I came across the following code:
import cv2
image = cv2.imread('xyz.jpg')
(h, w) = image.shape[:2]
# compute the center of the image
(cX, cY) = (w / 2, h / 2)
region = image[0:cY, 0:cX]
How can we read this part image[0:cY, 0:cX]? I tried printing out the result, but got an array printed out that couldn't help me understand the idea.
So, for instance, let's say that the center of the image was (50,50), how would region be defined in this case?
Thanks.
Related
I am currently working on a small project, but I have an unresolved problem. That is I want to draw a shape through the desired objects , The first thing is to determine the coordinates of the starting and ending points but I don't have a specific idea yet but I don't know how to do it,I hope you can give me suggestions, Glad to have your help.
i want the result in like this
Here is an example using opencv you can draw rectangle over an object:
By giving the template image of the source image you can draw the shape over the image
# importing needed libraries
import cv2
import numpy as np
img_rgb = cv2.imread(source image) # opening the source image
img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY) # converting to the gray scale
template = cv2.imread(template image,0) # opening the template image
w, h = template.shape[::-1] # giving the sape of template image
res = cv2.matchTemplate(img_gray,template,cv2.TM_CCOEFF_NORMED) # matching both the image using the opencv methods for matching object
threshold = 0.9
loc = np.where( res >= threshold)
for pt in zip(*loc[::-1]):
cv2.rectangle(img_rgb, pt, (pt[0] + w, pt[1] + h), (0,0,255), 1)
cv2.imshow('screen',img_rgb)
cv2.waitKey(0)
Source Image
Template Image
Result Image
I am writing a telegram bot that, when receiving an image based on text, would set the correct orientation of the picture. I wrote a function for rotation, the code is attached, I used tesseract, but the bot regularly throws an error if psm = 0 or invalid resolution is not specified, if psm = 3, [Errno 2] no such file in directory: ...\tess_*****.osd. Considering that the only place where osd is used is the rotation function, I think the error is somewhere here, how do I fix it?
def rotate(image, center=None, scale=1.0):
config = '--psm 3 -c min_characters_to_try=1'
angle = 360 - int(re.search('(?<=Rotate: )\d+', pytesseract.image_to_osd(image, config=config)).group(0))
(h, w) = image.shape[:2]
if center is None:
center = (w / 2, h / 2)
matrix = cv2.getRotationMatrix2D(center, angle, scale)
return cv2.warpAffine(image, matrix, (w, h))
I would like to be able to make a certain shape in either a PIL image or an OpenCV image 3 times larger and smaller without changing the resolution of the image or changing the shape of the shape I want to make larger. I have tried using OpenCV's dilation method but that is not it's intended use, plus it changed the shape of the image. For an example:
Thanks.
Here's a way of doing it:
find the interesting shape, i.e. non-white ROI area
extract it
scale it up by a factor
clear the original image to white
paste the scaled ROI back into image with same centre
#!/usr/bin/env python3
import cv2
import numpy as np
if __name__ == "__main__":
# Open image
orig = cv2.imread('image.png',cv2.IMREAD_COLOR)
# Get extent of interesting part, i.e. non-white part
y, x, _ = np.nonzero(~orig)
y0, y1 = np.min(y), np.max(y) # top and bottom rows
x0, x1 = np.min(x), np.max(x) # left and right cols
h, w = y1-y0, x1-x0 # height and width
ROI = orig[y0:y1, x0:x1] # extract ROI
cv2.imwrite('ROI.png', ROI) # DEBUG only
# Upscale ROI
factor = 3
scaledROI = cv2.resize(ROI, (w*factor,h*factor), interpolation=cv2.INTER_NEAREST)
newH, newW = scaledROI.shape[:2]
# Clear original image to white
orig[:] = [255,255,255]
# Get centre of original shape, and position of top-left of ROI in output image
cx, cy = (x0 + x1) //2, (y0 + y1)//2
top = cy - newH//2
left = cx - newW//2
# Paste in rescaled ROI
orig[top:top+newH, left:left+newW] = scaledROI
cv2.imwrite('result.png', orig)
That transforms this:
to this:
Puts me in mind of a pantograph:
I have been following a tutorial about computer vision and doing a little project to read the time from a game. The game time is formatted h:m. So far I got the h and m figured out using findContours, but I'm having trouble isolating the colon as the character shape is not continuous. Because of this when I try to matchTemplate the code freaks out and starts to use the dot to match to all the other digits.
Are there ways to group the contours by X?
Here are simplified code to get the reference digits, the code to get digits from the screen is basically the same.
refCnts = cv2.findContours(ref.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
refCnts = imutils.grab_contours(refCnts)
refCnts = contours.sort_contours(refCnts, method="left-to-right")[0]
digits = {}
# loop over the OCR-A reference contours
for (i, c) in enumerate(refCnts):
# compute the bounding box for the digit, extract it, and resize
# it to a fixed size
(x, y, w, h) = cv2.boundingRect(c)
roi = ref[y:y + h, x:x + w]
roi = cv2.resize(roi, (10, 13))
digits[i] = roi
Im new to python and opencv. Apologies in advance if this is a dumb question.
Here is the reference image I'm using:
Here is the input image I'm trying to read:
Do you have to use findCountours? Because there are better suited methods for such problems. For instance, you can use template matching as shown below:
These are input, template (cut out from your reference image), and output images:
import cv2
import numpy as np
# Read the input image & convert to grayscale
input_rgb = cv2.imread('input.png')
input_gray = cv2.cvtColor(input_rgb, cv2.COLOR_BGR2GRAY)
# Read the template (Using 0 to read image in grayscale mode)
template = cv2.imread('template.png', 0)
# Perform template matching - more on this here: https://docs.opencv.org/4.0.1/df/dfb/group__imgproc__object.html#ga3a7850640f1fe1f58fe91a2d7583695d
res = cv2.matchTemplate(input_gray,template,cv2.TM_CCOEFF_NORMED)
# Store the coordinates of matched area
# found the threshold value of .56 using trial & error using the input image - might be different in your game
lc = np.where( res >= 0.56)
# Draw a rectangle around the matched region
# I used the width and height of the template image but in practice you need to use a better method to accomplish this
w, h = template.shape[::-1]
for pt in zip(*lc[::-1]):
cv2.rectangle(input_rgb, pt, (pt[0] + w, pt[1] + h), (0,255,255), 1)
# display output
cv2.imshow('Detected',input_rgb)
# cv2.imwrite('output.png', input_rgb)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
You may also look into text detection & recognition using openCV.
I'm looking for a way to transform an image in polar coordinates using Python. The result I expect is the same as the following image (done in Matlab): https://i.stack.imgur.com/CKBBd.png
I already tried using cv2.linearPolar but I couldn't achieve this result.
Something like this should work:
import cv2
image = cv2.imread('image.jpg')
h, w, _ = image.shape
image2 = cv2.linearPolar(image, (w / 2, h / 2), min(w, h) / 2,
cv2.WARP_INVERSE_MAP + cv2.WARP_FILL_OUTLIERS)