blob_detection_video.py

# -*- coding: utf-8 -*-

'''
Sistema de detecção de Blobs


Lyang Leme de Medeiros - 19/04/2019
https://www.learnopencv.com/blob-detection-using-opencv-python-c/
'''
import cv2
import numpy as np

cap = cv2.VideoCapture(0)

while(True):
    # Capture frame-by-frame
    ret, frame = cap.read()

    # Our operations on the frame come here
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Setup SimpleBlobDetector parameters.
    params = cv2.SimpleBlobDetector_Params()

    # Change thresholds
    params.minThreshold = 10
    params.maxThreshold = 200

    # Filter by Area.
    params.filterByArea = True
    params.minArea = 1500

    # Filter by Circularity
    params.filterByCircularity = True
    params.minCircularity = 0.1

    # Filter by Convexity
    params.filterByConvexity = True
    params.minConvexity = 0.87

    # Filter by Inertia
    params.filterByInertia = True
    params.minInertiaRatio = 0.01

    # Create a detector with the parameters
    ver = (cv2.__version__).split('.')
    if int(ver[0]) < 3:
        detector = cv2.SimpleBlobDetector(params)
        detector = cv2.SimpleBlobDetector_create(params)
    else:
        detector = cv2.SimpleBlobDetector_create(params)

    # Detect blobs.
    keypoints = detector.detect(gray)

    # Draw detected blobs as red circles.
    # cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS ensures the size of the circle corresponds to the size of blob
    im_with_keypoints = cv2.drawKeypoints(gray, keypoints, np.array([]), (0, 0, 255), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)

    # Display the resulting frame
    cv2.imshow('frame', im_with_keypoints)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()