def main():
args = get_arguments()
range_filter = args['filter'].upper()
# if args['image']:
# image = cv2.imread(args['image'])
# if range_filter == 'RGB':
# frame_to_thresh = image.copy()
# else:
# frame_to_thresh = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
# else:
# camera = cv2.VideoCapture(0) # change 0 to 1 to change webcam number
if args['webcam']:
camera = cv2.VideoCapture(0) # change 0 to 1 to change webcam number
else:
# Initialize VREP-ARIF simulation
sim = arif.simulation().start()
# Get the camera instance
camera = arif.VideoCapture(sim, 'v0')
setup_trackbars(range_filter)
while True:
# if args['webcam']:
ret, image = camera.read()
# if not ret:
# break
if range_filter == 'RGB':
frame_to_thresh = image.copy()
else:
frame_to_thresh = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
v1_min, v2_min, v3_min, v1_max, v2_max, v3_max = get_trackbar_values(
range_filter)
thresh = cv2.inRange(frame_to_thresh, (v1_min, v2_min, v3_min),
(v1_max, v2_max, v3_max))
if args['preview']:
preview = cv2.bitwise_and(image, image, mask=thresh)
cv2.imshow("Preview", preview)
else:
cv2.imshow("Original", image)
cv2.imshow("Thresh", thresh)
if cv2.waitKey(1) & 0xFF is 27:
break
'''
import cv2
import numpy as np
import imutils
import math
'''--- For using the ARIF simulation ---'''
import sys, os
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
os.chdir("..\\ariflib") # <-- if in Windows
# os.chdir("../ariflib") # <-- if in Linux
from ariflib import arif
'''--------------------------------------'''
# Initialize VREP-ARIF simulation
sim = arif.simulation().start()
# Get the camera and robot instances
cap = arif.VideoCapture(sim, 'v0')
robot = arif.PioneerP3DX(sim)
# Threshold the HSV image for only orange colors
hsv_range = {
'lower_green': np.array([58, 70, 70]),
'upper_green': np.array([71, 255, 255]),
'lower_blue': np.array([115, 70, 70]),
'upper_blue': np.array([128, 255, 255]),
'lower_yellow': np.array([28, 70, 70]),
'upper_yellow': np.array([49, 255, 255]),
'lower_red': np.array([0, 70, 70]),
'upper_red': np.array([26, 255, 255])
}