How To Draw a Triangle-Arrow With The Positions of Detected Objects

Question

I am making a object detection project.

I have my code. And I have written it by following a tutorial. In the tutorial, the guy drew a rectangle in opencv for every single object which is detected.

But I want to change the rectangle to triangle or Arrow.

let me explain with code===>

In my function, I detect objects. And here I draw rectangle for detected objects==>

 cv2.rectangle(img, (x, y), (x+w,y+h), (255, 0 , 255), 2)

But I want to change this rectangle to a triangle.(And I want to set position of triangle to above of object. Just like in these images:::

This is the object detection with triangle [![enter image description here][1]][1]

This is the thing that what I want to make instead of rectangle::: [![enter image description here][2]][2]

How Can I make a triangle/arrow with positions of my detected objects? All of my code is here==>

from os.path import sep
import cv2 as cv2
import numpy as np
import json

# Camera feed
cap_cam = cv2.VideoCapture(0)

ret, frame_cam = cap_cam.read()

hey = 0

print(cv2. __version__)

whT = 320
confThreshold =0.5
nmsThreshold= 0.2

classesFile = "coco.names"
classNames = []
with open(classesFile, 'rt') as f:
    classNames = f.read().rstrip('\n').split('\n')
print(classNames)
## Model Files
modelConfiguration = "custom-yolov4-tiny-detector.cfg"
modelWeights = "custom-yolov4-tiny-detector_last.weights"
net = cv2.dnn.readNetFromDarknet(modelConfiguration, modelWeights)
net.setPreferableBackend(cv2.dnn.DNN_BACKEND_OPENCV)
net.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU)
def findObjects(outputs,img):
    global hey
    global previousHey  
    hT, wT, cT = img.shape
    bbox = []
    classIds = []
    confs = []
    for output in outputs:
        for det in output:
            scores = det[5:]
            classId = np.argmax(scores)
            confidence = scores[classId]
            if confidence > confThreshold:
                w,h = int(det[2]*wT) , int(det[3]*hT)
                x,y = int((det[0]*wT)-w/2) , int((det[1]*hT)-h/2)
                bbox.append([x,y,w,h])
                classIds.append(classId)
                confs.append(float(confidence))
    global indicates
    indices = cv2.dnn.NMSBoxes(bbox, confs, confThreshold, nmsThreshold)
    hey = 0
    for i in indices:
        i = i[0]
        box = bbox[i]
        x, y, w, h = box[0], box[1], box[2], box[3]
        # print(x,y,w,h)
        cv2.rectangle(img, (x, y), (x+w,y+h), (255, 0 , 255), 2)
        
        #cv2.line(img, (350,400), (x, y), (255,0,0), 4)
        #cv2.line(img, (400,400), (x + 50 , y), (255,0,0), 4)
        #cv.putText(img,f'{classNames[classIds[i]].upper()} {int(confs[i]*100)}%',
                  #(x, y-10), cv.FONT_HERSHEY_SIMPLEX, 0.6, (255, 0, 255), 2)
        print('success')
        hey = 1
            
        
video_frame_counter = 0
while cap_cam.isOpened():
    img = cv2.imread('photos' + sep + 'lutfen.jpg')
    #BURADA OK VİDEOSU OYNATILACAK
    #if not decetiona diye dene yarın.
    blob = cv2.dnn.blobFromImage(img, 1 / 255, (whT, whT), [0, 0, 0], 1, crop=False)
    net.setInput(blob)
    layersNames = net.getLayerNames()
    outputNames = [(layersNames[i[0] - 1]) for i in net.getUnconnectedOutLayers()]
    outputs = net.forward(outputNames)
    findObjects(outputs,img)
    cv2.imshow('Image', img)
    
    # Video feed
    if hey == 1:
        filename = 'photos' + sep + 'Baslksz-3.mp4'
        cap_vid = cv2.VideoCapture(filename)
        
    if hey == 0:
        filename = 'photos' + sep + 'vid2.mp4'
        cap_vid = cv2.VideoCapture(filename)    
    print(hey)
    ret, frame_vid = cap_vid.read()

#cap_cam.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
#cap_cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)

# Resize the camera frame to the size of the video
    height = int(cap_vid.get(cv2.CAP_PROP_FRAME_HEIGHT))
    width = int(cap_vid.get(cv2.CAP_PROP_FRAME_WIDTH))
    # Capture the next frame from camera
    ret, frame_cam = cap_cam.read()
    video_frame_counter += 1
    if video_frame_counter == cap_vid.get(cv2.CAP_PROP_FRAME_COUNT):
            video_frame_counter = 0
            cap_vid.set(cv2.CAP_PROP_POS_FRAMES, 0)
    frame_cam = cv2.resize(frame_cam, (width, height), interpolation = cv2.INTER_AREA)

    #ret = cap_vid.set(cv2.CAP_PROP_POS_MSEC, time_passed)

    ret, frame_vid = cap_vid.read()
    if not ret:
        print('Cannot read from video stream')
        break

    # Blend the two images and show the result
    tr = 0.4 # transparency between 0-1, show camera if 0
    frame = ((1-tr) * frame_cam.astype(np.float) + tr * frame_vid.astype(np.float)).astype(np.uint8)
    cv2.imshow('Transparent result', frame)
    if cv2.waitKey(1) == 27: # ESC is pressed
        break
    
cap_cam.release()
cap_vid.release()
cv2.destroyAllWindows()

Answer 1

The easy way

You can use the cv.arrowedLine() function that will draw something similar to what you want. For example, to draw a red arrow above your rectangle:

center_x = x + w//2
cv2.arrowedLine(img, (center_x, y-50), (center_x, y-5), (0,0,255), 2, 8, 0, 0.5)

which should give a result similar to the image below. Take a look at the OpenCV documentation for the description of the parameters of the function. You can change its size, thickness, color, etc.

Custom arrow shape

If you want more control over the shape of your arrow, you can define a contour (vertex by vertex) and use cv.drawContours() to render it. For example:

# define the arrow shape
shape = np.array([[[0,0],[-25,-25],[-10,-25],[-10,-50],
                   [10,-50],[10,-25],[25,-25]]])

# move it to the desired position
cx = x + w // 2
cy = y - 5
shape[:,:,0] += cx
shape[:,:,1] += cy

# draw it
cv2.drawContours(img, shape, -1, (0, 255, 0), -1)

This snippet will give you the image below. You can adjust the shape by altering the vertices in the shape array, or look at the documentation to change the way OpenCV draws it.