《OpenCV图像处理（Python）》网课笔记（从5到8）

5. image arithmetics and logic （图像算术和逻辑）

# coding: utf-8

# In[10]:


#lesson5


# In[11]:


import cv2
import numpy as np


# In[12]:


img1 = cv2.imread('3D-Matplotlib.png')
img2 = cv2.imread('mainsvmimage.png')


# In[14]:


# add = img1 + img2
# add = cv2.add(img1//2,img2//2)
weighted = cv2. addWeighted(img1,0.6,img2,0.4,0)

cv2.imwrite('lesson5-weighted.png',weighted)

cv2.imshow('weighted',weighted)
cv2.waitKey(0)
cv2.destroyAllWindows()


# In[15]:


img3 = cv2.imread('mainlogo.png')


# In[16]:


rows,cols,channels = img3.shape
roi = img1[0:rows,0:cols]

img3gray = cv2.cvtColor(img3,cv2.COLOR_BGR2GRAY)
ret, mask = cv2.threshold(img3gray,220,255,cv2.THRESH_BINARY_INV)


# In[17]:


mask_inv = cv2.bitwise_not(mask)

img1_bg = cv2.bitwise_and(roi,roi,mask = mask_inv)
img3_fg = cv2.bitwise_and(img3,img3,mask = mask)


# In[18]:


dst = cv2.add(img1_bg,img3_fg)
img1[0:rows,0:cols] = dst


# In[19]:


cv2.imshow('res',img1)
cv2.imshow('mask_inv',mask_inv)
cv2.imshow('img1_bg',img1_bg)
cv2.imshow('img3_fg',img3_fg)
cv2.imshow('dst',dst)


# In[20]:


# cv2.imshow('mask',mask)
cv2.imwrite('lesson5-dst.png',dst)
cv2.waitKey(0)
cv2.destroyAllWindows()

其中输入里面，

3D-Matplotlib.png

mainsvmimage.png

mainlogo.png

 

输出结果里面

 

6. thresholding(阈值）

代码部分

# coding: utf-8

# In[5]:


#leeson6


# In[13]:


import cv2
import numpy as np


# In[14]:


img = cv2.imread('bookpage.jpg')
retval, threshold = cv2.threshold(img,12,255,cv2.THRESH_BINARY)


# In[15]:


grayscaled = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
retval2, threshold2 = cv2.threshold(grayscaled,12,255,cv2.THRESH_BINARY)


# In[16]:


gaus = cv2.adaptiveThreshold(grayscaled,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,115,1)


# In[18]:


cv2.imwrite('lesson6-original.png',img)
cv2.imwrite('lesson6-threshold.png',threshold)
cv2.imwrite('lesson6-threshold2.png',threshold2)
cv2.imwrite('lesson6-gaus.png',gaus)


# In[19]:


cv2.imshow('original',img)
cv2.imshow('threshold',threshold)
cv2.imshow('threshold2',threshold2)
cv2.imshow('gaus',gaus)
cv2.waitKey(0)
cv2.destroyAllWindows()

lesson6-original.png

lesson6-threshold.png

lesson6-threshold2.png

lesson6-gaus.png

7. Color Filtering（颜色过滤器）

代码

# coding: utf-8

# In[1]:


#lesson7


# In[2]:


import cv2
import numpy as np


# In[3]:


cap = cv2.VideoCapture(0)


# In[4]:


while True:
    _, frame = cap.read()
    hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
    
    lower_red = np.array([50,0,0])
    upper_red = np.array([255,255,255])
    
    #Evidently, here mask is the same as hsv
    mask = cv2.inRange(hsv,lower_red,upper_red)
    res = cv2.bitwise_and(frame,frame,mask = mask)
    
    cv2.imshow('frame',frame)
    cv2.imshow('mask',mask)
    cv2.imshow('res',res)
    
    if cv2.waitKey(2) & 0xFF == ord('q'):
        break

cv2.destroyAllWindows()
cap.release()
    

    
    

8. Blurring and Smoothing (模糊和光滑）

代码

# coding: utf-8

# In[1]:


#lesson8


# In[19]:


import cv2
import numpy as np


# In[22]:


cap = cv2.VideoCapture(0)


# In[23]:


while True:
    _, frame = cap.read()
    hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
    
    lower_red = np.array([50,0,0])
    upper_red = np.array([255,255,255])
    
    #Evidently, here mask is the same as hsv
    mask = cv2.inRange(hsv,lower_red,upper_red)
    res = cv2.bitwise_and(frame,frame,mask = mask)
    
    kernel = np.ones((15,15),np.float32)/225
    smoothed = cv2.filter2D(res,-1,kernel)
    
    blur = cv2.GaussianBlur(res,(15,15),0)
    median = cv2.medianBlur(res,15)
    bilateral = cv2.bilateralFilter(res,15,75,75)
    
    cv2.imshow('frame',frame)
#     cv2.imshow('mask',mask)
    cv2.imshow('res',res)
    cv2.imshow('blur',blur)
    cv2.imshow('median',median)
    cv2.imshow('bilateral',bilateral)
    
    if cv2.waitKey(3) & 0xFF == ord('q'):
        break

cv2.destroyAllWindows()
cap.release()