问题
I am using the following code to detect face and draw rectangle on top of the face.
while True:
# get video frame
ret, img = cap.read()
input_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img_h, img_w, _ = np.shape(input_img)
detected = detector(input_img, 1)
for i, d in enumerate(detected):
x1, y1, x2, y2, w, h = d.left(), d.top(), d.right() + 1, d.bottom() + 1, d.width(), d.height()
cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 0), 2)
cv2.imshow("result", img)
key = cv2.waitKey(30)
if key == 27:
break
The rectangle appears to be like this:
However Im trying to get a rectangle similar to this:
Is there any OpenCV or dlib function that can help me get this sort of effective rectangle?
回答1:
You can achieve what you want by using the functions that draw lines and arcs.
The frame you want to draw consists of 4 similar parts (one per corner), each rotated (or mirrored).
Let's have a look at the top left corner:
As you can see, we need to draw 2 line segments (of length d) and an arc (a quarter of a circle of radius r).
Let's say the coordinates of the top-left corner are (x1, y1).
That means that the arc will have a center at position (x1 + r, y1 + r).
One of the lines will go from (x1 + r, y1) to (x1 + r + d, y1).
The other line will go from (x1, y1 + r) to (x1, y1 + r + d).
Similar situation will happen with the other corners.
Sample code:
import cv2
import numpy as np
# ============================================================================
def draw_border(img, pt1, pt2, color, thickness, r, d):
x1,y1 = pt1
x2,y2 = pt2
# Top left
cv2.line(img, (x1 + r, y1), (x1 + r + d, y1), color, thickness)
cv2.line(img, (x1, y1 + r), (x1, y1 + r + d), color, thickness)
cv2.ellipse(img, (x1 + r, y1 + r), (r, r), 180, 0, 90, color, thickness)
# Top right
cv2.line(img, (x2 - r, y1), (x2 - r - d, y1), color, thickness)
cv2.line(img, (x2, y1 + r), (x2, y1 + r + d), color, thickness)
cv2.ellipse(img, (x2 - r, y1 + r), (r, r), 270, 0, 90, color, thickness)
# Bottom left
cv2.line(img, (x1 + r, y2), (x1 + r + d, y2), color, thickness)
cv2.line(img, (x1, y2 - r), (x1, y2 - r - d), color, thickness)
cv2.ellipse(img, (x1 + r, y2 - r), (r, r), 90, 0, 90, color, thickness)
# Bottom right
cv2.line(img, (x2 - r, y2), (x2 - r - d, y2), color, thickness)
cv2.line(img, (x2, y2 - r), (x2, y2 - r - d), color, thickness)
cv2.ellipse(img, (x2 - r, y2 - r), (r, r), 0, 0, 90, color, thickness)
# ============================================================================
img = np.zeros((256,256,3), dtype=np.uint8)
draw_border(img, (10,10), (100, 100), (127,255,255), 1, 10, 20)
draw_border(img, (128,128), (240, 160), (255,255,127), 1, 5, 5)
cv2.imwrite('round_rect.png', img)
Result:
回答2:
I did something naive. You can implement with further modifications using a function.
Steps:
I manually marked a rectangle around the text and extracted the 4 points.
Then I fixed a length for the line to be drawn from these 4 points.
Result:
Functions used:
cv2.line()cv2.rectangle()
See THIS LINK for details about their usage.
回答3:
Instead of looking for a function/lib that lets you make fancy rectangles, the following tactic might be easier:
Step 1 - Download an image of the rectangle that you want, such that it should only contain the 4 strokes at the corner, and the rest of the background should be black.
Step 2 - In your code, use imread to save this image as a Mat object:
border = cv2.imread('your_img.jpg')
Step 3 - Modify your for loop to superimpose the border Mat on the detected rectangle, as shown below:
for i, d in enumerate(detected):
x1, y1, x2, y2, w, h = d.left(), d.top(), d.right() + 1, d.bottom() + 1, d.width(), d.height()
#cv2.rectangle won't be needed anymore
#cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 0), 2)
roi=img[y1+h/2-100:y1+h/2+100,x1+w/2-100:x1+w/2+100]
#this points to a section in original image
cv2.addWeighted(roi,1,border,1,0,roi)
Ensure that the size of roi and border is the same, or your code will crash.
This will superimpose the corner strokes on your input frame, and neglect the black background.
回答4:
Thanks to @Dan Mašek for his suggestions. You can easily draw a fancy rectangle by like this way. You can check the full details Here: Drawing Fancy Round Rectangle around the Face
def draw_border(img, pt1, pt2, color, thickness, r, d):
x1,y1 = pt1
x2,y2 = pt2
# Top left
cv2.line(img, (x1 + r, y1), (x1 + r + d, y1), color, thickness)
cv2.line(img, (x1, y1 + r), (x1, y1 + r + d), color, thickness)
cv2.ellipse(img, (x1 + r, y1 + r), (r, r), 180, 0, 90, color, thickness)
# Top right
cv2.line(img, (x2 - r, y1), (x2 - r - d, y1), color, thickness)
cv2.line(img, (x2, y1 + r), (x2, y1 + r + d), color, thickness)
cv2.ellipse(img, (x2 - r, y1 + r), (r, r), 270, 0, 90, color, thickness)
# Bottom left
cv2.line(img, (x1 + r, y2), (x1 + r + d, y2), color, thickness)
cv2.line(img, (x1, y2 - r), (x1, y2 - r - d), color, thickness)
cv2.ellipse(img, (x1 + r, y2 - r), (r, r), 90, 0, 90, color, thickness)
# Bottom right
cv2.line(img, (x2 - r, y2), (x2 - r - d, y2), color, thickness)
cv2.line(img, (x2, y2 - r), (x2, y2 - r - d), color, thickness)
cv2.ellipse(img, (x2 - r, y2 - r), (r, r), 0, 0, 90, color, thickness)
def detect(path,img):
cascade = cv2.CascadeClassifier(path)
img=cv2.imread(img,1)
# converting to gray image for faster video processing
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
rects = cascade.detectMultiScale(gray, 1.2, 3,minSize=(50, 50))
# if at least 1 face detected
if len(rects) >= 0:
# Draw a rectangle around the faces
for (x, y, w, h) in rects:
draw_border(img, (x, y), (x + w, y + h), (255, 0, 105),4, 15, 10)
# Display the resulting frame
cv2.imshow('Face Detection', img)
# wait for 'c' to close the application
cv2.waitKey(0)
来源：https://stackoverflow.com/questions/46036477/drawing-fancy-rectangle-around-face