def identify_easy_sample(img):
#mask_img = cv2.resize(mask_img, (img_start.shape[1], img.shape[0]))
#img = np.concatenate((img_start, mask_img), axis=1)
# filter out purple object
filtered = Color_Filter.filter_colors(frame=img, show_images=False, verbose=False)
# detect edges of purple object
edges = Color_Filter.contour_color(frame=filtered["Median Blur"][filtered["Colors"][0]], show_images=False)
# blur creates consistency
blurred = cv2.GaussianBlur(edges, (5,5), 0)
# get image contours (hopefully only one, the purple sample)
(cnts, _) = cv2.findContours(blurred.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
cv2.imshow('image', blurred)
if cnts:
# take the biggest contour and calculate its centroid
cont = max(cnts, key = cv2.contourArea)
moments = cv2.moments(cont)
centx = int(moments['m10']/moments['m00'])
centy = int(moments['m01']/moments['m00'])
# absolute coordinates where (0,0) is bottom left
return (centx,(centy))
else:
return None
def check_easy_sample(left, right):
xyz = None
# filter image so that only purple objects show up in each image
filter_left = Color_Filter.filter_colors(frame=left, show_images=False, verbose=False)
filter_right = Color_Filter.filter_colors(frame=right, show_images=False, verbose=False)
# detect edges of the purple objects in each image
edges_left = Color_Filter.contour_color(frame=filter_left["Median Blur"][filter_left["Colors"][0]], show_images=False)
edges_right = Color_Filter.contour_color(frame=filter_right["Median Blur"][filter_right["Colors"][0]], show_images=False)
#cv2.imshow('LEFT', edges_left)
#cv2.imshow('RIGHT', edges_right)
# blur to create consistency
#blurred_left = cv2.GaussianBlur(edges_left, (5,5), 0)
#blurred_right = cv2.GaussianBlur(edges_right, (5,5), 0)
# find image contours
(cnts_left, _) = cv2.findContours(edges_left.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
(cnts_right, _) = cv2.findContours(edges_right.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
if cnts_left and cnts_right:
# take the biggest contour from each image and calculate their centroids
left_cont = max(cnts_left, key = cv2.contourArea)
right_cont = max(cnts_right, key = cv2.contourArea)
left_moments = cv2.moments(left_cont)
right_moments = cv2.moments(right_cont)
if left_moments['m00'] != 0 and right_moments['m00'] != 0:
left_centx = int(left_moments['m10']/left_moments['m00'])
right_centx = int(right_moments['m10']/right_moments['m00'])
left_centy = int(left_moments['m01']/left_moments['m00'])
right_centy = int(right_moments['m01']/right_moments['m00'])
# calulcate distance from camera (in mm):
xyz = calculate_distance(left_centx, right_centx, left_centy, right_centy)
rospy.loginfo("Easy_Sample:(x,y,z): {0}".format(xyz))
else:
rospy.loginfo("DIVIDE BY ZERO")
else:
rospy.loginfo("NO PURPLE")
return None
# print for testing only
#cv2.imshow('LEFT', blurred_left)
#cv2.imshow('RIGHT', blurred_right)
# returns a tuple (x,y,z), or None if no sample is detected
print "see thing at "+str(xyz)
return xyz
