Python OpenCV | cv2.circle () method

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OpenCV-Python is a Python link library designed to solve computer vision problems. The cv2.circle () method is used to draw a circle on any image.
Syntax: cv2.circle(image, center_coordinates, radius, color, thickness) Parameters: image: It is the image on which circle is to be drawn. center_coordinates: It is the center coordinates of circle. The coordinates are represented as tuples of two values i.e. (X coordinate value, Y coordinate value). radius: It is the radius of circle. color: It is the color of border line of circle to be drawn. For BGR, we pass a tuple. eg: (255, 0, 0) for blue color. thickness: It is the thickness of the circle border line in px. Thickness of -1 px will fill the circle shape by the specified color. Return Value: It returns an image.

How to draw a circle over image OpenCV?

StackOverflow question

Im usign python and opencv to get a image from the webcam, and I want to know how to draw a circle over my image, just a simple green circle with transparent fill enter image description here my code:
import cv2
import numpy
import sys

if __name__ == ’__main__’:


    #get current frame from webcam
    cam = cv2.VideoCapture(0)
    img = cam.read()

    #how draw a circle????

    cv2.imshow(’WebCam’, img)

    cv2.waitKey()
Thanks in advance.

Answer

cv2.circle(img, center, radius, color, thickness=1, lineType=8, shift=0) ‚Üí None
Draws a circle.

Parameters: 
img (CvArr) – Image where the circle is drawn
center (CvPoint) – Center of the circle
radius (int) – Radius of the circle
color (CvScalar) – Circle color
thickness (int) – Thickness of the circle outline if positive, otherwise this indicates that a filled circle is to be drawn
lineType (int) – Type of the circle boundary, see Line description
shift (int) – Number of fractional bits in the center coordinates and radius value
Use "thickness" parameter for only the border.

Example #1

def blob(x):
    """Given an Nx3 matrix of blob positions and size, 
    create N img_size x img_size images, each with a blob drawn on 
    them given by the value in each row of x
    
    One row of x = [x,y,radius]."""
    y = np.zeros((x.shape[0], img_size, img_size))
    for i, particle in enumerate(x):
        rr, cc = skimage.draw.circle(
            particle[0], particle[1], max(particle[2], 1), shape=(img_size, img_size)
        )
        y[i, rr, cc] = 1
    return y


#%%

# names (this is just for reference for the moment!) 

Example #2

def update(self, radarData):
        self.img = np.zeros((self.height, self.width, self.channels), np.uint8)
        cv2.line(self.img, (10, 0), (self.width/2 - 5, self.height), (100, 255, 255))
        cv2.line(self.img, (self.width - 10, 0), (self.width/2 + 5, self.height), (100, 255, 255))

        for track_number in range(1, 65):
            if str(track_number)+’_track_range’ in radarData:
                track_range = radarData[str(track_number)+’_track_range’]
                track_angle = (float(radarData[str(track_number)+’_track_angle’])+90.0)*math.pi/180

                x_pos = math.cos(track_angle)*track_range*4
                y_pos = math.sin(track_angle)*track_range*4

                cv2.circle(self.img, (self.width/2 + int(x_pos), self.height - int(y_pos) - 10), 5, (255, 255, 255))
                #cv2.putText(self.img, str(track_number), 
                #    (self.width/2 + int(x_pos)-2, self.height - int(y_pos) - 10), self.font, 1, (255,255,255), 2)

        cv2.imshow("Radar", self.img)
        cv2.waitKey(2) 

Example #3

def ProcessFrame(self, frame):
        # segment arm region
        segment = self.SegmentArm(frame)

        # make a copy of the segmented image to draw on
        draw = cv2.cvtColor(segment, cv2.COLOR_GRAY2RGB)

        # draw some helpers for correctly placing hand
        cv2.circle(draw,(self.imgWidth/2,self.imgHeight/2),3,[255,102,0],2)       
        cv2.rectangle(draw, (self.imgWidth/3,self.imgHeight/3), (self.imgWidth*2/3, self.imgHeight*2/3), [255,102,0],2)

        # find the hull of the segmented area, and based on that find the
        # convexity defects
        [contours,defects] = self.FindHullDefects(segment)

        # detect the number of fingers depending on the contours and convexity defects
        # draw defects that belong to fingers green, others red
        [nofingers,draw] = self.DetectNumberFingers(contours, defects, draw)

        # print number of fingers on image
        cv2.putText(draw, str(nofingers), (30,30), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255))
        return draw 

Example #4

def mark_hand_center(frame_in,cont):    
    max_d=0
    pt=(0,0)
    x,y,w,h = cv2.boundingRect(cont)
    for ind_y in xrange(int(y+0.3*h),int(y+0.8*h)): #around 0.25 to 0.6 region of height (Faster calculation with ok results)
        for ind_x in xrange(int(x+0.3*w),int(x+0.6*w)): #around 0.3 to 0.6 region of width (Faster calculation with ok results)
            dist= cv2.pointPolygonTest(cont,(ind_x,ind_y),True)
            if(dist>max_d):
                max_d=dist
                pt=(ind_x,ind_y)
    if(max_d>radius_thresh*frame_in.shape[1]):
        thresh_score=True
        cv2.circle(frame_in,pt,int(max_d),(255,0,0),2)
    else:
        thresh_score=False
    return frame_in,pt,max_d,thresh_score

# 6. Find and display gesture 

Example #5

def update(self, radarData):
        self.img = np.zeros((self.height, self.width, self.channels), np.uint8)
        cv2.line(self.img, (10, 0), (self.width/2 - 5, self.height), (100, 255, 255))
        cv2.line(self.img, (self.width - 10, 0), (self.width/2 + 5, self.height), (100, 255, 255))

        for track_number in range(1, 65):
            if str(track_number)+’_track_range’ in radarData:
                track_range = radarData[str(track_number)+’_track_range’]
                track_angle = (float(radarData[str(track_number)+’_track_angle’])+90.0)*math.pi/180

                x_pos = math.cos(track_angle)*track_range*4
                y_pos = math.sin(track_angle)*track_range*4

                cv2.circle(self.img, (self.width/2 + int(x_pos), self.height - int(y_pos) - 10), 5, (255, 255, 255))
                #cv2.putText(self.img, str(track_number), 
                #    (self.width/2 + int(x_pos)-2, self.height - int(y_pos) - 10), self.font, 1, (255,255,255), 2)

        cv2.imshow("Radar", self.img)
        cv2.waitKey(2) 

Archived version

OpenCV-Python —¬†is a Python bindings library for solving computer vision problems.¬† cv2.circle () is used to draw a circle on any image.
Syntax: cv2.circle (image, center_coordinates, radius, color , thickness) Parameters: image: It is the image on which circle is to be drawn. center_coordinates: It is the center coordinates of circle. The coordinates are represented as tuples of two values ​​ie ( X coordinate value, Y coordinate value). radius: It is the radius of circle. color: It is the color of border line of circle to be drawn. For BGR , we pass a tuple. eg: (255, 0, 0) for blue color. thickness: It is the thickness of the circle border line in px . Thickness of -1 px will fill the rectangle shape by the specified color. Return Value: It returns an image. The image is used for all examples below: Example # 1:
# Python program to explain the cv2.circle () method ¬† # cv2 import import cv2¬† ¬† # path path = r ’C: UsersRajnishDesktoppythonengineeringgeeks.png’ ¬†¬† # Read image in default mode image = cv2.imread (path) ¬† # Name of the window in which the image is displayed window_name = ’Image’ ¬†¬† # Center coordinates center_coordinates = ( 120 , 50 ) ¬† # Circle radius radius = 20 ¬†¬† # Blue color in BGR color = ( 255 , 0 , 0 ) ¬† # Line width 2 px thickness = 2 ¬† # Using the cv2.circle () method # Draw a circle with a 2 px blue border image = cv2.circle (image, center_coordinates, radius, color, thickness) ¬† # Display image cv2.imshow (window_name, image)¬†
Output: Example # 2: Using -1 px thickness to fill the rectangle with red.
# Python program to explain the cv2.circle () method ¬† # cv2 import import cv2¬† ¬† # path path = r ’C: UsersRajnishDesktoppythonengineeringgeeks.png’ ¬† # Read image in default mode image = cv2.imread (path) ¬† # Name of the window in which the image is displayed window_name = ’Image’ ¬†¬† # Center coordinates center_coordinates = ( 120 , 100 ) ¬†¬† # Circle radius radius = 30 ¬†¬† # Red in BGR color = ( 0 , 0 , 255 ) ¬† # Line thickness -1 px thickness = - 1 ¬† # Using the cv2.circle () method # Draw a -1 px red circle image = cv2.circle (image, center_coordinates, radius, color, thickness) <¬†code class = "undefined spaces">¬†¬† # Displaying an image cv2.imshow (window_name, image )¬† ¬†
Output:

Python OpenCV | cv2.circle () method around: Questions

Removing white space around a saved image in matplotlib

2 answers

I need to take an image and save it after some process. The figure looks fine when I display it, but after saving the figure, I got some white space around the saved image. I have tried the "tight" option for savefig method, did not work either. The code:

  import matplotlib.image as mpimg
  import matplotlib.pyplot as plt

  fig = plt.figure(1)
  img = mpimg.imread(path)
  plt.imshow(img)
  ax=fig.add_subplot(1,1,1)

  extent = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
  plt.savefig("1.png", bbox_inches=extent)

  plt.axis("off") 
  plt.show()

I am trying to draw a basic graph by using NetworkX on a figure and save it. I realized that without a graph it works, but when added a graph I get white space around the saved image;

import matplotlib.image as mpimg
import matplotlib.pyplot as plt
import networkx as nx

G = nx.Graph()
G.add_node(1)
G.add_node(2)
G.add_node(3)
G.add_edge(1,3)
G.add_edge(1,2)
pos = {1:[100,120], 2:[200,300], 3:[50,75]}

fig = plt.figure(1)
img = mpimg.imread("image.jpg")
plt.imshow(img)
ax=fig.add_subplot(1,1,1)

nx.draw(G, pos=pos)

extent = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
plt.savefig("1.png", bbox_inches = extent)

plt.axis("off") 
plt.show()
228

Answer #1

You can remove the white space padding by setting bbox_inches="tight" in savefig:

plt.savefig("test.png",bbox_inches="tight")

You"ll have to put the argument to bbox_inches as a string, perhaps this is why it didn"t work earlier for you.


Possible duplicates:

Matplotlib plots: removing axis, legends and white spaces

How to set the margins for a matplotlib figure?

Reduce left and right margins in matplotlib plot

228

Answer #2

I cannot claim I know exactly why or how my “solution” works, but this is what I had to do when I wanted to plot the outline of a couple of aerofoil sections — without white margins — to a PDF file. (Note that I used matplotlib inside an IPython notebook, with the -pylab flag.)

plt.gca().set_axis_off()
plt.subplots_adjust(top = 1, bottom = 0, right = 1, left = 0, 
            hspace = 0, wspace = 0)
plt.margins(0,0)
plt.gca().xaxis.set_major_locator(plt.NullLocator())
plt.gca().yaxis.set_major_locator(plt.NullLocator())
plt.savefig("filename.pdf", bbox_inches = "tight",
    pad_inches = 0)

I have tried to deactivate different parts of this, but this always lead to a white margin somewhere. You may even have modify this to keep fat lines near the limits of the figure from being shaved by the lack of margins.

Python OpenCV | cv2.circle () method circle: Questions

How to do a scatter plot with empty circles in Python?

2 answers

In Python, with Matplotlib, how can a scatter plot with empty circles be plotted? The goal is to draw empty circles around some of the colored disks already plotted by scatter(), so as to highlight them, ideally without having to redraw the colored circles.

I tried facecolors=None, to no avail.

204

Answer #1

From the documentation for scatter:

Optional kwargs control the Collection properties; in particular:

    edgecolors:
        The string ‘none’ to plot faces with no outlines
    facecolors:
        The string ‘none’ to plot unfilled outlines

Try the following:

import matplotlib.pyplot as plt 
import numpy as np 

x = np.random.randn(60) 
y = np.random.randn(60)

plt.scatter(x, y, s=80, facecolors="none", edgecolors="r")
plt.show()

example image

Note: For other types of plots see this post on the use of markeredgecolor and markerfacecolor.

plot a circle with pyplot

2 answers

surprisingly I didn"t find a straight-forward description on how to draw a circle with matplotlib.pyplot (please no pylab) taking as input center (x,y) and radius r. I tried some variants of this:

import matplotlib.pyplot as plt
circle=plt.Circle((0,0),2)
# here must be something like circle.plot() or not?
plt.show()

... but still didn"t get it working.

199

Answer #1

You need to add it to an axes. A Circle is a subclass of an Patch, and an axes has an add_patch method. (You can also use add_artist but it"s not recommended.)

Here"s an example of doing this:

import matplotlib.pyplot as plt

circle1 = plt.Circle((0, 0), 0.2, color="r")
circle2 = plt.Circle((0.5, 0.5), 0.2, color="blue")
circle3 = plt.Circle((1, 1), 0.2, color="g", clip_on=False)

fig, ax = plt.subplots() # note we must use plt.subplots, not plt.subplot
# (or if you have an existing figure)
# fig = plt.gcf()
# ax = fig.gca()

ax.add_patch(circle1)
ax.add_patch(circle2)
ax.add_patch(circle3)

fig.savefig("plotcircles.png")

This results in the following figure:

The first circle is at the origin, but by default clip_on is True, so the circle is clipped when ever it extends beyond the axes. The third (green) circle shows what happens when you don"t clip the Artist. It extends beyond the axes (but not beyond the figure, ie the figure size is not automatically adjusted to plot all of your artists).

The units for x, y and radius correspond to data units by default. In this case, I didn"t plot anything on my axes (fig.gca() returns the current axes), and since the limits have never been set, they defaults to an x and y range from 0 to 1.

Here"s a continuation of the example, showing how units matter:

circle1 = plt.Circle((0, 0), 2, color="r")
# now make a circle with no fill, which is good for hi-lighting key results
circle2 = plt.Circle((5, 5), 0.5, color="b", fill=False)
circle3 = plt.Circle((10, 10), 2, color="g", clip_on=False)
    
ax = plt.gca()
ax.cla() # clear things for fresh plot

# change default range so that new circles will work
ax.set_xlim((0, 10))
ax.set_ylim((0, 10))
# some data
ax.plot(range(11), "o", color="black")
# key data point that we are encircling
ax.plot((5), (5), "o", color="y")
    
ax.add_patch(circle1)
ax.add_patch(circle2)
ax.add_patch(circle3)
fig.savefig("plotcircles2.png")

which results in:

You can see how I set the fill of the 2nd circle to False, which is useful for encircling key results (like my yellow data point).

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