convertPx_2_cm.py

#!/usr/bin/env python

# Importing Librariesimport cv2
# from curses import window
import cv2
import numpy as np
from matplotlib import pyplot as plt

cv2.namedWindow('window')

# !/usr/bin/env python

# Importing Librariesimport cv2
# from curses import window
import cv2
import numpy as np
from matplotlib import pyplot as plt

# Capturing video
cap = cv2.VideoCapture("patitos.mp4")

while True:
    _, frame = cap.read()

    blurred = cv2.GaussianBlur(frame, (15, 15), 0, None)
    dst = cv2.fastNlMeansDenoisingColored(blurred, None, 6, 6, 1, 1)
    # cv2.imshow("dst", dst)

    image = cv2.cvtColor(dst, cv2.COLOR_BGR2HLS)
    # image = cv2.cvtColor(blurred,cv2.COLOR_Lab2RGB)
    # image = cv2.cvtColor(blurred,cv2.COLOR_RGB2GRAY)
    # cv2.imshow("video", image)

    lower = np.uint8([0, 200, 0])
    upper = np.uint8([255, 255, 255])
    white_mask = cv2.inRange(image, lower, upper)
    # yellow color mask
    lower = np.uint8([10, 0, 100])
    upper = np.uint8([40, 255, 255])
    yellow_mask = cv2.inRange(image, lower, upper)
    # combine the mask
    mask = cv2.bitwise_or(white_mask, yellow_mask)
    # cv2.imshow("mask",mask)

    blurred = cv2.GaussianBlur(mask, (15, 15), 0, None)
    # cv2.imshow("blurred", blurred)

    canny = cv2.Canny(blurred, 0, 255)

    cv2.imshow('window', canny)

    # detect contours
    cnts, hierarchy = cv2.findContours(canny, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2:]

    prom_l = 0
    num_cuadrados = 0

    for cnt in cnts:
        x1, y1 = cnt[0][0]
        approx = cv2.approxPolyDP(cnt, 0.01 * cv2.arcLength(cnt, True), True)
        # print(len(approx))

        if (len(approx) == 5):
            # x y son coordendas
            x, y, w, h = cv2.boundingRect(cnt)

            perimeter = 2 * (w + h)
            l = perimeter / 4

            if (l > 50 and l < 200):
                dif = h - w

                if (dif < 90 and dif > -90):
                    num_cuadrados += 1
                    prom_l += l
                    img = cv2.drawContours(dst, [cnt], -1, (0, 255, 255), 3)
                    # cv2.putText(dst, 'Square', (x1, y1), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 0), 2)

    try:
        prom_l = prom_l/num_cuadrados
        pix_2_cm = 30/prom_l
        print("promedio por frame: %f", prom_l)
        print("pixel a centimetro: %f", pix_2_cm)
    except:
        print("No hay cuadrados")
    cv2.imshow("Shapes", dst)
    key = cv2.waitKey(10)

    # plt.imshow(frame)
    plt.show()
    if key == 27:
        break

cap.release()
cv2.destroyAllWindows()