python cv2.imshow wait_time
时间: 2024-06-06 16:11:06 浏览: 13
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:
```python
import pygame
import sys
from pygame.locals import *
from robomaster import robot
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[2]
# 在图像上绘制圆形轮廓
cv2.circle(img, center, known_radius, (0, 255, 0), 2)
# 计算距离
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()
```
python Gst.Buffer转成彩色图片
在Python中,Gstreamer(GStreamer)是一个强大的多媒体框架,常用于处理流媒体数据。如果你想要将Gstreamer的Buffer转换为彩色图片,通常这个过程涉及到从Buffer中提取图像数据,然后可能使用OpenCV等库进行解码和显示。
首先,你需要确保你已经安装了`gstreamer`, `opencv-python`以及可能的其他依赖库。以下是一个简化的步骤:
1. **连接到Gstreamer pipeline**:
假设你已经有了一个从摄像头或者其他视频源获取数据的Gstreamer Pipeline。例如:
```python
from gi.repository import Gst, GObject
GObject.threads_init()
Gst.init(None)
pipeline_str = "v4l2src ! videoconvert ! video/x-raw,format=RGB ! appsink"
pipeline = Gst.parse_launch(pipeline_str)
```
2. **获取并复制Buffer**:
```python
bus = pipeline.get_bus()
bus.add_signal_watch()
sink_pad = pipeline.get_by_name("appsink").get_static_pad("sink")
sink_pad.link(None)
while True:
# Wait for a new buffer
buffer = bus.timed_pop_filtered(Gst.CLOCK_TIME_NONE, Gst.MessageType.EOS | Gst.MessageType.ERROR | Gst.MessageType.NEW_BUFFER)
if buffer is not None:
# 处理buffer
```
3. **解码和创建彩色图片**:
```python
if buffer.type == Gst.MessageType.NEW_BUFFER:
caps = buffer.get_caps()
img_data = buffer.extract_all_samples().get_buffer().map(Gst.MapFlags.READ)
width = caps.get_value("width")
height = caps[0].get_value("height")
# 使用OpenCV解码图像数据
img_array = np.ndarray(shape=(height, width, 3), dtype=np.uint8, buffer=img_data)
cv2.imshow("Color Image", img_array)
# 如果需要保存图片,可以使用cv2.imwrite
# cv2.imwrite('output.jpg', img_array)
buffer.unchain()
```
4. **处理结束信号**:
```python
if buffer.type == Gst.MessageType.EOS:
print("End of stream")
break
elif buffer.type == Gst.MessageType.ERROR:
error, debug = buffer.parse_error()
print(f"Error: {error.message}, Debug: {debug}")
pipeline.set_state(Gst.State.NULL)
break
```
**相关问题--:**
1. Gstreamer的基本组件和数据类型是什么?
2. OpenCV在图像处理中的主要作用是什么?
3. 如何处理Gstreamer中的错误消息?