[boundingBox] opencv code WIP

gistfile1.txt

contours, _ = cv2.findContours(thresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
for c in contours:
    rect = cv2.boundingRect(c)
    if rect[2] < 100 or rect[3] < 100: continue
    print cv2.contourArea(c)
    x,y,w,h = rect
    cv2.rectangle(im,(x,y),(x+w,y+h),(0,255,0),2)
    cv2.putText(im,'Moth Detected',(x+w+10,y+h),0,0.3,(0,255,0))
cv2.imshow("Show",im)
cv2.waitKey()  
cv2.destroyAllWindows()




import cv2
import numpy as np 
 
# read and scale down image
img = cv2.pyrDown(cv2.imread('hammer.jpg', cv2.IMREAD_UNCHANGED))
 
# threshold image
ret, threshed_img = cv2.threshold(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY),
                127, 255, cv2.THRESH_BINARY)
# find contours and get the external one
image, contours, hier = cv2.findContours(threshed_img, cv2.RETR_TREE,
                cv2.CHAIN_APPROX_SIMPLE)
 
# with each contour, draw boundingRect in green
# a minAreaRect in red and
# a minEnclosingCircle in blue
for c in contours:
    # get the bounding rect
    x, y, w, h = cv2.boundingRect(c)
    # draw a green rectangle to visualize the bounding rect
    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
 
    # get the min area rect
    rect = cv2.minAreaRect(c)
    box = cv2.boxPoints(rect)
    # convert all coordinates floating point values to int
    box = np.int0(box)
    # draw a red 'nghien' rectangle
    cv2.drawContours(img, [box], 0, (0, 0, 255))
 
    # finally, get the min enclosing circle
    (x, y), radius = cv2.minEnclosingCircle(c)
    # convert all values to int
    center = (int(x), int(y))
    radius = int(radius)
    # and draw the circle in blue
    img = cv2.circle(img, center, radius, (255, 0, 0), 2)
 
print(len(contours))
cv2.drawContours(img, contours, -1, (255, 255, 0), 1)
 
cv2.imshow("contours", img)
 
ESC = 27
while True:
    keycode = cv2.waitKey()
    if keycode != -1:
        keycode &amp;= 0xFF
        if keycode == ESC:
            break
cv2.destroyAllWindows()
Use cv2.boundingRect to get the bounding rectangle (in green), cv2.minAreaRect to get the minimum area rectangle (in red), and cv2.minEnclosingCircle to get minimum enclosing circle (in blue).

Result:

contour_all.png