python cv2.imshow wait_time

The parameter "wait_time" in the cv2.imshow() function in Python OpenCV is used to specify the amount of time to wait for a keyboard event before closing the window.

If the wait_time is set to 0, the window will remain open until the user manually closes it.

If the wait_time is set to a positive integer, for example, wait_time=100, the window will be displayed for 100 milliseconds before it is closed.

The wait_time parameter is useful for displaying multiple images in sequence, where each image is displayed for a certain amount of time before being replaced by the next image.

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修改此代码使其可重复运行import pygame import sys from pygame.locals import * from robomaster import * import cv2 import numpy as np focal_length = 750 # 焦距 known_radius = 2 # 已知球的半径 def calculate_distance(focal_length, known_radius, perceived_radius): distance = (known_radius * focal_length) / perceived_radius return distance def show_video(ep_robot, screen): 获取机器人第一视角图像帧 img = ep_robot.camera.read_cv2_image(strategy="newest") 转换图像格式，转换为pygame的surface对象 img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) img = cv2.transpose(img) # 行列互换 img = pygame.surfarray.make_surface(img) screen.blit(img, (0, 0)) # 绘制图像 def detect_white_circle(ep_robot): 获取机器人第一视角图像帧 img = ep_robot.camera.read_cv2_image(strategy="newest") 转换为灰度图像 gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 进行中值滤波处理 gray = cv2.medianBlur(gray, 5) 检测圆形轮廓 circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, 50, param1=160, param2=40, minRadius=5, maxRadius=60) if circles is not None: circles = np.uint16(np.around(circles)) for circle in circles[0, :]: center = (circle[0], circle[1]) known_radius = circle 在图像上绘制圆形轮廓 cv2.circle(img, center, known_radius, (0, 255, 0), 2) 显示图像 distance = calculate_distance(focal_length, known_radius, known_radius) 在图像上绘制圆和距离 cv2.circle(img, center, known_radius, (0, 255, 0), 2) cv2.putText(img, f"Distance: {distance:.2f} cm", (center[0] - known_radius, center[1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2) cv2.imshow("White Circle Detection", img) cv2.waitKey(1) def main(): pygame.init() screen_size = width, height = 1280, 720 screen = pygame.display.set_mode(screen_size) ep_robot = robot.Robot() ep_robot.initialize(conn_type='ap') version = ep_robot.get_version() print("Robot version: {0}".format(version)) ep_robot.camera.start_video_stream(display=False) pygame.time.wait(100) clock = pygame.time.Clock() while True: clock.tick(5) # 将帧数设置为25帧 for event in pygame.event.get(): if event.type == QUIT: ep_robot.close() pygame.quit() sys.exit() show_video(ep_robot, screen) detect_white_circle(ep_robot) if name == 'main': main()

修改后的代码如下所示：

import pygame
import sys
from pygame.locals import *
import robomaster
import cv2
import numpy as np

focal_length = 750  # 焦距
known_radius = 2  # 已知球的半径


def calculate_distance(focal_length, known_radius, perceived_radius):
    distance = (known_radius * focal_length) / perceived_radius
    return distance


def show_video(ep_robot, screen):
    # 获取机器人第一视角图像帧
    img = ep_robot.camera.read_cv2_image(strategy="newest")

    # 转换图像格式，转换为pygame的surface对象
    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    img = cv2.transpose(img)  # 行列互换
    img = pygame.surfarray.make_surface(img)
    screen.blit(img, (0, 0))  # 绘制图像


def detect_white_circle(ep_robot):
    # 获取机器人第一视角图像帧
    img = ep_robot.camera.read_cv2_image(strategy="newest")

    # 转换为灰度图像
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # 进行中值滤波处理
    gray = cv2.medianBlur(gray, 5)

    # 检测圆形轮廓
    circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, 50, param1=160, param2=40, minRadius=5, maxRadius=60)
    if circles is not None:
        circles = np.uint16(np.around(circles

cv2.convertScaleAbs

cv2.convertScaleAbs is a function in OpenCV library in Python used to convert an image from one data type to another and then apply an absolute transformation. This function is used for linear scaling of pixel values from one range to another range. It is commonly used to enhance the contrast of an image.

Syntax: cv2.convertScaleAbs(src, alpha, beta)

Parameters:

src: It is the source or input image of type uint8 or float32.

alpha: It is a scalar used to multiply pixel values.

beta: It is a scalar used to add to pixel values.

Return Value: It returns the converted image of type uint8.

Example:

import cv2

img = cv2.imread('image.jpg')

converted_img = cv2.convertScaleAbs(img, alpha=2, beta=50)

cv2.imshow('Original Image', img)

cv2.imshow('Converted Image', converted_img)

cv2.waitKey(0)

cv2.destroyAllWindows()

In the above example, the input image is read using the imread() function. Then the convertScaleAbs() function is used to convert the image by multiplying pixel values by 2 and adding 50 to them. The converted image is then displayed using the imshow() function. Finally, the waitKey() function is used to wait until a key is pressed and the destroyAllWindows() function is used to close all windows.