我想使用OpenCV和相机的SDK，VimbaPython在tkinter帧内显示来自Allied Vision相机的图像。
初始化相机的唯一可能方法是使用 Pythonwith语句：
with Vimba.get_instance() as vimba:
cams = vimba.get_all_cameras()
with cams[0] as camera:
camera.get_frame()
# Convert frame to opencv image, then use Image.fromarray and ImageTk.PhotoImage to
# display it on the tkinter GUI
到目前为止一切正常。但我不仅需要一帧。相反，我需要不断获取帧并将它们显示在屏幕上，以便流式传输。 我发现一种方法是从 tkinter 标签小部件调用.after(delay, function)方法。 因此，在获得一个帧后，我想调用相同的函数来获取一个新帧并再次显示它。代码如下所示：
with Vimba.get_instance() as vimba:
cams = vimba.get_all_cameras()
with cams[0] as camera:
def show_frame():
frame = camera.get_frame()
frame = frame.as_opencv_image()
im = Image.fromarray(frame)
img = Image.PhotoImage(im)
lblVideo.configure(image=img) # this is the Tkinter Label Widget
lblVideo.image = img
show_frame()
lblVideo.after(20, show_frame)
然后这显示了第一帧并停止，抛出一个错误，指出 Vimba 需要使用with语句进行初始化。我对 Python 了解不多，但看起来当我使用.after()方法调用函数时，它会结束 with 语句。
我想知道是否可以在不结束with的情况下执行此show_frame()函数。另外，我不能每次都初始化相机，因为程序运行得非常慢。 谢谢
我知道这个问题已经很老了，但我在Allied Vision相机上遇到了类似的问题，并发现解决方案相对强大。所以我希望这对某人有所帮助，即使不是 OP。
使用with 语句的替代方法是使用__enter__和__exit__(请参阅此处的示例)。有了这个，我为 Vimba 相机创建了一个类，在__init__期间，我使用了这些函数两次：一次用于初始化 Vimba 实例，一次用于打开相机本身。示例如下...
vimba_handle = Vimba.get_instance().__enter__()
camera = vimba_handle.get_all_cameras()[0].__enter__()
我还将包含一个更长的代码片段作为代码，但请注意，我的目的与 OP 的意图略有不同。希望它仍然有用。
class VimbaCam:
def __init__(self, device_id=0):
# Variables
self.current_frame = np.array([])
self.device = None
self.device_id = device_id
self.vimba_handle = Vimba.get_instance().__enter__()
self.is_streaming = False
self.scale_window = 4
self.stream_thread = threading.Thread(target=self.thread_stream, daemon=True)
# Default settings
self.auto_exposure = "Off"
self.auto_gain = "Off"
self.acquisition = "Continuous"
self.exposure_us = 200000
self.fps = 6.763
self.gain = 0
self.gamma = 1
self.open()
def close(self):
if self.device is not None:
if self.is_streaming:
self.stop_stream()
time.sleep(1)
self.device.__exit__(None, None, None)
self.vimba_handle.__exit__(None, None, None)
def open(self):
cams = self.vimba_handle.get_all_cameras()
if not cams:
error_check(151, currentframe())
else:
self.device = cams[self.device_id].__enter__()
self.set_defaults()
self.start_stream()
def start_stream(self):
if self.device is not None:
self.is_streaming = True
self.stream_thread.start()
time.sleep(1)
def thread_stream(self):
while self.is_streaming:
current_frame = self.device.get_frame().as_opencv_image()
h, w, _ = current_frame.shape
self.current_frame = current_frame.reshape((h, w))
self.stream_thread = threading.Thread(target=self.thread_stream, daemon=True)
def stop_stream(self):
if self.device is not None:
self.is_streaming = False
def live_video(self):
if self.device is not None:
window_name = "Allied Vision"
h, w = self.current_frame.shape
w = int(w / self.scale_window)
h = int(h / self.scale_window)
cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
cv2.resizeWindow(window_name, w, h)
while 1:
cv2.imshow(window_name, self.current_frame)
cv2.waitKey(1)
if cv2.getWindowProperty(window_name, cv2.WND_PROP_VISIBLE) < 1:
break
cv2.destroyAllWindows()
def set_defaults(self):
if self.device is not None:
# Exposure time settings
self.device.ExposureAuto.set(self.auto_exposure)
self.device.ExposureTimeAbs.set(self.exposure_us)
# Gain settings
self.device.GainAuto.set(self.auto_gain)
self.device.Gain.set(self.gain)
# Gamma settings
self.device.Gamma.set(self.gamma)
self.device.AcquisitionMode.set(self.acquisition)
self.device.AcquisitionFrameRateAbs.set(self.fps)
# Try to adjust GeV packet size (available for GigE only)
try:
self.device.GVSPAdjustPacketSize.run()
while not self.device.GVSPAdjustPacketSize.is_done():
pass
except (AttributeError, VimbaFeatureError):
pass
# Color formatting (tries mono first, then color)
cv_formats = intersect_pixel_formats(self.device.get_pixel_formats(), OPENCV_PIXEL_FORMATS)
mono_formats = intersect_pixel_formats(cv_formats, MONO_PIXEL_FORMATS)
color_formats = intersect_pixel_formats(cv_formats, COLOR_PIXEL_FORMATS)
if mono_formats:
self.device.set_pixel_format(mono_formats[0])
elif color_formats:
self.device.set_pixel_format(color_formats[0])
if __name__ == "__main__":
dev = VimbaCam()
dev.live_video()
dev.close()
您需要使用线程来运行捕获代码并传递通过queue读取的帧。 然后，主tkinter应用程序读取queue并使用.after()定期显示帧。
下面是一个基于您发布的代码的示例：
import threading
from queue import SimpleQueue
import tkinter as tk
from PIL import Image, ImageTk
from vimba import Vimba
def camera_streaming(queue):
global is_streaming
is_streaming = True
print("streaming started")
with Vimba.get_instance() as vimba:
with vimba.get_all_cameras()[0] as camera:
while is_streaming:
frame = camera.get_frame()
frame = frame.as_opencv_image()
im = Image.fromarray(frame)
img = ImageTk.PhotoImage(im)
queue.put(img) # put the capture image into queue
print("streaming stopped")
def start_streaming():
start_btn["state"] = "disabled" # disable start button to avoid running the threaded task more than once
stop_btn["state"] = "normal" # enable stop button to allow user to stop the threaded task
show_streaming()
threading.Thread(target=camera_streaming, args=(queue,), daemon=True).start()
def stop_streaming():
global is_streaming, after_id
is_streaming = False # terminate the streaming thread
if after_id:
lblVideo.after_cancel(after_id) # cancel the showing task
after_id = None
stop_btn["state"] = "disabled" # disable stop button
start_btn["state"] = "normal" # enable start button
# periodical task to show frames in queue
def show_streaming():
global after_id
if not queue.empty():
image = queue.get()
lblVideo.config(image=image)
lblVideo.image = image
after_id = lblVideo.after(20, show_streaming)
queue = SimpleQueue() # queue for video frames
after_id = None
root = tk.Tk()
lblVideo = tk.Label(root, image=tk.PhotoImage(), width=640, height=480)
lblVideo.grid(row=0, column=0, columnspan=2)
start_btn = tk.Button(root, text="Start", width=10, command=start_streaming)
start_btn.grid(row=1, column=0)
stop_btn = tk.Button(root, text="Stop", width=10, command=stop_streaming, state="disabled")
stop_btn.grid(row=1, column=1)
root.mainloop()
请注意，我没有安装相机和SDK，上面的代码可能不适合您。 我只是演示如何使用线程，队列和.after()。
下面是一个测试vimba模块(另存为vimba.py)，我用来模拟VimbaPythonOpenCV和网络摄像头的模块：
import cv2
class Frame:
def __init__(self, frame):
self.frame = frame
def as_opencv_image(self):
return self.frame
class Camera:
def __init__(self, cam_id=0):
self.cap = cv2.VideoCapture(cam_id, cv2.CAP_DSHOW)
def __enter__(self):
return self
def __exit__(self, *args):
self.cap.release()
return self
def get_frame(self):
ret, frame = self.cap.read()
if ret:
return Frame(frame)
class Vimba:
_instance = None
@classmethod
def get_instance(self):
if self._instance is None:
self._instance = Vimba()
return self._instance
def __enter__(self):
return self
def __exit__(self, *args):
return self
def get_all_cameras(self):
return (Camera(),)
我试图在openCV中读取框架并在tkinter标签中显示它们。我能够使用以下代码做到这一点：
import tkinter as tk
import cv2
from PIL import ImageTk, Image
video_path = "SAMPLE/STORED_VIDEO/PATH"
root = tk.Tk()
base_img = Image.open("PATH/TO/DEFAULT/LABLE/IMAGE")
img_obj = ImageTk.PhotoImage(base_img)
lblVideo = tk.Label(root, image=img_obj)
lblVideo.pack()
cap = cv2.VideoCapture(video_path)
if cap.isOpened():
def show_frame():
_, frame = cap.read()
im = Image.fromarray(frame)
img = ImageTk.PhotoImage(im)
lblVideo.configure(image=img)
lblVideo.image = img
lblVideo.after(1, show_frame) # Need to create callback here
show_frame()
root.mainloop()
尽管这不包含 with 语句，但您可以尝试替换show_frame函数本身中的after()回调。