Created
July 26, 2018 11:38
-
-
Save ghandic/b9c56dcb974e368f7467f7f92ce40052 to your computer and use it in GitHub Desktop.
Function to detect fields from a form, may need fine tuning!
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| from PIL import Image | |
| import numpy as np | |
| import cv2 | |
| import time | |
| # Helper function for jupyter notebooks | |
| def showarray(a): | |
| return Image.fromarray(a) | |
| def detect_boxes(img, min_percent_of_area=0.02, max_percent_of_area=2): | |
| # Make a copy of the image | |
| cp_img = img.copy() | |
| gray = cv2.cvtColor(cp_img, cv2.COLOR_RGB2GRAY) | |
| h, w, _ = img.shape | |
| blank_image = np.zeros((h,w), np.uint8) | |
| # Use edge detection to pull out lines, notice aperture size is not default, 5 works best | |
| edges = cv2.Canny(gray,0, 10, apertureSize=5) | |
| # Detect contours using the default settings | |
| _, contours,_ = cv2.findContours(edges,1,2) | |
| # If we find any contours that have 4 corners and within restrictions then add them onto the blank image | |
| for cnt in contours: | |
| approx = cv2.approxPolyDP(cnt,0.02*cv2.arcLength(cnt,True),True) | |
| if len(approx) == 4: | |
| if cv2.contourArea(cnt) > min_percent_of_area*h*w/100 and cv2.contourArea(cnt) < max_percent_of_area*h*w/100: | |
| cv2.drawContours(blank_image,[cnt],0,(255),-1) | |
| # Find all of the contours on the new image we have formed, this time with no restrictions, this now gets | |
| # one box if the contours were overlapping | |
| _, contours,_ = cv2.findContours(blank_image,1,2) | |
| # Now get the miniumum bounding box for each of the contours and return them as top_left and bottom_right | |
| countours_bb = [cv2.boundingRect(cnt) for cnt in contours] | |
| rects = [[(cnt[0], cnt[1]), (cnt[0]+cnt[2], cnt[1]+cnt[3])] for cnt in countours_bb] | |
| return rects | |
| if __name__ == '__main__': | |
| IMAGE_PATH = 'path/to/image.png' | |
| # Read image in | |
| img = cv2.imread(IMAGE_PATH) | |
| # Detect fields | |
| rects = detect_boxes(img) | |
| # Draw predicted boxes on | |
| _ = [cv2.rectangle(img, rect[0], rect[1], (255,0,0), 2) for rect in rects] | |
| # Show image in Jupyter Notebook | |
| showarray(img) | |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment