Show green blobs with rectangles around three quadrants of target

show_green_rect.py

import cv2
import numpy as np
import math
import argparse

res = np.array([0])

# the following will:
# - find a green blob
# - find a contour around it
# - find a rectangle around the contour
# - extract a portion of the image for that rectangle
# - split the rectangle into three parts
# - find the contour and minAreaRect of each part
#
# The left part usually has an angle of around -30 degrees
# The middle part should be close to 0 degrees, but often isn't
# The right part usually has an angle around -60 degrees
#
def proc_part(part):
    contours2, hier2 = cv2.findContours(part, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    if len(contours2) > 0:
        cont2 = contours2[0]

        rect = cv2.minAreaRect(cont2)
        print(f"RECT: {rect}")
        box = cv2.boxPoints(rect)
        box = np.int0(box)
        return box

    return []


def proc_img(mask, img):
    global res
    contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    hexes = []

    res = cv2.bitwise_and(img, img, mask=mask)

    # debug code to show some contours for frame 100
    #print(f"Got contours, count: {len(contours)}")
    #print(contours)
    #img = cv2.drawContours(img, contours, -1, (0,255,255), 2)

    for cont in contours:
        x, y, w, h = cv2.boundingRect(cont)
        # only process larger areas with at least 5 points in the contour
        if (len(cont) > 4 and w > 40 and h > 40):
            quarter_w = int(w * 0.28)
            x0 = x
            y0 = y
            x1 = x + quarter_w
            y1 = y + h
            x2 = x + w - quarter_w
            x3 = x + w

            cv2.rectangle(img, (x0,y0), (x1, y1), (255,255,0), 2)
            cv2.rectangle(img, (x1,y0), (x2, y1), (255,255,0), 2)
            cv2.rectangle(img, (x2,y0), (x3, y1), (255,255,0), 2)

            part1 = mask[y0:y1, x0:x1]
            box1 = proc_part(part1)
            box1a = box1 + [x0, y0]
            #print(f"{x0:3d}/{y0:3d}  box1: {box1a}")
            img = cv2.drawContours(img, [box1a], 0, (0,200,255), 1)

            part2 = mask[y0:y1, x1:x2]
            box2 = proc_part(part2)
            box2a = box2 + [x1, y0]
            #print(f"box2: {box2a}")
            img = cv2.drawContours(img, [box2a], 0, (200,200,155), 1)

            part3 = mask[y0:y1, x2:x3]
            box3 = proc_part(part3)
            box3a = box3 + [x2, y0]
            #print(f"box3: {box3a}")
            img = cv2.drawContours(img, [box3a], 0, (0,200,155), 1)

            hexes.append(cont)
            #imgx = cv2.resize(img[y:y+h, x:x+w], None, fx=4.0, fy=4.0)
            #cv2.imshow('imgx', imgx)

        else:
            print(f"ELSE: bounding rect x y w h: {x:3d} {y:3d} {w:3d} {h:3d}")

    img = cv2.drawContours(img, hexes, -1, (0,0,255), 1)

    return img

def show_frame(img, res, mask):
    cv2.imshow('orig', img)
    cv2.imshow('res', res)
    cv2.imshow('mask', mask)
    img2 = cv2.resize(img, None, fx=2.0, fy=2.0)
    cv2.imwrite('testx.jpg', img2)
    ch = cv2.waitKey(20000) & 0xff

def process_pic(fname):
    
    upper_green = np.array([79,255,255])
    lower_green = np.array([58,50,100])
    cv2.namedWindow('orig')
    cv2.namedWindow('res')
    cv2.namedWindow('mask')
    cv2.moveWindow('orig', 0, 0)
    cv2.moveWindow('res', 600, 0)
    cv2.moveWindow('mask', 300, 500)
    quit_flag = False
    ratio = -1

    img = cv2.imread(fname, cv2.IMREAD_COLOR)
    
    if ratio < 0:
        ratio = 640.0 / img.shape[1]
        print(f"ratio = {ratio}")

    img = cv2.resize(img, None, fx=ratio, fy=ratio)
    # blur to get try to remove missing parts
    img = cv2.GaussianBlur(img, (5,5), 0)
    hsvimg = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsvimg, lower_green, upper_green)

    # mask out the bottom of the image 
    mask[250:,:] = 0

    img = proc_img(mask, img)

    show_frame(img, res, mask)


def main():
    parser = argparse.ArgumentParser()
    parser.add_argument('fname', help='Video filename', nargs='+')
    args = parser.parse_args()
    for video_fname in args.fname:
        process_pic(video_fname)

    cv2.destroyAllWindows()

if __name__ == '__main__':
    main()