# Computer vision : A box on a industrial conveyor

### 1. Introduction

To start exploring OpenCV with Python, we’ll start by a simple exercise : Detect a cardboard box on a industrial conveyor (from a average picture took with a smartphone) : As as first step, we’ll identity the contour of the box and define a “perfect” rotated rectangle of the minimum area enclosing our box. The result will be this : ### 2. Code details

```img = cv2.imread('box-1.jpg')
```

Blur the picture :

``` Convert to gray scale : Calculate the threshold level and we apply it : Detect contours :
cv2.drawContours(img, contours, -1, (0, 255, 0), 3 )

The result is : That’s why, to do it quick, we sort out the biggest and convex (close) contour:
cv2.drawContours(img, contours, max_index, (0, 255, 0), 3 ) Now we just have the contour that we wanted, but it’s not a rectangle !
Let’s draw a rotated rectangle of the minimum area enclosing our box, in red : And to finish, just the code to show a picture in a good size windows in Python :

import numpy as np
import cv2

#Gaussian blur
blurred = cv2.GaussianBlur(img, (5, 5), 0)
#Convert to graysscale
gray = cv2.cvtColor(blurred,cv2.COLOR_BGR2GRAY)
#Autocalculate the thresholding level
#Threshold
retval, bin = cv2.threshold(gray, 100, 255, cv2.THRESH_BINARY)
#Find contours
bin, contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
#Sort out the biggest contour (biggest area)
max_area = 0
max_index = -1
index = -1
for i in contours:
area = cv2.contourArea(i)
index=index+1
if area > max_area :
max_area = area
max_index = index

#Draw the raw contours
cv2.drawContours(img, contours, max_index, (0, 255, 0), 3 )
cv2.imwrite("box-1-biggest-contour.png", img)

#Draw a rotated rectangle of the minimum area enclosing our box (red)
cnt=contours[max_index]
rect = cv2.minAreaRect(cnt)
box = cv2.boxPoints(rect)
box = np.int0(box)
img = cv2.drawContours(img,[box],0,(0,0,255),2)

#Show original picture with contour
cv2.namedWindow('image', cv2.WINDOW_NORMAL)
cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

```