EdiBot 2.0 Python Test

edibot_2.0_test_01.py

import cv2

# Debugging options
SHOW_IMAGE = True
VERBOSE = True

# HSV color thresholds for YELLOW
THRESHOLD_LOW = (15, 215, 50);
THRESHOLD_HIGH = (35, 255, 255);

# Camera resolution
CAMERA_WIDTH = 640
CAMERA_HEIGHT = 240

# Blob detector options
detectorParams = cv2.SimpleBlobDetector_Params()
detectorParams.minThreshold = 10
detectorParams.maxThreshold = 200
detectorParams.filterByArea = True
detectorParams.minArea = 40
detectorParams.maxArea = 70000
detectorParams.filterByCircularity = False
detectorParams.minCircularity = 0.1
detectorParams.filterByConvexity = False
detectorParams.minConvexity = 0.5
detectorParams.filterByInertia = False
detectorParams.minInertiaRatio = 0.5
detectorParams.filterByColor = False

###MAIN###

# Initialize camera
cam = cv2.VideoCapture(0)
cam.set(3, CAMERA_WIDTH)
cam.set(4, CAMERA_HEIGHT)

# Create blob detector
detector = cv2.SimpleBlobDetector(detectorParams)

while True:

  # Get image from camera
  ret_val, img = cam.read()

  # Blur image to remove noise
  img = cv2.GaussianBlur(img, (3, 3), 0)

  # Convert image from BGR to HSV
  img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

  # Set pixels to white if in color range, others to black
  img = cv2.inRange(img, THRESHOLD_LOW, THRESHOLD_HIGH)

  # Dilate image to make white blobs larger
  img = cv2.dilate(img, None, iterations = 1)

  # Find the largest blob
  keypoints = detector.detect(255 - img)
  blob = None
  blobSize = 0
  if keypoints:
    for k in keypoints:
      if k.size > blobSize:
        blob = k
        blobSize = k.size
  
  # Print blob location and size
  if VERBOSE:
    if blob != None:
      print "(" + str(blob.pt[0]) + "," + str(blob.pt[1]) + ") " + \
          str(blob.size)

  # Show image window (if debugging)
  if SHOW_IMAGE:
    img = cv2.drawKeypoints(img, [blob])
    cv2.imshow('my webcam', img)
    cv2.waitKey(1)