Python Project : pillow, tesseract, and opencv - Coursera - Python 3 Programming Specialization - University of Michigan

Python Project pillow, tesseract, and opencv.py

'''
author : Jaydatt Patel
Python Project : pillow, tesseract, and opencv  Course on Coursera (University of Michigan)
Week - 3 Project
'''
import zipfile
from PIL import Image, ImageDraw
import pytesseract
import cv2 as cv
import numpy as np
from IPython.display import display
# loading the face detection classifier
face_cascade = cv.CascadeClassifier('readonly/haarcascade_frontalface_default.xml')

def search(search_text,path):
    
    
    # extraxt all images from zip
    z = zipfile.ZipFile(path, mode="r")
    images_list = z.namelist()
    save_path = path.replace('.zip','/')
    z.extractall(save_path)
    z.close()
    
    # create Global_list of {file_name : image text,...}
    Global_list = {}
    for image_name in images_list:
        file_name= save_path + image_name
        img = Image.open(file_name)
        text = pytesseract.image_to_string(img)
        text = text.replace("\n"," ").replace("  "," ")
        Global_list[file_name] = text
  
    for file_name in Global_list:
        
        try:
            # now check search_text in text of image file
            if(Global_list[file_name].find(search_text) >= 0):
            
                print('Results found in file',file_name)
            
                # now find cordinates of faces in image.
                img = cv.imread(file_name)
                gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) # convert image RGB to gray
                faces_cordinates = face_cascade.detectMultiScale(gray,1.35,4) # array([x,y,wid,hgt])
                
                # now check how many faces detected, otherwise error will occur for some functions. 
                if (len(faces_cordinates) > 0) :
                
                    #pil_img = Image.fromarray(img)
                    #drawing = ImageDraw.Draw(pil_img) 
            
                    # now crop all faces from images as per faces coordinates
                    img = Image.open(file_name)
                    faces_img = []
                    for x,y,w,h in faces_cordinates:
                        faces_img.append(img.crop((x,y,x+w,y+h)))
                        #drawing.rectangle((x,y,x+w,y+h), outline="red")
                    #display(pil_img)    
            
                    # thumbnail to convert into small image (100x100)(w x h)
                    thum_size = 100
                    for img in faces_img:                
                        img.thumbnail((thum_size,thum_size)) # thumbnail to convert into small image (100x100)(w x h)
                    
                    # now creating base contact sheet as total images and max-5 image in single row then paste all images.
                    contact_sheet = Image.new(img.mode, ((5*thum_size),(thum_size * int(np.ceil(len(faces_img)/5)))))
                    x = 0
                    y = 0
                    for img in faces_img:                
                        contact_sheet.paste(img, (x, y))  
                        if(contact_sheet.width == x+thum_size):
                            x = 0
                            y += thum_size
                        else:
                            x += thum_size
                    display(contact_sheet)
                else:
                    print('But there were no faces in that file!',file_name) 
        except Exception as err:
            print('Error :',err) 
            
search('Christopher',"readonly/small_img.zip")
search('Mark',"readonly/images.zip")

Week-1 assignment.py

'''
author : Jaydatt Patel
Python Project : pillow, tesseract, and opencv  Course on Coursera (University of Michigan)
Week - 1 Project
'''
import PIL
from PIL import Image
from PIL import ImageEnhance
from PIL import ImageDraw
from PIL import ImageFont
# read image and convert to RGB
image=Image.open("readonly/msi_recruitment.gif")
image=image.convert('RGB')
font=ImageFont.truetype(r'readonly/fanwood-webfont.ttf', 70)
# build a list of 9 images which have different brightnesses
newimage=PIL.Image.new(image.mode, (image.width, image.height+70))
newimage.paste(image, (0,0))
images=[]
for i in range(1,10):
    if i%3==1:
        intensity=0.1
    elif i%3==2:
        intensity=0.5
    elif i%3==0:
        intensity=0.9
    if i<=3:
        channel=0
    elif i<=6:
        channel=1
    else:
        channel=2
   
    new_image=newimage.copy()
    text="channel {} intensity {}".format(channel, intensity)
    ImageDraw.Draw(new_image).text((0, new_image.height-70), text, font=font, align='left')
    r,g,b=new_image.split()
    if channel==0:
        r=r.point(lambda x: x*intensity)
    elif channel==1:
        g=g.point(lambda x: x*intensity)
    elif channel==2:
        b=b.point(lambda x: x*intensity)
    result=Image.merge('RGB', (r,g,b))
    images.append(result)
       
   
# create a contact sheet from different brightnesses
first_image=images[0]
contact_sheet=PIL.Image.new(first_image.mode, (first_image.width*3,first_image.height*3))
x=0
y=0
for img in images:
    # Lets paste the current image into the contact sheet
    contact_sheet.paste(img, (x, y) )
    # Now we update our X position. If it is going to be the width of the image, then we set it to 0
    # and update Y as well to point to the next "line" of the contact sheet.
    if x+first_image.width == contact_sheet.width:
        x=0
        y=y+first_image.height
    else:
        x=x+first_image.width
# resize and display the contact sheet
contact_sheet = contact_sheet.resize((int(contact_sheet.width/2),int(contact_sheet.height/2) ))
display(contact_sheet)