.Format_RGB888)
# Set the pixmap of the QLabel to the QImage
self.label.setPixmap(QPixmap.fromImage(qImg))

Make sure to run the frame capture and display code in a separate thread or use a timer to continuously update the QLabel with new frames to avoid freezing app's main thread.

[jiangtangaaaa]

To display the live feed from a camera in X-AnyLabeling, you would typically use a video capturing library to capture frames from the camera and then display those frames in a suitable widget. In PyQt, you can use the QLabel widget to display the video frames. Here's a basic outline of the steps you would follow:

1. Capture Frames: Use a library like OpenCV to capture frames from the camera.
2. Convert Frames: Convert the frames to a format that can be displayed in PyQt, such as QImage.
3. Display Frames: Use a QLabel widget to display the frames.
   Your code snippet seems to be on the right track. However, you need to ensure that the frame is converted to a QImage before setting it as a pixmap for the QLabel. Here's a revised version of your code:

import cv2
from PyQt5.QtWidgets import QLabel
from PyQt5.QtGui import QImage, QPixmap
import numpy as np
# Assuming 'cap' is your video capture object
ret, frame = cap.read()
# Convert the frame from BGR to RGB (OpenCV uses BGR, while QImage uses RGB)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# Convert the frame to a QImage
h, w, ch = frame.shape
bytesPerLine = ch * w
qImg = QImage(frame.data, w, h, bytesPerLine, QImage.Format_RGB888)
# Set the pixmap of the QLabel to the QImage
self.label.setPixmap(QPixmap.fromImage(qImg))

Make sure to run the frame capture and display code in a separate thread or use a timer to continuously update the QLabel with new frames to avoid freezing app's main thread.

To display the live feed from a camera in X-AnyLabeling, you would typically use a video capturing library to capture frames from the camera and then display those frames in a suitable widget. In PyQt, you can use the QLabel widget to display the video frames. Here's a basic outline of the steps you would follow:

1. Capture Frames: Use a library like OpenCV to capture frames from the camera.
2. Convert Frames: Convert the frames to a format that can be displayed in PyQt, such as QImage.
3. Display Frames: Use a QLabel widget to display the frames.
   Your code snippet seems to be on the right track. However, you need to ensure that the frame is converted to a QImage before setting it as a pixmap for the QLabel. Here's a revised version of your code:

import cv2
from PyQt5.QtWidgets import QLabel
from PyQt5.QtGui import QImage, QPixmap
import numpy as np
# Assuming 'cap' is your video capture object
ret, frame = cap.read()
# Convert the frame from BGR to RGB (OpenCV uses BGR, while QImage uses RGB)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# Convert the frame to a QImage
h, w, ch = frame.shape
bytesPerLine = ch * w
qImg = QImage(frame.data, w, h, bytesPerLine, QImage.Format_RGB888)
# Set the pixmap of the QLabel to the QImage
self.label.setPixmap(QPixmap.fromImage(qImg))

Make sure to run the frame capture and display code in a separate thread or use a timer to continuously update the QLabel with new frames to avoid freezing app's main thread.

感谢您指点我，首先您说使用多线程是对的，不然会冻结主线程
我的意思是在X-AnyLabeling的标注区域内展示摄像头图像，我现在把转换后的图像让canvas加载出来显示了实时影像，self.canvas.load_pixmap(QPixmap.fromImage(p))
但是有一个问题是：实时影像我不知道该怎么跟缩放联系起来，如果我点击缩放按钮或者按住Ctrl+滚轮，就会导致程序退出
我现在正在研究这段代码,还没有思路把实时影像和缩放联系起来，而且影像画面有点小

# set zoom values
        is_initial_load = not self.zoom_values
        print(self.zoom_values)
        print(is_initial_load)
        if self.filename in self.zoom_values:
            self.zoom_mode = self.zoom_values[self.filename][0]
            self.set_zoom(self.zoom_values[self.filename][1])
        elif is_initial_load or not self._config["keep_prev_scale"]:
            self.adjust_scale(initial=True)
        # set scroll values
        for orientation in self.scroll_values:
            if self.filename in self.scroll_values[orientation]:
                self.set_scroll(
                    orientation, self.scroll_values[orientation][self.filename]
                )

[jiangtangaaaa]

@CVHub520 您好~~早上好