def camShift():
global frame, frame2, inputmode, trackWindow, roi_hist, out
try:
cap = cv2.VideoCapture(1)
cap.set(3, 480)
cap.set(4, 320)
except:
print('카메라 구동 실패')
return
ret, frame = cap.read()
cv2.nameWindow('frame')
cv2.setMouseCallback('frame', onMouse, param=(frame, frame2))
termination = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1)
while True:
ret, frame = cap.read()
if not ret:
break
if trackWindow is not None:
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
dst = cv2.calcBackProject([hsv], [0], roi_hist, [0, 180], 1)
ret, trackWindow = cv2.Camshift(dst, trackWindow, termination)
pts = cv2.boxPoints(ret)
pts = np.int0(pts)
cv2.polylines(frame, [pts], True, (0, 255, 0), 2)
cv2.imshow('frame', frame)
k = cv2.waitKey(60) & 0xFF
if k == 27:
break
if k == ord('i'):
print('추적할 영역을 지정하고 아무키나 누르세요')
inputmode = True
frame2 = frame.copy()
while inputmode:
cv2.imshow('frame', frame)
cv2.waitKey(0)
cap.release()
cv2.destroyAllwindows()
import cv2 cam=cv2.VideoCapture(0) s, img=cam.read() winname="movement" cv2.nameWindow(winname, cv2.CV_WINDOW_AUTOSIZE) while s: cv2.imshow( winName,img ) s, img = cam.read() key = cv2.waitKey(10) if key == 27: cv2.destroyWindow(winName) break print "Goodbye"
#intent :
#Author :Michael Jack hu
#start date : 2018/10/8
#File : 人脸识别2.py
#Software : PyCharm
#finish date :
'''
# 在识别的图片上面添加人脸识别：重点注意 需要添加模型
# 1.导入库
import cv2
# 2.加载图片
img = cv2.imread('D:\04.jpg')
# 3.加载人脸模型
face = cv2.Case("D:\timg.jpg")
# 4.调整图片灰度
gray = cv2.cvColor(img, cv2.COLOR_RGB2GRAY)
# 5.检查人脸
faces = face.detectMultiScale(gray)
# 6.标记人脸
for (x, y, w, h) in faces:
#里面有四个参数 1，写图片 2，坐标原点 3，识别大小 4，颜色RGB5，线宽
cv2.rectang(img, (x, y), (x + w, y + h), (0, 255, 0), 10)
# 7.创建窗口
cv2.nameWindow('james 窗口')
# 8.显示图片
cv2.imshow('jiaqi', img)
# 9.暂停窗口
cv2.waitKey(0)
# 10.关闭窗口
cv2.destroyAllWindows()
global start_point
global end_point
global canvas
global is_drawing
if event == cv2.EVENT_LBUTTONDOWN:
if is_drawing:
start_point(x,y)
elif event == cv2.EVENT_MOUSEMOVE:
if is_drawing
end_point = (x,y)
draw_line(canvas,start_point,end_point)
start_point = end_point
elif event == cv2.EVENT_LBUTTONUP
is_drawing = False
cv2.nameWindow(wname)
cv2.setMouseCallback(wname, shape)
while True:
cv2.imshow(wname, canvas)
key = cv2.waitKey(1) # press any keyto go to next state
if key == ord('q'):
break
elif key == ord('c'):
canvas[50:350, 50:350] = 0
elif key == ord('w'):
out = canvas[100:500, 100:500]
result = net.predict(image)
print("PREDICTION :", result)
#intent :摄像头识别人脸
#Author :Michael Jack hu
#start date : 2018/10/8
#File : 人脸识别4.py
#Software : PyCharm
#finish date :
'''
# 1.导入库
import cv2
# 2.加载人脸模型
cv2.CascadeClassifiler()
# 3.打开摄像头
capture = cv2.VideoCapture(0)
# 4.创建窗口
cv2.nameWindow()
# 5.获取摄像头实时画面
cv2.nameWindow('she xiang tou')
while True:
#获取摄像头的帧画面
ret, frame = capture.read()
# 图片灰度调整
gary = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
#检查人脸
faces = face.detecMultiScale(gary, 1.1, 3, 0 (100, 100))
#标记人脸
for (x, y, w, h) in faces:
# 里面有四个参数 1，写图片 2，坐标原点 3，识别大小 4，颜色RGB5，线宽
cv2.rectang(frame, (x, y), (x + w, y + h), (0, 255, 0), 10)
#显示图片
cv2.imshow('shexiangtou', frame)
def original():
cv2.nameWindow("Original Image")
cv2.imshow("Orignal Image", pic)
from PIL import Image
import pytesseract
import cv2
img = cv2.imread('plate1.png')
tex = pytesseract.image_to_string(Image.open('plate1.png'), lang='ben')
print(pytesseract.image_to_string(Image.open('plate1.png'), lang='ben'))
cv2.nameWindow('Input image')
cv2.imshow("Input image", img)
cv2.waitkey(0)
cv2.destroyWindow("Test")
cv2.destroyWindow("Main")
import cv2
import numpy as np
cv2.nameWindow("gray")
img = np.zeros((512, 512), np.uint8) #生成一张空的灰度图像
cv2.line(img, (0, 0), (511, 511), 255, 5) #绘制一条白色直线
cv2.imshow("gray", img) #显示图像
#循环等待，按q键退出
while True:
key = cv2.waitKey(1)
if key == ord("q"):
break
cv2.destoryWindow("gray")
def __init__(self):
self.bridge = cv.bridge.CvBridge()
cv2.nameWindow("window",1)
self.image_sub = rospy.Subscriber("camera/rgb/image_raw",Image,self.image_callback)
import numpy as np
img = cv2.imread(
"C:\Users\Xiaoxi Chen\Downloads\OpenCV_Preperation\OpenCV_homework\Test_image\baboon.jpg"
)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.iwrite(
"C:\Users\Xiaoxi Chen\Downloads\OpenCV_Preperation\OpenCV_homework\Test_image\baboon.jpg",
gray)
#gray
threshold_type = 2
threshold_value = 128
ret, dst = cv2.threshold(gray, threshold_value, 255, cv2.TRESH_TRUNC)
cv2.imshow("threshold", dst)
cv2.nameWindow("threshold image")
#binary threshold
current_threshold = 128
max_threshold = 255
ret, thre = cv2.threshold(gray, current_threshold, max_threshold,
cv2.THRESH_BINARY)
cv2.imshow("binary threshold", thre)
cv2.nameWindow("binary threshold")
#band thresholding
threshold1 = 27
threshold2 = 125
ret, bin1 = cv2.thresold(gray, threshold1, 255, cv2.THRESH_BINARY)
ret, bin2 = cv2.thresold(gray, threshold2, 255, cv2.THRESH_BINARY_INV)
band_thre_img = np.bitwise_and(bin1, bin2)
# -*- coding: utf-8 -*-
"""
Created on Sat Jul 11 23:18:29 2020
@author: ZYD
"""
"""
【学习内容】
学习使用cv.getTrackbarPos(), cv.createTrackbar。
了解将滑动条固定到openCV窗口。
【代码内容】
在GUI中使用滑动条自定义的RGB颜色。
"""
import cv2 as cv
import numpy as np
def nothing(x):
pass
img = np.zeros((300,512,3), np.uint8) #创建黑色图像
cv.nameWindow('image') #创建窗口
#创建颜色变化的滑动条
cv.createTrackbar('R', 'image', 0, 255, nothing)
cv.createTrackbar('G', 'image', 0, 255, nothing)
cv.createTrackbar('B', 'image', 0, 255, nothing)
import cv2
import numpy as np
x,y,z=200,200,-1
cap= cv2.VideoCapture(0)
def take_inp(event, x1,y1,flag,param):
gloabal x,y,k
if event == cv2.EVENT_LBUTTONDOWN:
x=x1
y=y1
k=1
cv2.nameWindow("enter_point")
cv2
# -- coding: utf-8 --
import numpy as np
import cv2
from matplotlib import pyplot as plt # python绘图库
# 读入图像
# Load an color image in grayscale
img = cv2.imread('../test0.png', 0)
# 事先创建一个window，可调整大小
cv2.nameWindow('image', cv2.WINDOW_NORMAL)
# 显示图像
cv2.imshow('image', img)
# cv2.waiKey(0)
k = cv2.waitKey(0)
if k == 27: # wait for ESC key to exit
cv2.destroyAllWindows() # 删除所有窗口，删除自定窗口使用cv2.destroyWindow(windowname)
elif k == ord('s') # wait for 's' key to save and exit
cv2.imwrite('test0Gray.png', img) # 保存图像
cv2.destroyAllWindows()
# 使用matplotlib
img = cv2.imread('test0.png', 0)
plt.imshow(img, cmap = 'gray', interpolation = 'bicubic')
plt.xticks([]), plt.yticks([]), # to hide tick values on X and Y axis
plt.show()
if not depth_frame or not color_frame:
continue
depth_image = np.asanyarray(depth_frame.get_data())
color_image = np.asanyarray(color_frame.get_data())
depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image,alph=0.03),cv2.COLORMAP_JET)
face_cascade = cv2.CascadeClassifier('/home/isp/Desktop/opencv-master/data/haarcascades/haarcascade_frontalface_default.xml')
gray = cv2.cvtColor(color_image,cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray,scaleFactor=1.2,minNeighbor=5,minsize=(50,50))
for (x,y,w,h) in faces:
cv2.rectangle(color_image,(x,y-5),(x+w,y+h),(255,0,0),2)
text_depth = "depth is "+str(np.round(depth_frame.get_distance(int (x+(1/2)*w),int (y+(1/2)*h)),3)+"m")
color_image=cv2.putText(color_image,text_depth,(x,y-5),cv2.FONT_HERSHEY_PLAIN,1,(0.0.255),1,cv2.LINE_AA)
images = np.hstack((color_image,depthcolormap))
cv2.nameWindow('Realsense',cv2.WINDOW_AUTOSIZE)
cv2.imshow('Realsense',images)
key = cv2.waitKey(1)
if Key & 0xFF == ord('q') or Key == 27:
cv2.destroyAllWindows()
break
finally:
pipeline.stop()
import cv2
import numpy as np
events = [i for i in dir(cv2) if 'EVENT' in i]
print events
# mouse callback function
def draw_circle(event, x, y, flags, param):
if event == cv2.EVENT_LBUTTONDBLCLK:
cv2.circle(img, (x,y), 100, (255, 0, 0), -1)
#window with a black pic
img = np.zeros((512, 512, 3), np.unit8)
cv2.nameWindow('image')
cv2.setMouseCallback
# -*- coding: utf-8 -*-
'''
#intent :人脸识别
#Author :Michael Jack hu
#start date : 2018/10/8
#File : 人脸识别.py
#Software : PyCharm
#finish date :
'''
#
#1. 导入库
import cv2
font = cv2.FONT_HERSHEY_SIMPLEX
#2. 加载图片
img = cv2.imread('C\huzhi\Desktop\04.jpg')
#3. 创建窗口
cv2.nameWindow('james')
#4. 显示图片
cv2.imshow('jiaqi', img)
#5. 暂停窗口
cv2.waitKey(0)
#6. 关闭窗口
cv2.destroyAllWindows()
import cv2
import numpy as np
img = cv2.imread("C:\Users\Xiaoxi Chen\Downloads\OpenCV_Preperation\OpenCV_homework\Test_images\Lenna")
cv2.nameWindow("Lenna")
cv2.imshow("Lenna", img)
#show RGB
r,g,b = cv2.split(img)
cv2.imshow('Original Image', img)
cv2.imshow('Red', r)
cv2.imwrite('Red.png', r)
cv2.imshow('Green', g)
cv2.imwrite('Green.png', g)
cv2.imshow('Blue', b)
cv2.imwrite('Blue.png', b)
rgbPixel = img[20,25]
print rgbPixel
#YCC
imgYCC = cv2.cvtColor(img, cv2.COLOR_RGB2YCrCb)
Y,Cb,Cr = cv2.split(ycrcb_image)
cv2.imshow('Y', y)
cv2.imwrite('Y.png', y)
cv2.imshow('Cr', cr)
cv2.imwrite('Cr.png', cr)
cv2.imshow('Cb', cb)
cv2.imwrite('Cb.png', cb)
ycrcbPixel = imgYCC[20,25]
print ycrcbPixel
import cv2
import numpy as np
from math import tan,pi
pipe=rs.pipeline()
cfg=rs.config()
cfg.enable_stream(rs.stream.pose)
pipe.start(cfg)
try:
WINDOW_TITLE='Realsense'
cv2.nameWindow(WINDOW_TITLE,cv2.WINDOW_NORMAL)
window_size=5
min_disp=0
num_disp=112-min_disp
max_disp=min_disp+num_disp
stereo = cv2.StereoSGBM_create(minDisparity = min_disp,
numDisparities = num_disp,
blockSize = 16,
P1 = 8*3*window_size**2,
P2 = 32*3*window_size**2,
disp12MaxDiff = 1,
uniquenessRatio = 10,
speckleWindowSize = 100,
import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('messi5.jpg', 0)
plt.imshow(img, cmap='gray', interpolation='bicubic')
plt.xticks([]), plt.yticks([])
plt.show()
"""
cv2.nameWindow('image',cv2.WINDOW_NORMAL)
cv2.imshow('inamge',img)
cv2.waitKey(0)
cv2.destroyAllWindows()
"""
