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-rw-r--r--de-de/opencv-de.html.markdown93
-rw-r--r--opencv.html.markdown69
-rw-r--r--zh-cn/opencv-cn.html.markdown88
3 files changed, 126 insertions, 124 deletions
diff --git a/de-de/opencv-de.html.markdown b/de-de/opencv-de.html.markdown
index a2b55439..c39e5a65 100644
--- a/de-de/opencv-de.html.markdown
+++ b/de-de/opencv-de.html.markdown
@@ -8,11 +8,10 @@ translators:
- ["Dennis Keller", "https://github.com/denniskeller"]
lang: de-de
---
-### OpenCV
-OpenCV (Open Source Computer Vision) ist eine Bibliothek von Programmierfunktionen,
+OpenCV (Open Source Computer Vision) ist eine Bibliothek von Programmierfunktionen,
die hauptsächlich auf maschinelles Sehen in Echtzeit ausgerichtet ist.
-Ursprünglich wurde OpenCV von Intel entwickelt. Später wurde es von
+Ursprünglich wurde OpenCV von Intel entwickelt. Später wurde es von
Willow Garage und dann Itseez (das später von Intel übernommen wurde) unterstützt.
OpenCV unterstützt derzeit eine Vielzahl von Sprachen, wie C++, Python, Java uvm.
@@ -20,9 +19,9 @@ OpenCV unterstützt derzeit eine Vielzahl von Sprachen, wie C++, Python, Java uv
Bitte lies diesen Artikel für die Installation von OpenCV auf deinem Computer.
-* Windows Installationsanleitung: [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html#install-opencv-python-in-windows]()
-* Mac Installationsanleitung (High Sierra): [https://medium.com/@nuwanprabhath/installing-opencv-in-macos-high-sierra-for-python-3-89c79f0a246a]()
-* Linux Installationsanleitung (Ubuntu 18.04): [https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv]()
+* [Windows Installationsanleitung](https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html#install-opencv-python-in-windows)
+* [Mac Installationsanleitung](https://medium.com/@nuwanprabhath/installing-opencv-in-macos-high-sierra-for-python-3-89c79f0a246a) (High Sierra)
+* [Linux Installationsanleitung](https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv) (Ubuntu 18.04)
### Hier werden wir uns auf die Pythonimplementierung von OpenCV konzentrieren.
@@ -33,16 +32,16 @@ img = cv2.imread('Katze.jpg')
# Bild darstellen
# Die imshow() Funktion wird verwendet um das Display darzustellen.
-cv2.imshow('Image',img)
+cv2.imshow('Image', img)
# Das erste Argument ist der Titel des Fensters und der zweite Parameter ist das Bild
# Wenn du den Fehler Object Type None bekommst, ist eventuell dein Bildpfad falsch.
# Bitte überprüfe dann den Pfad des Bildes erneut.
cv2.waitKey(0)
-# waitKey() ist eine Tastaturbindungsfunktion, sie nimmt Argumente in
+# waitKey() ist eine Tastaturbindungsfunktion, sie nimmt Argumente in
# Millisekunden an. Für GUI Ereignisse MUSST du die waitKey() Funktion verwenden.
# Ein Bild schreiben
-cv2.imwrite('graueKatze.png',img)
+cv2.imwrite('graueKatze.png', img)
# Das erste Argument ist der Dateiname und das zweite ist das Bild
# Konvertiert das Bild zu Graustufen
@@ -51,10 +50,10 @@ gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Videoaufnahme von der Webcam
cap = cv2.VideoCapture(0)
# 0 ist deine Kamera, wenn du mehrere Kameras hast musst du deren Id eingeben
-while(True):
+while True:
# Erfassen von Einzelbildern
_, frame = cap.read()
- cv2.imshow('Frame',frame)
+ cv2.imshow('Frame', frame)
# Wenn der Benutzer q drückt -> beenden
if cv2.waitKey(1) & 0xFF == ord('q'):
break
@@ -63,59 +62,60 @@ cap.release()
# Wiedergabe von Videos aus einer Datei
cap = cv2.VideoCapture('film.mp4')
-while(cap.isOpened()):
+while cap.isOpened():
_, frame = cap.read()
# Das Video in Graustufen abspielen
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
- cv2.imshow('frame',gray)
+ cv2.imshow('frame', gray)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
# Zeichne eine Linie in OpenCV
-# cv2.line(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)
-cv2.line(img,(0,0),(511,511),(255,0,0),5)
+# cv2.line(img, (x,y), (x1,y1), (color->r,g,b->0 to 255), thickness)
+cv2.line(img, (0, 0), (511, 511), (255, 0, 0), 5)
# Zeichne ein Rechteck
-# cv2.rectangle(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)
+# cv2.rectangle(img, (x,y), (x1,y1), (color->r,g,b->0 to 255), thickness)
# thickness = -1 wird zum Füllen des Rechtecks verwendet
-cv2.rectangle(img,(384,0),(510,128),(0,255,0),3)
+cv2.rectangle(img, (384, 0), (510, 128), (0, 255, 0), 3)
# Zeichne ein Kreis
-cv2.circle(img,(xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness)
-cv2.circle(img,(200,90), 100, (0,0,255), -1)
+# cv2.circle(img, (xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness)
+cv2.circle(img, (200, 90), 100, (0, 0, 255), -1)
# Zeichne eine Ellipse
-cv2.ellipse(img,(256,256),(100,50),0,0,180,255,-1)
+cv2.ellipse(img, (256, 256), (100, 50), 0, 0, 180, 255, -1)
# Text auf Bildern hinzufügen
-cv2.putText(img,"Hello World!!!", (x,y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255)
+cv2.putText(img, "Hello World!!!", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255)
# Bilder zusammenfügen
img1 = cv2.imread('Katze.png')
img2 = cv2.imread('openCV.jpg')
-dst = cv2.addWeighted(img1,0.5,img2,0.5,0)
+dst = cv2.addWeighted(img1, 0.5, img2, 0.5, 0)
# Schwellwertbild
# Binäre Schwellenwerte
-_,thresImg = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
-# Anpassbare Schwellenwerte
-adapThres = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,11,2)
+_, thresImg = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)
+# Anpassbare Schwellenwerte
+adapThres = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
# Weichzeichnung von einem Bild
# Gaußscher Weichzeichner
-blur = cv2.GaussianBlur(img,(5,5),0)
+blur = cv2.GaussianBlur(img, (5, 5), 0)
# Rangordnungsfilter
-medianBlur = cv2.medianBlur(img,5)
+medianBlur = cv2.medianBlur(img, 5)
# Canny-Algorithmus
-img = cv2.imread('Katze.jpg',0)
-edges = cv2.Canny(img,100,200)
+img = cv2.imread('Katze.jpg', 0)
+edges = cv2.Canny(img, 100, 200)
# Gesichtserkennung mit Haarkaskaden
# Lade die Haarkaskaden von https://github.com/opencv/opencv/blob/master/data/haarcascades/ herunter
import cv2
import numpy as np
+
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
@@ -123,31 +123,32 @@ img = cv2.imread('Mensch.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
aces = face_cascade.detectMultiScale(gray, 1.3, 5)
-for (x,y,w,h) in faces:
- cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
- roi_gray = gray[y:y+h, x:x+w]
- roi_color = img[y:y+h, x:x+w]
+for x, y, w, h in faces:
+ cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
+ roi_gray = gray[y : y + h, x : x + w]
+ roi_color = img[y : y + h, x : x + w]
eyes = eye_cascade.detectMultiScale(roi_gray)
- for (ex,ey,ew,eh) in eyes:
- cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
+ for ex, ey, ew, eh in eyes:
+ cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
-cv2.imshow('img',img)
+cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
# destroyAllWindows() zerstört alle Fenster
-# Wenn du ein bestimmtes Fenster zerstören möchtest, musst du den genauen Namen des
+# Wenn du ein bestimmtes Fenster zerstören möchtest, musst du den genauen Namen des
# von dir erstellten Fensters übergeben.
```
### Weiterführende Literatur:
-* Lade Kaskade hier herunter [https://github.com/opencv/opencv/blob/master/data/haarcascades]()
-* OpenCV Zeichenfunktionen [https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html]()
-* Eine aktuelle Sprachenreferenz kann hier gefunden werden [https://opencv.org]()
-* Zusätzliche Ressourcen können hier gefunden werden [https://en.wikipedia.org/wiki/OpenCV]()
+
+* Lade Kaskade hier herunter [https://github.com/opencv/opencv/blob/master/data/haarcascades](https://github.com/opencv/opencv/blob/master/data/haarcascades)
+* OpenCV Zeichenfunktionen [https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html](https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html)
+* Eine aktuelle Sprachenreferenz kann hier gefunden werden [https://opencv.org](https://opencv.org)
+* Zusätzliche Ressourcen können hier gefunden werden [https://en.wikipedia.org/wiki/OpenCV](https://en.wikipedia.org/wiki/OpenCV)
* Gute OpenCV Tutorials
- * [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html]()
- * [https://realpython.com/python-opencv-color-spaces]()
- * [https://pyimagesearch.com]()
- * [https://www.learnopencv.com]()
- * [https://docs.opencv.org/master/]()
+ * [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html](https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html)
+ * [https://realpython.com/python-opencv-color-spaces](https://realpython.com/python-opencv-color-spaces)
+ * [https://pyimagesearch.com](https://pyimagesearch.com)
+ * [https://www.learnopencv.com](https://www.learnopencv.com)
+ * [https://docs.opencv.org/master/](https://docs.opencv.org/master/)
diff --git a/opencv.html.markdown b/opencv.html.markdown
index ff91d2a5..9a931bcb 100644
--- a/opencv.html.markdown
+++ b/opencv.html.markdown
@@ -7,9 +7,9 @@ contributors:
---
### Opencv
-OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision.
-Originally developed by Intel, it was later supported by Willow Garage then Itseez (which was later acquired by Intel).
-Opencv currently supports wide variety of languages like, C++, Python, Java etc
+OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision.
+Originally developed by Intel, it was later supported by Willow Garage then Itseez (which was later acquired by Intel).
+OpenCV currently supports wide variety of languages like, C++, Python, Java etc
#### Installation
Please refer to these articles for installation of OpenCV on your computer.
@@ -27,14 +27,14 @@ img = cv2.imread('cat.jpg')
# Displaying the image
# imshow() function is used to display the image
-cv2.imshow('Image',img)
+cv2.imshow('Image', img)
# Your first arguement is the title of the window and second parameter is image
# If you are getting error, Object Type None, your image path may be wrong. Please recheck the pack to the image
cv2.waitKey(0)
# waitKey() is a keyboard binding function and takes arguement in milliseconds. For GUI events you MUST use waitKey() function.
# Writing an image
-cv2.imwrite('catgray.png',img)
+cv2.imwrite('catgray.png', img)
# first arguement is the file name and second is the image
# Convert image to grayscale
@@ -42,11 +42,11 @@ gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Capturing Video from Webcam
cap = cv2.VideoCapture(0)
-#0 is your camera, if you have multiple camera, you need to enter their id
-while(True):
+# 0 is your camera, if you have multiple camera, you need to enter their id
+while True:
# Capturing frame-by-frame
_, frame = cap.read()
- cv2.imshow('Frame',frame)
+ cv2.imshow('Frame', frame)
# When user presses q -> quit
if cv2.waitKey(1) & 0xFF == ord('q'):
break
@@ -55,59 +55,60 @@ cap.release()
# Playing Video from file
cap = cv2.VideoCapture('movie.mp4')
-while(cap.isOpened()):
+while cap.isOpened():
_, frame = cap.read()
# Play the video in grayscale
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
- cv2.imshow('frame',gray)
+ cv2.imshow('frame', gray)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
# Drawing The Line in OpenCV
-# cv2.line(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)
-cv2.line(img,(0,0),(511,511),(255,0,0),5)
+# cv2.line(img, (x,y), (x1,y1), (color->r,g,b->0 to 255), thickness)
+cv2.line(img, (0, 0), (511, 511), (255, 0, 0), 5)
# Drawing Rectangle
-# cv2.rectangle(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)
+# cv2.rectangle(img, (x,y), (x1,y1), (color->r,g,b->0 to 255), thickness)
# thickness = -1 used for filling the rectangle
-cv2.rectangle(img,(384,0),(510,128),(0,255,0),3)
+cv2.rectangle(img, (384, 0), (510, 128), (0, 255, 0), 3)
# Drawing Circle
-cv2.circle(img,(xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness)
-cv2.circle(img,(200,90), 100, (0,0,255), -1)
+# cv2.circle(img, (xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness)
+cv2.circle(img, (200, 90), 100, (0, 0, 255), -1)
# Drawing Ellipse
-cv2.ellipse(img,(256,256),(100,50),0,0,180,255,-1)
+cv2.ellipse(img, (256, 256), (100, 50), 0, 0, 180, 255, -1)
# Adding Text On Images
-cv2.putText(img,"Hello World!!!", (x,y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255)
+cv2.putText(img, "Hello World!!!", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255)
# Blending Images
img1 = cv2.imread('cat.png')
img2 = cv2.imread('openCV.jpg')
-dst = cv2.addWeighted(img1,0.5,img2,0.5,0)
+dst = cv2.addWeighted(img1, 0.5, img2, 0.5, 0)
# Thresholding image
# Binary Thresholding
-_,thresImg = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
+_, thresImg = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)
# Adaptive Thresholding
-adapThres = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,11,2)
+adapThres = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
# Blur Image
# Gaussian Blur
-blur = cv2.GaussianBlur(img,(5,5),0)
+blur = cv2.GaussianBlur(img, (5, 5), 0)
# Median Blur
-medianBlur = cv2.medianBlur(img,5)
+medianBlur = cv2.medianBlur(img, 5)
# Canny Edge Detection
-img = cv2.imread('cat.jpg',0)
-edges = cv2.Canny(img,100,200)
+img = cv2.imread('cat.jpg', 0)
+edges = cv2.Canny(img, 100, 200)
# Face Detection using Haar Cascades
# Download Haar Cascades from https://github.com/opencv/opencv/blob/master/data/haarcascades/
import cv2
import numpy as np
+
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
@@ -115,21 +116,21 @@ img = cv2.imread('human.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
-for (x,y,w,h) in faces:
+for x, y, w, h in faces:
# Draw a rectangle around detected face
- cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
- roi_gray = gray[y:y+h, x:x+w]
- roi_color = img[y:y+h, x:x+w]
+ cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
+ roi_gray = gray[y : y + h, x : x + w]
+ roi_color = img[y : y + h, x : x + w]
eyes = eye_cascade.detectMultiScale(roi_gray)
- for (ex,ey,ew,eh) in eyes:
+ for ex, ey, ew, eh in eyes:
# Draw a rectangle around detected eyes
- cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
+ cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
-cv2.imshow('img',img)
+cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
-# destroyAllWindows() destroys all windows.
+# destroyAllWindows() destroys all windows.
# If you wish to destroy specific window pass the exact name of window you created.
```
@@ -139,7 +140,7 @@ cv2.destroyAllWindows()
* OpenCV drawing Functions [https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html](https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html)
* An up-to-date language reference can be found at [https://opencv.org](https://opencv.org)
* Additional resources may be found at [https://en.wikipedia.org/wiki/OpenCV](https://en.wikipedia.org/wiki/OpenCV)
-* Good OpenCv Tutorials
+* Good OpenCV Tutorials
* [https://realpython.com/python-opencv-color-spaces](https://realpython.com/python-opencv-color-spaces)
* [https://pyimagesearch.com](https://pyimagesearch.com)
* [https://www.learnopencv.com](https://www.learnopencv.com)
diff --git a/zh-cn/opencv-cn.html.markdown b/zh-cn/opencv-cn.html.markdown
index 2932e586..596430f6 100644
--- a/zh-cn/opencv-cn.html.markdown
+++ b/zh-cn/opencv-cn.html.markdown
@@ -8,18 +8,18 @@ translators:
- ["GengchenXU", "https://github.com/GengchenXU"]
lang: zh-cn
---
-### Opencv
-Opencv(开源计算机视觉)是一个编程功能库,主要面向实时计算机视觉。最初由英特尔开发,后来由Willow Garage,然后Itseez(后来被英特尔收购)支持。Opencv 目前支持多种语言,如C++、Python、Java 等
+OpenCV(开源计算机视觉)是一个编程功能库,主要面向实时计算机视觉。最初由英特尔开发,后来由Willow Garage,然后Itseez(后来被英特尔收购)支持。OpenCV 目前支持多种语言,如C++、Python、Java 等
#### 安装
+
有关在计算机上安装 OpenCV,请参阅这些文章。
-* Windows 安装说明: [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html#install-opencv-python-in-windows]()
-* Mac 安装说明 (High Sierra): [https://medium.com/@nuwanprabhath/installing-opencv-in-macos-high-sierra-for-python-3-89c79f0a246a]()
-* Linux 安装说明 (Ubuntu 18.04): [https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv]()
+* [Windows 安装说明](https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html#install-opencv-python-in-windows)
+* [Mac 安装说明](https://medium.com/@nuwanprabhath/installing-opencv-in-macos-high-sierra-for-python-3-89c79f0a246a) (High Sierra)
+* [Linux 安装说明](https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv) (Ubuntu 18.04)
-### 在这里,我们将专注于 OpenCV 的 python 实现
+### 在这里,我们将专注于 OpenCV 的 Python 实现
```python
# OpenCV读取图片
@@ -28,14 +28,14 @@ img = cv2.imread('cat.jpg')
# 显示图片
# imshow() 函数被用来显示图片
-cv2.imshow('Image',img)
+cv2.imshow('Image', img)
# 第一个参数是窗口的标题,第二个参数是image
# 如果你得到错误,对象类型为None,你的图像路径可能是错误的。请重新检查图像包
cv2.waitKey(0)
# waitKey() 是一个键盘绑定函数,参数以毫秒为单位。对于GUI事件,必须使用waitKey()函数。
# 保存图片
-cv2.imwrite('catgray.png',img)
+cv2.imwrite('catgray.png', img)
# 第一个参数是文件名,第二个参数是图像
# 转换图像灰度
@@ -43,11 +43,11 @@ gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 从摄像头捕捉视频
cap = cv2.VideoCapture(0)
-#0 是你的相机,如果你有多台相机,你需要输入他们的id
-while(True):
+# 0 是你的相机,如果你有多台相机,你需要输入他们的id
+while True:
# 一帧一帧地获取
_, frame = cap.read()
- cv2.imshow('Frame',frame)
+ cv2.imshow('Frame', frame)
# 当用户按下q ->退出
if cv2.waitKey(1) & 0xFF == ord('q'):
break
@@ -56,54 +56,54 @@ cap.release()
# 在文件中播放视频
cap = cv2.VideoCapture('movie.mp4')
-while(cap.isOpened()):
+while cap.isOpened():
_, frame = cap.read()
# 灰度播放视频
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
- cv2.imshow('frame',gray)
+ cv2.imshow('frame', gray)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
# 在OpenCV中画线
-# cv2.line(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)(注 color颜色rgb参数 thickness粗细)
-cv2.line(img,(0,0),(511,511),(255,0,0),5)
+# cv2.line(img, (x,y), (x1,y1), (color->r,g,b->0 to 255), thickness)(注 color颜色rgb参数 thickness粗细)
+cv2.line(img, (0, 0), (511, 511), (255, 0, 0), 5)
# 画矩形
-# cv2.rectangle(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)
+# cv2.rectangle(img, (x,y), (x1,y1), (color->r,g,b->0 to 255), thickness)
# 粗细= -1用于填充矩形
-cv2.rectangle(img,(384,0),(510,128),(0,255,0),3)
+cv2.rectangle(img, (384, 0), (510, 128), (0, 255, 0), 3)
# 画圆
-cv2.circle(img,(xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness)
-cv2.circle(img,(200,90), 100, (0,0,255), -1)
+# cv2.circle(img, (xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness)
+cv2.circle(img, (200, 90), 100, (0, 0, 255), -1)
# 画椭圆
-cv2.ellipse(img,(256,256),(100,50),0,0,180,255,-1)
+cv2.ellipse(img, (256, 256), (100, 50), 0, 0, 180, 255, -1)
# 在图像上增加文字
-cv2.putText(img,"Hello World!!!", (x,y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255)
+cv2.putText(img, "Hello World!!!", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255)
# 合成图像
img1 = cv2.imread('cat.png')
img2 = cv2.imread('openCV.jpg')
-dst = cv2.addWeighted(img1,0.5,img2,0.5,0)
+dst = cv2.addWeighted(img1, 0.5, img2, 0.5, 0)
# 阈值图像
# 二进制阈值
-_,thresImg = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
+_, thresImg = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)
# Adaptive Thresholding
-adapThres = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,11,2)
+adapThres = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
# 模糊的形象
# 高斯模糊
-blur = cv2.GaussianBlur(img,(5,5),0)
+blur = cv2.GaussianBlur(img, (5, 5), 0)
# 模糊中值
-medianBlur = cv2.medianBlur(img,5)
+medianBlur = cv2.medianBlur(img, 5)
# Canny 边缘检测
-img = cv2.imread('cat.jpg',0)
-edges = cv2.Canny(img,100,200)
+img = cv2.imread('cat.jpg', 0)
+edges = cv2.Canny(img, 100, 200)
# 用Haar Cascades进行人脸检测
# 下载 Haar Cascades 在 https://github.com/opencv/opencv/blob/master/data/haarcascades/
@@ -116,30 +116,30 @@ img = cv2.imread('human.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
aces = face_cascade.detectMultiScale(gray, 1.3, 5)
-for (x,y,w,h) in faces:
- cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
- roi_gray = gray[y:y+h, x:x+w]
- roi_color = img[y:y+h, x:x+w]
+for x, y, w, h in faces:
+ cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
+ roi_gray = gray[y : y + h, x : x + w]
+ roi_color = img[y : y + h, x : x + w]
eyes = eye_cascade.detectMultiScale(roi_gray)
- for (ex,ey,ew,eh) in eyes:
- cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
+ for ex, ey, ew, eh in eyes:
+ cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
-cv2.imshow('img',img)
+cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
-# destroyAllWindows() destroys all windows.
+# destroyAllWindows() destroys all windows.
# 如果您希望销毁特定窗口,请传递您创建的窗口的确切名称。
```
### 进一步阅读:
-* Download Cascade from [https://github.com/opencv/opencv/blob/master/data/haarcascades]()
-* OpenCV 绘图函数 [https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html]()
-* 最新的语言参考 [https://opencv.org]()
-* 更多的资源 [https://en.wikipedia.org/wiki/OpenCV]()
+* Download Cascade from [https://github.com/opencv/opencv/blob/master/data/haarcascades](https://github.com/opencv/opencv/blob/master/data/haarcascades)
+* OpenCV 绘图函数 [https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html](https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html)
+* 最新的语言参考 [https://opencv.org](https://opencv.org)
+* 更多的资源 [https://en.wikipedia.org/wiki/OpenCV](https://en.wikipedia.org/wiki/OpenCV)
* 优秀的的 OpenCV 教程
- * [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html]()
- * [https://realpython.com/python-opencv-color-spaces]()
- * [https://pyimagesearch.com]()
- * [https://www.learnopencv.com]()
+ * [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html](https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html)
+ * [https://realpython.com/python-opencv-color-spaces](https://realpython.com/python-opencv-color-spaces)
+ * [https://pyimagesearch.com](https://pyimagesearch.com)
+ * [https://www.learnopencv.com](https://www.learnopencv.com)