图像识别（四）光点的运动轨迹

最新推荐文章于 2022-07-17 16:30:10 发布

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最新推荐文章于 2022-07-17 16:30:10 发布

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分类专栏：图像识别文章标签：光点追踪

本文链接：https://blog.youkuaiyun.com/qq_29507011/article/details/99901398

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本文介绍了一个利用Python中的Matplotlib和OpenCV库创建动态轨迹动画的实例。通过从视频文件中读取帧并提取关键点，然后在Matplotlib画布上绘制这些点的轨迹，形成了一个动态更新的动画。特别注意了在动画更新函数中正确返回多个对象以避免错误。

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遇到一个坑，plot动画update init返回值需要逗号，不然报错
代码如下：

import cv2
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation

path = r'./t3.mp4'
cap = cv2.VideoCapture(path)

def get_threshold(image):
	_,image = cv2.threshold(image,220,255,cv2.THRESH_BINARY)
	return image

def show_image(image,num=0):
	name = 'num is '+str(num)
	#h,w = image.shape
	# h,w = int(h*0.5),int(w*0.5)
	cv2.namedWindow(name,0)
	#cv2.resizeWindow(name,w,h)
	cv2.imshow(name,image)
	cv2.waitKey(1000)
	cv2.destroyAllWindows()

def get_box(image):
	image_map = np.zeros(image.shape)
	_,contours,h = cv2.findContours(image,0,1)
	for contour in contours:
		eps = 1e-3 * cv2.arcLength(contour,True)
		#拟合多边形
		approx = cv2.approxPolyDP(contour,eps,True)
		#提取矩形
		rect = cv2.minAreaRect(approx)
		#提取矩形坐标
		box = cv2.boxPoints(rect)
		box = np.int0(box)
		center_x = (box[0][0]+box[2][0])/2
		center_y = (box[0][1]+box[2][1])/2
	return center_x,center_y

x_list = []
y_list = []
xdata = []
ydata = []

#配置画布尺寸
fig = plt.figure()
ax = plt.axes(xlim=(0,2000),ylim=(0,1000))

scatters = plt.scatter(xdata, ydata, marker = 'o', color = 'green',s=120)
def init():
	return scatters,

def update(frame):
	print(frame)
	xdata.append(frame[0])
	ydata.append(frame[1])
	#scatters.set_data(xdata,ydata)
	scatters = plt.scatter(xdata, ydata, marker = 'o', color = 'green',s=10)
	return scatters,

def get_data_list(x_list,y_list):
	num = len(x_list)
	data_list = []
	for i in range(num):
		data_list.append([x_list[i],y_list[i]])
	return data_list

try:
	while (cap.isOpened()):
		ret,frame = cap.read()
		image = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
		image = get_threshold(image)
		center_x,center_y = get_box(image)
		x_list.append(center_x)
		y_list.append(center_y)
		
		#show_image(image)
except Exception as e:
	print(e)
finally:
	#data_list = np.stack([x_list,y_list],axis=1)
	data_list = get_data_list(x_list,y_list)
	ani = FuncAnimation(
			fig = fig,
			func = update,
			frames = data_list,
			interval=10,
			init_func=init,
			blit = True
			)
	ani.save('points.gif',writer = 'imagemagick')
	plt.show()

效果图如下：
在这里插入图片描述