import cv2
import numpy as np
def mycvshow(imagein, title='Image'): #title can be specified or left to the default
cv2.imshow(title,imagein)
cv2.waitKey()
#cv2.destroyWindow(title)
img_gray=cv2.imread('cat.jpg',0)
big_picture=np.zeros((img_gray.shape[0]+1000,img_gray.shape[1]+1000))
big_picture[0:img_gray.shape[0],0:img_gray.shape[1]]=img_gray
mycvshow(big_picture)
The above is my code. I read in an image in grayscale and then put it in a large matrix of zeros. I expect it to return a picture of a cat with a black background but it just breaks the mycvshow function and shows an almost completely white picture of the cat on a black background and window displaying the image seems to have problems too. Everything goes perfectly if i just write mycvshow(img_gray).
Related
To set this up, I used svgwrite library to create a sample SVG image (20 squares of length 100 at random locations on a display size of length 400)
import svgwrite
import random
random.seed(42)
dwg = svgwrite.Drawing('x.svg', size=(400,400))
dwg.add(dwg.rect(insert=(0,0), size=('100%', '100%'), fill='white')) # White background
for i in range(20):
coordinates = (random.randint(0,399), random.randint(0,399))
color = (random.randint(0,255), random.randint(0,255), random.randint(0,255))
dwg.add(dwg.rect(coordinates, (100, 100),
stroke='black',
fill=svgwrite.rgb(*color),
stroke_width=1)
)
dwg.save()
I then wrote a sample pygame program to generate a PNG image of the same sample. (A seed has been used to generate the same sequence of squares.)
import pygame
import random
random.seed(42)
display = pygame.display.set_mode((400,400))
display.fill((255,255,255)) # White background
for i in range(20):
coordinates = (random.randint(0,399), random.randint(0,399))
color = (random.randint(0,255), random.randint(0,255), random.randint(0,255))
pygame.draw.rect(display, color, coordinates+(100,100), 0)
pygame.draw.rect(display, (0,0,0), coordinates+(100,100), 1) #For black border
pygame.image.save(display, "x.png")
These are the images that I got (SVG's can't be uploaded to SO, so I have provided a screenshot. Nevertheless, the programs above can be run to output the same).
My question is, why is the PNG (on the left) richer and sharper than the corresponding SVG image? The SVG looks blurred and bland, comparatively.
EDIT: One can notice the fine white line between the first two squares at the top-left corner. It's not very clear in the SVG.
Two things I think may impact:
You are using an image viewer, which could distort the vectorial SVG image. I think all of the vector images viewers get the actual screen size, then export the vectorial image into a matrix image sized in function of the size of the screen you have. Then they display the matrix image. If they render the image with softened sharpness, or if they have a problem by getting the size of your screen, the image may be blurred.
To make the PNG image, you use pygame. But you are using another module to make the SVG image. This module may function differently, and also exports the image with another quality than if you were exporting it with pygame.
For me personally the SVG image appears blurred with Gimp, for example, but not with another SVG viewer.
So I think the problem comes from your image viewer.
Now I have an image that contains some text and it has a colored background , I want to extract it using tesseract but first i want to replace the colored background with white one and make the text itself black to increase the accuracy of detection process .
i was trying to use Canny Detection
import cv2
import numpy as np
image=cv2.imread('tt.png')
cv2.imshow('input image',image)
cv2.waitKey(0)
gray=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
edged=cv2.Canny(gray,30,200)
edged = cv2.bitwise_not(edged)
cv2.imshow('canny edges',edged)
cv2.waitKey(0)
that worked fine to replace the colored background with white but made the text's color white with black outlines (check the below images) .
so is there any way to make the whole text colored black ?
or
is there another way i can use to make that ?
before Canny detection
after Canny detection
Edit
the image may has mixed background colors like
input image
You should simply do it by using THRESH_BINARY_INV, it is the code:
cv::namedWindow("Original_Image", cv::WINDOW_FREERATIO);
cv::namedWindow("Result", cv::WINDOW_FREERATIO);
cv::Mat originalImg = cv::imread("BCQqn.png");
cv::Mat gray;
cv::cvtColor(originalImg, gray, cv::COLOR_BGR2GRAY);
cv::threshold(gray, gray, 130, 255, cv::THRESH_BINARY_INV);
cv::imshow("Original_Image", originalImg);
cv::imshow("Result", gray);
cv::waitKey();
And it is the result:
You can play with the threshold value (130 in the above example).
Note: The code is in C++, if you are using Python, then you can go the same steps, and is that.
Good Luck!!
I have multiple pictures, each of which has an object with its background removed. The pictures are 500x400 pixels in size.
I am looking for a way to programmatically (preferably using python) calculate the total number of pixels of the image inside the picture (inside the space without the background).
I used the PIL package in Python to get the dimensions of the image object, as follows:
print(image.size)
This command successfully produced the dimensions of the entire picture (500x400 pixels) but not the dimensions of the object of interest inside the picture.
Does anyone know how to calculate the dimensions of an object inside a picture using python? An example of a picture is embedded below.
You could floodfill the background pixels with some colour not present in the image, e.g. magenta, then count the magenta pixels and subtract that number from number of pixels in image (width x height).
Here is an example:
#!/usr/bin/env python3
from PIL import Image, ImageDraw
import numpy as np
# Open the image and ensure RGB
im = Image.open('man.png').convert('RGB')
# Make all background pixels magenta
ImageDraw.floodfill(im,xy=(0,0),value=(255,0,255),thresh=50)
# Save for checking
im.save('floodfilled.png')
# Make into Numpy array
n = np.array(im)
# Mask of magenta background pixels
bgMask =(n[:, :, 0:3] == [255,0,255]).all(2)
count = np.count_nonzero(bgMask)
# Report results
print(f"Background pixels: {count} of {im.width*im.height} total")
Sample Output
Background pixels: 148259 of 199600 total
Not sure how important the enclosed areas between arms and body are to you... if you just replace all greys without using the flood-filling technique, you risk making, say, the shirt magenta and counting that as background.
I am processing an image with OpenCV on Python and I want to count every objects (worms) on it. Worms are rather light beige whereas the background is black (see picture) so it is rather easy to distinguish them. The problem is that sometimes worms are too close to each other (sometimes they even overlap) and cv.findContours() will draw one big contour instead of two smaller ones (see picture below).
Because I am using cv.foundContours(), I have to first turn the picture into black and white, then blur it (optional) and finally threshold it in order to have white worms in a black background.
I am using the following code :
import cv2 as cv
img = cv.imread('worms.jpg')
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
blur=cv.GaussianBlur(gray,(5,5),1)
ret,osu = cv.threshold(blur,0,255,cv.THRESH_BINARY+cv.THRESH_OTSU)
imsource,contours,test = cv.findContours(osu,1,1)
cv.drawContours(img,contours,-1, (0,0,255),2)
I tried to erode the thresholded picture but it doesn't work well since the "bond" between two worms is quite big.
Thanks for the help
My application was recently working fine, but when I upgraded Python to v3.7.2, which solved another problem I was having, the images are either no longer shown or of poor quality.
After doing some testing, I've concluded that I can display any PNG without transparency, but PNGs with transparency exhibit this problem. I can recreate it with this code:
import tkinter as tk
from PIL import Image, ImageTk
root = tk.Tk()
path = 'png-transparent.png'
img = Image.open(path)
imgtk = ImageTk.PhotoImage(img)
panel = tk.Label(root, image=imgtk).pack()
root.mainloop()
If I use a label to display the image, it doesn't show at all. If I use a button to display the image, which is what I really need to do, it is poor quality (which means not displaying properly, no definition, coarse edges).
They are very small (16x16), but you can see two different icons here, the ones in the boxes are the distorted ones and the ones not in boxes are how they are supposed to look.
Current versions: Python 3.7.2, Pillow 5.4.1, OS X 10.13.6