AL-2020/coder/rocognizer.py

import numpy as np
import argparse
import imutils
import cv2
import matplotlib.pyplot as plt
import torch
from PIL import Image

path = "test1.jpg"

img = cv2.imread(path)

img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img_gray = cv2.GaussianBlur(img_gray, (5, 5), 0)

ret, im_th = cv2.threshold(img_gray, 90, 255, cv2.THRESH_BINARY_INV)

ctrs, hier = cv2.findContours(im_th.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

rects = [cv2.boundingRect(ctr) for ctr in ctrs]

for rect in rects:
    # Draw the rectangles
    cv2.rectangle(img, (rect[0], rect[1]), (rect[0] + rect[2], rect[1] + rect[3]), (0, 255, 0), 3)
    # Make the rectangular region around the digit
    leng = int(rect[3] * 1.6)
    pt1 = int(rect[1] + rect[3] // 2 - leng // 2)
    pt2 = int(rect[0] + rect[2] // 2 - leng // 2)
    roi = im_th[pt1:pt1+leng, pt2:pt2+leng]
    # Resize the image
    roi = cv2.resize(roi, (28, 28), interpolation=cv2.INTER_AREA)
    roi = cv2.dilate(roi, (3, 3))
    # Calculate the HOG features

cv2.imshow("Resulting Image with Rectangular ROIs", img)
cv2.waitKey()