In python, I have written some code that generates a circle using Bresenham's Midpoint Algorithm:
from PIL import Image, ImageDraw
radius = 100 #radius of circle
xpts = [] #array to hold x pts
ypts = [] #array to hold y pts
img = Image.new('RGB', (1000, 1000))
draw = ImageDraw.Draw(img) #to use draw.line()
pixels = img.load()
d = (5/4) - radius
x = 0
y = radius
xpts.append(x) #initial x value
ypts.append(y) #initial y value
while x < y:
if d < 0:
d += (2*x + 3)
x += 1
xpts.append(x + 500) #translate points to center by 500px
ypts.append(y - 500)
else:
d += (2 * (x - y) + 5)
x += 1
y -= 1
xpts.append(x + 500) #translate points to center by 500px
ypts.append(y - 500)
for i in range(len(xpts)): #draw initial and reflected octant points
pixels[xpts[i] ,ypts[i]] = (255,255,0) #initial octant
pixels[xpts[i],-ypts[i]] = (255,255,0)
pixels[-xpts[i],ypts[i]] = (255,255,0)
pixels[-xpts[i],-ypts[i]] = (255,255,0)
pixels[ypts[i],xpts[i]] = (255,255,0)
pixels[-ypts[i],xpts[i]] = (255,255,0)
pixels[ypts[i],-xpts[i]] = (255,255,0)
pixels[-ypts[i],-xpts[i]] = (255,255,0)
img.show()
To fill it, I had planned to use ImageDraw to draw a line horizontally within the circle from each point that is generated from the initial octant using draw.line(). I have the x and y coordinates stored in arrays. However, I am stuck interpreting each point and its reflection point to draw the horizontal line using draw.line(). Could someone clarify this?
Instead of drawing individual pixels, you would just add a line that connects the pixels corresponding to each other (either -x and +x or -y and +y). For each Bresenham step, you draw four lines (each connecting two octants).
Here is your adapted sample code. I dropped the points array and instead drew the lines directly. I also added the cx and cy variables that define the circle center. In your code, you sometimes used negative indices. This only works by coincidence because the circle is in the center:
from PIL import Image, ImageDraw
radius = 100 # radius of circle
xpts = [] # array to hold x pts
ypts = [] # array to hold y pts
img = Image.new('RGB', (1000, 1000))
draw = ImageDraw.Draw(img) # to use draw.line()
pixels = img.load()
d = (5 / 4) - radius
x = 0
y = radius
cx = 500
cy = 500
def draw_scanlines(x, y):
color = (255, 255, 0)
draw.line((cx - x, cy + y, cx + x, cy + y), fill=color)
draw.line((cx - x, cy - y, cx + x, cy - y), fill=color)
draw.line((cx - y, cy + x, cx + y, cy + x), fill=color)
draw.line((cx - y, cy - x, cx + y, cy - x), fill=color)
draw_scanlines(x, y)
while x < y:
if d < 0:
d += (2 * x + 3)
x += 1
else:
d += (2 * (x - y) + 5)
x += 1
y -= 1
draw_scanlines(x, y)
img.show()
Instead of drawing lines, you can fill all points inside a circle with radius radius in O(n^2) using:
# Your code here
for x in range(radius):
for y in range(radius):
if x**2 + y**2 < radius**2:
pixels[ x + 500 , y-500] = (255,255,0)
pixels[ x + 500 , -y-500] = (255,255,0)
pixels[ -x + 500 , y-500] = (255,255,0)
pixels[ -x + 500 , -y-500] = (255,255,0)
img.show()
Related
I am using Zelle graphics, but I suppose it is the same for any graphics program. From what I can tell, Zelle graphics does not have a "setheading" or "rotate" command for the rectangle (this is probably because the bounding box is created with two points). In turtle graphics it is easy with setheading(). So presently, I have a class that creates a polygon. I have a draw method and a rotate method. In the rotate method I am changing the Point(x1,y1) for each corner in a FOR LOOP. I broke out some graph paper to get the initial first few points to rotate, there is complex math I believe that would make this more palatable.
Presently this is my init method with these attributes, but I am sure there is a better way:
class create():
def __init__(self, p1x,p1y,p2x,p2y,p3x,p3y,p4x,p4y):
self.p1x = p1x
self.p2x = p2x
self.p3x = p3x
self.p4x = p4x
self.p1y = p1y
self.p2y = p2y
self.p3y = p3y
self.p4y = p4y
NOTE : this is not the entirety of my code. This is just the INIT method. I don't want anyone to think I have not tried this. I have with working code to rotate a polygon to the left about 5 points, but this is just using self.p1x=self.p1x+1 - I know this is not the correct way to rotate a rectangle. But at present I have a working model for rotating it slightly.
EDIT :
Here is the new work I have tried. I am still trying to understand this :
I need the midpoint, because the equation is derived from it. That is after I get the rotation correct. I am going to assume a midpoint in a 10x10 starting from the origin is going to be 5,5 for this example.
Does this code look ok so far? I am going to assume a rotation angle of 10 degrees for this example.
import math
#assume a 10 x 10 rectangle top left corner 0,0
#top left coords
x=0
y=0
#midpoints
midx = 5
midy = 5
#degrees to radians???????
angle=math.radians(10)
#new top left x
newx1 = x - midx * math.cos(angle) - (y-midy)*math.sin(angle)+ midx
#new top left y
newy1 = y - midy * math.sin(angle) + (x-midx)*math.cos(angle)+ midy
print(newx1, newy1)
The output is : 0.9442021232736115 -0.7922796533956911
This is version which works for me - it rotates Point around midx, midy with angle.
First it has to move middle to (0,0) and get current angle.
def rotate_point(point, angle, midx, midy):
old_x = point.x
old_y = point.y
old_cx = old_x - midx # move middle to (0,0)
old_cy = old_y - midy # move middle to (0,0)
angle_radians = math.radians(angle)
angle_sin = math.sin(angle_radians)
angle_cos = math.cos(angle_radians)
new_cx = old_cx * angle_cos - old_cy * angle_sin
new_cy = old_cx * angle_sin + old_cy * angle_cos
new_x = new_cx + midx # move back
new_y = new_cy + midy # move back
point = Point(new_x, new_y)
return point
And next I can use it to rotate Polygon
def rotate_polygon(polygon, angle, midx, midy):
new_points = []
for p in polygon.getPoints():
new_p = rotate_point(p, angle, midx, midy)
new_points.append(new_p)
return Polygon(*new_points)
Here full code which rotates
rectangle around middle point (angles: 30, 60),
triangle around one of corners (angles: 90, 180, 270).
import math
from graphics import *
def rotate_point(point, angle, midx, midy):
old_x = point.x
old_y = point.y
old_cx = old_x - midx # move middle to (0,0)
old_cy = old_y - midy # move middle to (0,0)
angle_radians = math.radians(angle)
angle_sin = math.sin(angle_radians)
angle_cos = math.cos(angle_radians)
new_cx = old_cx * angle_cos - old_cy * angle_sin
new_cy = old_cx * angle_sin + old_cy * angle_cos
new_x = new_cx + midx # move back
new_y = new_cy + midy # move back
point = Point(new_x, new_y)
return point
def rotate_polygon(polygon, angle, midx, midy):
new_points = []
for p in polygon.getPoints():
new_p = rotate_point(p, angle, midx, midy)
new_points.append(new_p)
return Polygon(*new_points)
# --- main ---
win = GraphWin()
# --- rectangle ---
x = 100
y = 100
w = 50
h = 50
midx = x + w//2 # rectangle middle
midy = y + h//2 # rectangle middle
p1 = Polygon(Point(x, y), Point(x+w, y), Point(x+w, y+h), Point(x, y+h), Point(x, y))
p1.draw(win)
p2 = rotate_polygon(p1, 30, midx, midy)
p2.draw(win)
p3 = rotate_polygon(p1, 60, midx, midy)
p3.draw(win)
# --- triangle ---
x = 60
y = 60
w = 50
h = 50
midx = x #+5 # triangle corner
midy = y #+5 # triangle corner
t1 = Polygon(Point(x, y), Point(x+w, y), Point(x+w//2, y+h), Point(x, y))
t1.draw(win)
t2 = rotate_polygon(t1, 90, midx, midy)
t2.draw(win)
t3 = rotate_polygon(t1, 180, midx, midy)
t3.draw(win)
t4 = rotate_polygon(t1, 270, midx, midy)
t4.draw(win)
# ---
win.getMouse()
win.close()
I am trying to generate an image with a randomly placed and rotated ellipse. Everything else is working as it should, however the ellipse is not rotating.
from PIL import ImageDraw, Image, ImageFilter
import math
import numpy as np
import random
#define build area
x_bound = int(input("X Resolution? (Pixel) "))
y_bound = int(input("Y resolution? (Pixel) "))
#define number of outputs
repetitions = int(input("How many output images would you like? "))
count = 0
#choose amount of bubbles
distortion = int(input("how many distorting circles would you like "))
while count != repetitions:
img = Image.new("RGB", (x_bound, y_bound), color="White")
draw = ImageDraw.Draw(img)
#initialize randomness based on clock
random.seed()
# Generate a basic random colour, random RGB values 10-245
R, G, B = random.randint(10, 245), random.randint(10, 245), random.randint(10, 245),
for _ in range(0, distortion):
# Choose RGB values for this circle
r = R + random.randint(-10, 10)
g = G + random.randint(-10, 10)
b = B + random.randint(-10, 10)
diam = random.randint(30, 90)
x, y = random.randint(0, x_bound), random.randint(0, y_bound)
draw.ellipse([x, y, x + diam, y + diam], fill=(r, g, b))
# Blur the background a bit
res = img.filter(ImageFilter.BoxBlur(5))
#img.show(res)
# define shape bounds.
# I don't want to have a 0 value for size, always moving in the positive direction
x1 = random.randint(0, x_bound) y1 = random.randint(0, y_bound)
x2 = random.randint(x1, x_bound)
y2 = random.randint(y1, y_bound)
#commented line allows you to check coordinates, point of error check
print(x1, y1, x2, y2)
shape = [(x1, y1), (x2, y2)]
# create ellipse image
img1 = ImageDraw.Draw(img)
img1.ellipse(shape, fill=None, outline="black")
# rotate the ellipse image
rotation_value = random.randint(0, 180)
rotate = img.rotate(rotation_value)
#img.show(rotate)
# finding bounds of rotated figure
angle = rotation_value * math.pi / 180
# rotated coordinates of each of the four bounded corners
x_prime_1 = -y1 * math.sin(angle) + x1 * math.cos(angle)
y_prime_1 = y1 * math.cos(angle) + x1 * math.sin(angle)
x_prime_2 = -y2 * math.sin(angle) + x2 * math.cos(angle)
y_prime_2 = y2 * math.cos(angle) + x2 * math.sin(angle)
# commented code line is to check coordinates of rotated shape for validity
print(x_prime_1, y_prime_1, x_prime_2, y_prime_2)
# start a counter, ensure that x coordinates fall within defined bounds
x_count = 0
if x_prime_1 < x_bound:
x_count += 1
if x_prime_1 > 0:
x_count += 1
if x_prime_2 < x_bound:
x_count += 1
if x_prime_2 > 0:
x_count += 1
# start a counter, ensure that y coordinates fall within defined bounds
y_count = 0
if y_prime_1 < y_bound:
y_count += 1
if y_prime_1 > 0:
y_count += 1
if y_prime_2 < y_bound:
y_count += 1
if y_prime_2 > 0:
y_count += 1
print(x_count), print(y_count)
# ensure that both x and y coordinates fall within the defined area. Only then will it produce an
image.
if y_count == 4:
if x_count == 4:
img.show()
count += 1
I am using OpenCV-Python to fit an ellipse to the shape of a droplet.
Then I choose a line, which represents the surface the droplet is resting on.
I calculate the tangents at the intersection of the surface and the ellipse to get the contact angle of the droplet.
It works most of the time, but in some cases, the tangents are flipped upside down or just wrong.
It seems that the calculation for the slope of the tangent fails.
Can someone tell me why this happens?
Here you can see how it should look like (surface at y=250):
And this is the result when I choose a surface level of y=47:
I did some research and I need to detect which of the two maj_ax, min_ax was parallel to the x-Axis before the ellipse gets rotated by phi or else the slope calculation algorithm fails.
What am I doing wrong?
Here is a minimal reproducible example:
from math import cos, sin, pi, sqrt, tan, atan2, radians
import cv2
class Droplet():
def __init__(self):
self.is_valid = False
self.angle_l = 0
self.angle_r = 0
self.center = (0,0)
self.maj = 0
self.min = 0
self.phi = 0.0
self.tilt_deg = 0
self.foc_pt1 = (0,0)
self.foc_pt2 = (0,0)
self.tan_l_m = 0
self.int_l = (0,0)
self.line_l = (0,0,0,0)
self.tan_r_m = 0
self.int_r = (0,0)
self.line_r = (0,0,0,0)
self.base_diam = 0
def evaluate_droplet(img, y_base) -> Droplet:
drplt = Droplet()
crop_img = img[:y_base,:]
shape = img.shape
height = shape[0]
width = shape[1]
# values only for 8bit images!
bw_edges = cv2.Canny(crop_img, 76, 179)
contours, hierarchy = cv2.findContours(bw_edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
if len(contours) == 0:
raise ValueError('No contours found!')
edge = max(contours, key=cv2.contourArea)
(x0,y0),(maj_ax,min_ax),phi_deg = cv2.fitEllipse(edge)
phi = radians(phi_deg) # to radians
a = maj_ax/2
b = min_ax/2
intersection = calc_intersection_line_ellipse((x0,y0,a,b,phi),(0,y_base))
if intersection is None:
raise ValueError('No intersections found')
# select left and right intersection points
x_int_l = min(intersection)
x_int_r = max(intersection)
foc_len = sqrt(abs(a**2 - b**2))
# calc slope and angle of tangent
m_t_l = calc_slope_of_ellipse((x0,y0,a,b,phi), x_int_l, y_base)
angle_l = pi - atan2(m_t_l,1)
m_t_r = calc_slope_of_ellipse((x0,y0,a,b,phi), x_int_r, y_base)
angle_r = atan2(m_t_r,1) + pi
drplt.angle_l = angle_l
drplt.angle_r = angle_r
drplt.maj = maj_ax
drplt.min = min_ax
drplt.center = (x0, y0)
drplt.phi = phi
drplt.tilt_deg = phi_deg
drplt.tan_l_m = m_t_l
drplt.tan_r_m = m_t_r
drplt.line_l = (int(round(x_int_l - (int(round(y_base))/m_t_l))), 0, int(round(x_int_l + ((height - int(round(y_base)))/m_t_l))), int(round(height)))
drplt.line_r = (int(round(x_int_r - (int(round(y_base))/m_t_r))), 0, int(round(x_int_r + ((height - int(round(y_base)))/m_t_r))), int(round(height)))
drplt.int_l = (x_int_l, y_base)
drplt.int_r = (x_int_r, y_base)
drplt.foc_pt1 = (x0 + foc_len*cos(phi), y0 + foc_len*sin(phi))
drplt.foc_pt2 = (x0 - foc_len*cos(phi), y0 - foc_len*sin(phi))
drplt.base_diam = x_int_r - x_int_l
drplt.is_valid = True
# draw ellipse and lines
img = cv2.drawContours(img,contours,-1,(100,100,255),2)
img = cv2.drawContours(img,edge,-1,(255,0,0),2)
img = cv2.ellipse(img, (int(round(x0)),int(round(y0))), (int(round(a)),int(round(b))), int(round(phi*180/pi)), 0, 360, (255,0,255), thickness=1, lineType=cv2.LINE_AA)
y_int = int(round(y_base))
img = cv2.line(img, (int(round(x_int_l - (y_int/m_t_l))), 0), (int(round(x_int_l + ((height - y_int)/m_t_l))), int(round(height))), (255,0,255), thickness=1, lineType=cv2.LINE_AA)
img = cv2.line(img, (int(round(x_int_r - (y_int/m_t_r))), 0), (int(round(x_int_r + ((height - y_int)/m_t_r))), int(round(height))), (255,0,255), thickness=1, lineType=cv2.LINE_AA)
img = cv2.ellipse(img, (int(round(x_int_l)),y_int), (20,20), 0, 0, -int(round(angle_l*180/pi)), (255,0,255), thickness=1, lineType=cv2.LINE_AA)
img = cv2.ellipse(img, (int(round(x_int_r)),y_int), (20,20), 0, 180, 180 + int(round(angle_r*180/pi)), (255,0,255), thickness=1, lineType=cv2.LINE_AA)
img = cv2.line(img, (0,y_int), (width, y_int), (255,0,0), thickness=2, lineType=cv2.LINE_AA)
img = cv2.putText(img, '<' + str(round(angle_l*180/pi,1)), (5,y_int-5), cv2.FONT_HERSHEY_COMPLEX, .5, (0,0,0))
img = cv2.putText(img, '<' + str(round(angle_r*180/pi,1)), (width - 80,y_int-5), cv2.FONT_HERSHEY_COMPLEX, .5, (0,0,0))
cv2.imshow('Test',img)
cv2.waitKey(0)
return drplt
def calc_intersection_line_ellipse(ellipse_pars, line_pars):
"""
calculates intersection(s) of an ellipse with a line
:param ellipse_pars: tuple of (x0,y0,a,b,phi): x0,y0 center of ellipse; a,b sem-axis of ellipse; phi tilt rel to x axis
:param line_pars: tuple of (m,t): m is the slope and t is intercept of the intersecting line
:returns: x-coordinate(s) of intesection as list or float or none if none found
"""
## -->> http://quickcalcbasic.com/ellipse%20line%20intersection.pdf
(x0, y0, h, v, phi) = ellipse_pars
(m, t) = line_pars
y = t - y0
try:
a = v**2 * cos(phi)**2 + h**2 * sin(phi)**2
b = 2*y*cos(phi)*sin(phi) * (v**2 - h**2)
c = y**2 * (v**2 * sin(phi)**2 + h**2 * cos(phi)**2) - (h**2 * v**2)
det = b**2 - 4*a*c
if det > 0:
x1 = int(round((-b - sqrt(det))/(2*a) + x0))
x2 = int(round((-b + sqrt(det))/(2*a) + x0))
return x1,x2
elif det == 0:
x = int(round(-b / (2*a)))
return x
else:
return None
except Exception as ex:
raise ex
def calc_slope_of_ellipse(ellipse_pars, x, y):
"""
calculates the slope of the tangent at point x,y, the point needs to be on the ellipse!
:param ellipse_params: tuple of (x0,y0,a,b,phi): x0,y0 center of ellipse; a,b sem-axis of ellipse; phi tilt rel to x axis
:param x: x-coord where the slope will be calculated
:returns: the slope of the tangent
"""
(x0, y0, a, b, phi) = ellipse_pars
# transform to non-rotated ellipse
x_rot = (x - x0)*cos(phi) + (y - y0)*sin(phi)
y_rot = (x - x0)*sin(phi) + (y - y0)*cos(phi)
m_rot = -(b**2 * x_rot)/(a**2 * y_rot) # slope of tangent to unrotated ellipse
#rotate tangent line back to angle of the rotated ellipse
m_tan = tan(atan2(m_rot,1) + phi)
return m_tan
if __name__ == "__main__":
im = cv2.imread('untitled1.png')
# any value below 250 is just the droplet without the substrate
drp = evaluate_droplet(im, 250)
Original image:
I made a mistake in calc_slope_ellipse:
x_rot = (x - x0)*cos(phi) + (y - y0)*sin(phi)
should be
x_rot = (x - x0)*cos(phi) - (y - y0)*sin(phi)
this fixes the wrong sign of the slope at y=47.
I replaced the atan2:
m_rot = -(b**2 * x_rot)/(a**2 * y_rot) # slope of tangent to unrotated ellipse
#rotate tangent line back to angle of the rotated ellipse
m_tan = tan(atan2(m_rot,1) + phi)
with
tan_a = x_rot/a**2
tan_b = y_rot/b**2
#rotate tangent line back to angle of the rotated ellipse
tan_a_r = tan_a*cos(phi) + tan_b*sin(phi)
tan_b_r = tan_b*cos(phi) - tan_a*sin(phi)
m_tan = - (tan_a_r / tan_b_r)
This fixes the weird behaviour for certain cases (y=62).
Complete fcn:
def calc_slope_of_ellipse(ellipse_pars, x, y):
(x0, y0, a, b, phi) = ellipse_pars
# transform to non-rotated ellipse centered to origin
x_rot = (x - x0)*cos(phi) - (y - y0)*sin(phi)
y_rot = (x - x0)*sin(phi) + (y - y0)*cos(phi)
# Ax + By = C
tan_a = x_rot/a**2
tan_b = y_rot/b**2
#rotate tangent line back to angle of the rotated ellipse
tan_a_r = tan_a*cos(phi) + tan_b*sin(phi)
tan_b_r = tan_b*cos(phi) - tan_a*sin(phi)
m_tan = - (tan_a_r / tan_b_r)
return m_tan
I am attempting to draw a rectangle with 3:2 aspect ratio.
I am using OpenCV to detect objects in image. So from the output values I am drawing a rectangle with min X, min Y, max X, max Y. Now I need to make that rectangle have a 3:2 aspect ratio from the starting points i.e min x and min Y.
It should not go beyond the original image max X and max Y and the
rectangle should not be lesser than existing rectangle around the
detected objects.
Here is one way you can solve this:
# determine the y / x length of the rectangle
len_X = maxX - minX
len_Y = maxY - minY
# determine the largest side, this will be the 3 in the aspect ratio
if len_X > len_Y:
# check if the shorter side is larger than a 3:2 ration
if len_Y > len_X * (3/2):
# if so, increase larger side to 3:2 ratio
len_X = len_Y * 1.5
else:
# else, increase shorter side to 3:2 ratio
len_Y = len_X * (3/2)
else:
# same as above
if len_X > len_Y * (3/2):
len_Y = len_X * 1.5
else:
len_X = len_Y * (3/2)
# if the rectangle exceeds the image, constrain the rectangle
# other option (commented): move the starting position
if minX + len_X > img.shape[1]:
len_X = img.shape[1]-minX
#minX = img.shape[1]-len_X
if minY + len_Y > img.shape[0]:
len_Y = img.shape[0]-minY
#minY = img.shape[0]-len_Y
# draw the rectangle
cv2.rectangle(img, (minX, minY), (minX + len_X, minY + len_Y), (0,0,255),1)
First calculate the new box size so that its w:h is 3:2. And then trim the box if one of its sides is longer than that of the image's.
After determining the box size, we then calculate the box center. By default, the box center remains the same, but it will be shifted if the box cross the boundary of the image.
Finally we can use box size and box center to calculate the coordinates of box corners.
import cv2
def draw_rectangle(img, min_x, min_y, max_x, max_y):
# resize box to 3:2(only enlarge it)
# determine the box_w and box_h
box_w, box_h = max_x-min_x, max_y-min_y
if box_w/box_h < 3/2:
box_w = int(box_h*(3/2))
else:
box_h = int(box_w*(2/3))
# trim the box so it won't be bigger than image
h, w = img.shape[:2]
box_w = w if box_w > w else box_w
box_h = h if box_h > h else box_h
# determine the center of box
# the default box center
box_center_x = (min_x+max_x)//2
box_center_y = (min_y+max_y)//2
# shift the box if it cross the boundary
if box_center_x + box_w//2 > w:
box_center_x = w - box_w//2
elif box_center_x - box_w//2 < 0:
box_center_x = box_w//2
if box_center_y + box_h//2 > h:
box_center_y = h - box_h//2
elif box_center_y - box_h//2 < 0:
box_center_y = box_h//2
# calculate the corner of the box
min_x, max_x = box_center_x - box_w//2, box_center_x + box_w//2
min_y, max_y = box_center_y - box_h//2, box_center_y + box_h//2
cv2.rectangle(img, (min_x, min_y), (max_x, max_y), (255,0,0), thickness=10)
return img
img = cv2.imread('image.jpg')
min_x, min_y, max_x, max_y = 0, 0, 400, 230
img = draw_rectangle(img, min_x, min_y, max_x, max_y)
cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
So apologies for the length of code here. Basically I have used opencv to analyse an image of 7 shapes and read 4 features from it.
The problem is that the code is only giving me out arrays for 5 shapes and I'm unsure why. I have left out the imports etc at the start to shorten the code.
img = cv2.imread("C:\\Users\\telli\\Desktop\\Shapetest.jpg")
#print(img)
#Converting the image to Grayscale
grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret,thresh = cv2.threshold(grey,127,255,1)
im2,contours, h = cv2.findContours(thresh, 1, cv2.CHAIN_APPROX_SIMPLE)
contours.sort(key = len)
numberOfSides = []
corners = []
standardDeviationsPerimeter = []
sidesDividedByPerimeter = []
standardDeviationsAngles = []
largestAngles = []
angles = []
perimeters = []
featureVectors = []
#finding all the possible circles in the image (likely many false positives)
circles = cv2.HoughCircles(grey,cv2.HOUGH_GRADIENT,1,20,
param1=50,param2=30,minRadius=0,maxRadius=0)
#finding sides
count = 0;
#print("New perimeter")
for contour in contours:
#remove double recognitions due to thick lines
if count %2 == 0:
epsilon = 10
x, y, w, h = cv2.boundingRect(contour)
x-= epsilon
y-= epsilon
w+= 2 *epsilon
h+= 2 * epsilon
insideCircle = False
#Removing false positive circles by testing each circle against
#the bounding box of this contour
#if we find a circle that is COMPLETELY inside the bounding box
#we have found a circle
for possibleCircle in range (0, len(circles[0])):
centreX = circles[0][possibleCircle][0]
centreY = circles[0][possibleCircle][1]
radius = circles[0][possibleCircle][2]
ToRight = centreX - radius >= x
ToLeft = centreX + radius <= x + w
ToBottom = centreY - radius >= y
ToTop = centreY + radius <= y + h
insideCircle = insideCircle or ToRight and ToLeft and ToBottom and ToTop
#Finding the perimeter of the shapes
perim = cv2.arcLength(contour, True)
perimeters.append(perim)
#if we found that this contour is a circle then the number of sides is 1
if insideCircle:
numberOfSides.append(1)
#use the number of corners found in the contours to determine how many
#sides it has
else:
corner = cv2.approxPolyDP(contour, 0.01 * perim, True)
corners.append(corner)
numberOfSides.append(len(corner))
#print(numberOfSides)
count = count + 1
#finding angles in shape
for shape in range(0, len(corners)):
angles.append([])
sidesDividedByPerimeter.append([])
for corner in range(0, len(corners[shape])):
# 3 vertices we need to find the angle at vertice b
ax = corners[shape][corner % len(corners[shape])][0][0]
ay = corners[shape][corner % len(corners[shape])][0][1]
bx = corners[shape][(corner + 1) % len(corners[shape])][0][0]
by = corners[shape][(corner + 1) % len(corners[shape])][0][1]
cx = corners[shape][(corner + 2) % len(corners[shape])][0][0]
cy = corners[shape][(corner + 2) % len(corners[shape])][0][1]
#print ("A: ", ax, ", ", ay, "\tB: ", bx, ", ", by, "\tC: ", cx, ", ", cy)
dirBAx = ax - bx
dirBAy = ay - by
dirBCx = cx - bx
dirBCy = cy - by
#do dot product and find angle in degrees
dot = dirBAx * dirBCx + dirBAy * dirBCy
lengthBC = math.sqrt(dirBCx * dirBCx + dirBCy * dirBCy)
lengthBA = math.sqrt(dirBAx * dirBAx + dirBAy * dirBAy)
angle = math.acos(dot / (lengthBC * lengthBA))
angle = angle * 180 / math.pi
angles[shape].append(angle)
sidesDividedByPerimeter[shape].append(lengthBC / perimeters[shape])
#print(lengthBC / perimeters[shape])
#print(angle)
#finding max of all angles in each shape
for shape in range(0, len(angles)):
largestAngles.append(np.amax(angles[shape]))
#print(largestAngles)
#if len(approx) == 16:
# cv2.drawContours(img, [contours[0]], 0, (0,0,255), -1)
#Calculating the standard deviation of the sides divided by the perimeter
#print("Standard Devs")
for shape in range(0, len(sidesDividedByPerimeter)):
standarddevPerim = statistics.stdev(sidesDividedByPerimeter[shape])
#Caluclating the standard deviation of the angles of each shape
standarddevAngle = statistics.stdev(angles[shape])
standardDeviationsPerimeter.append(standarddevPerim)
standardDeviationsAngles.append(standarddevAngle)
for shape in range(0, len(sidesDividedByPerimeter)):
featureVectors.append([])
featureVectors[shape].append(numberOfSides[shape])
featureVectors[shape].append(standardDeviationsPerimeter[shape])
featureVectors[shape].append(standardDeviationsAngles[shape])
featureVectors[shape].append(largestAngles[shape])
print(featureVectors)
And featureVector prints out this:
[[4, 0.001743713493735165, 0.6497055601752815, 90.795723552739275],
[4, 0.0460937435599832, 0.19764217920409227, 90.204147248752378],
[1, 0.001185534503063044, 0.3034913722821194, 60.348908179729023],
[1, 0.015455289770298222, 0.8380914254332884, 109.02120657826231],
[3, 0.0169961646358455, 41.36919146079211, 136.83829993466398]]
However there should be 7 shapes.
What i cant figure out is where to append blank values for the 2nd/3rd/4th feature for a circle and allow the program to continue running. It currently appears to be giving the 2nd/3rd/4th value from the next two shapes to the circles.