实时将cv2.imshow()与matplotlib plt.show()结合 [英] Combining cv2.imshow() with matplotlib plt.show() in real time

问题描述

我正在尝试使用openCV合并来自网络摄像头的供稿，然后使用matplotlib更新图形.

I'm trying to combine a feed from webcam using openCV, and then updating a graph using matplotlib.

获取和显示框架的基本示例:

For getting and showing the frames a basic example:

import cv2

cap = cv2.VideoCapture(0)

while(True):
    # Capture frame-by-frame
    ret, frame = cap.read()

    # Display the resulting frame
    cv2.imshow('frame',frame)

    # When to exit loop - terminate program
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()

使用matplotlib连续更新图形(随机绘图)的示例:

An example of continuously updating a graph (plotting randomly) with matplotlib:

import numpy as np
import matplotlib.pyplot as plt

x = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
y = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

# x goes from 0-9 numbers
# y goes from 0-100%
fig = plt.figure()
ax = plt.axes(xlim=(0, 9), ylim=(0, 100))
# line, = ax.plot([], [], lw=2)
rects = plt.bar(x, y, color='b')

def animate(i):
    y = random.sample(xrange(100), 10)
    for rect, yi in zip(rects, y):
        rect.set_height(yi)
    return rects

anim = animation.FuncAnimation(fig, animate,
                           frames=200, interval=20, blit=True)

plt.show()

所以我想要将两者结合在一起.应该通过传递我从框架中获得的结果来更新该图.我面临的主要问题是使两个窗口同时并发更新. plt.show()似乎在阻止其他所有内容.

So what I want is to combine the two together. The graph should be updated by passing results that I obtain from the frames. The major problem I am facing is getting both windows to update simultaneously side by side. The plt.show() seems to be blocking everything else.

有任何解决方法的想法吗?

Any idea on how to resolve?

欢呼

推荐答案

下面是将plt.figure()转换为np.array并通过cv2.imshow

Here's an example of converting a plt.figure() to np.array and show it along camera feed with cv2.imshow

import matplotlib
matplotlib.use('TkAgg')

import numpy as np
import cv2
import matplotlib.pyplot as plt

fig = plt.figure()
cap = cv2.VideoCapture(0)


x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)

y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)


line1, = plt.plot(x1, y1, 'ko-')        # so that we can update data later

for i in range(1000):
    # update data
    line1.set_ydata(np.cos(2 * np.pi * (x1+i*3.14/2) ) * np.exp(-x1) )

    # redraw the canvas
    fig.canvas.draw()

    # convert canvas to image
    img = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8,
            sep='')
    img  = img.reshape(fig.canvas.get_width_height()[::-1] + (3,))

    # img is rgb, convert to opencv's default bgr
    img = cv2.cvtColor(img,cv2.COLOR_RGB2BGR)


    # display image with opencv or any operation you like
    cv2.imshow("plot",img)

    # display camera feed
    ret,frame = cap.read()
    cv2.imshow("cam",frame)

    k = cv2.waitKey(33) & 0xFF
    if k == 27:
        break

这篇关于实时将cv2.imshow()与matplotlib plt.show()结合的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！