FRC Stuff

CvEdge-nvidia.py

import cv2
import numpy as np
import os
vidSrc = 0
# Capture Video
cap = cv2.VideoCapture(vidSrc)
os.system("./vidSetup.sh "+str(vidSrc))
# Color filter range
lowG = np.array([40,100,100])
highG = np.array([75,255,255])
# Min area of a object to be recognized
minArea = 500
def areaFilter(inputContours, minArea):
	ret = []
	for contour in inputContours:
		area = cv2.contourArea(contour)
		if area >= minArea:
			ret.append(contour)
	return ret

def genShape(contour):
	ret = []
	for cont in contour:
		ret.append(cv2.minAreaRect(cont))
	return ret

def maskGen(input,low, high):
	hsv = cv2.cvtColor(input, cv2.COLOR_RGB2HSV)
	mask = cv2.inRange(hsv, low, high)
	return mask

def getCountors(mask, minArea):
	_, contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
	filtered = areaFilter(contours,minArea)
	return contours, filtered

while True:
	#Capture Frame
	_, src = cap.read()
	cv2.imshow('origin',src)
	# Mask making
	mask=  maskGen(src, lowG, highG)

	# Mask showing
	mask_view = cv2.bitwise_and(src, src, mask = mask)
	cv2.imshow('Mask', mask_view)

	# Mask Proccessing
	cont, filt = getCountors(mask, minArea)
	rects = genShape(filt)

	# Show final image
	opt = src.copy()
	cv2.drawContours(opt, cont, -1, (255,0, 0), 1)
	cv2.drawContours(opt, filt, -1, (255,255,0), 3)
	
	for rect in rects:
		cv2.circle(opt, (int(rect[0][0]),int(rect[0][1])), 7, (0, 0, 0), -1)
		cv2.drawContours(opt, [np.int0(cv2.boxPoints(rect))], -1, (0,0,0), 2)
		print(rect)
	cv2.imshow('Result', opt)
	if cv2.waitKey(1) & 0xff == ord('q'):
		break
cap.release()
cv2.destroyAllWindows()

CvEdge.py

import cv2
import numpy as np

def areaFilter(inputContours, minArea):
	ret = []
	for contour in inputContours:
		area = cv2.contourArea(contour)
		if area >= minArea:
			ret.append(contour)
	return ret

def genShape(contour):
	ret = []
	for cont in contour:
		ret.append(cv2.minAreaRect(cont))
	return ret

def maskGen(input,low, high):
	hsv = cv2.cvtColor(input, cv2.COLOR_BGR2HSV)
	mask = cv2.inRange(hsv, low, high)
	return mask

def getCountors(mask, minArea):
	_, contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
	filtered = areaFilter(contours,minArea)
	return contours, filtered

# Capture Video
cap = cv2.VideoCapture(0)
# Color filter range
lowG = np.array([50,100,100])
highG = np.array([70,255,255])
# Min area of a object to be recognized
minPercent = 0.1
minArea = cap.get(cv2.CAP_PROP_FRAME_WIDTH) * cap.get(cv2.CAP_PROP_FRAME_HEIGHT) * minPercent
while True:
	#Capture Frame
	_, src = cap.read()

	# Mask making
	mask=  maskGen(src, lowG, highG)

	# Mask showing
	mask_view = cv2.bitwise_and(src, src, mask = mask)
	cv2.imshow('Mask', mask_view)

	# Mask Proccessing
	cont, filt = getCountors(mask, minArea)
	rects = genShape(filt)

	# Show final image
	opt = src.copy()
	cv2.drawContours(opt, cont, -1, (255,0, 0), 1)
	cv2.drawContours(opt, filt, -1, (255,255,0), 3)
	
	for rect in rects:
		cv2.circle(opt, (int(rect[0][0]),int(rect[0][1])), 7, (0, 0, 0), -1)
		cv2.drawContours(opt, [np.int0(cv2.boxPoints(rect))], -1, (0,0,0), 2)
		print(rect)
	cv2.imshow('Result', opt)
	if cv2.waitKey(1) & 0xff == ord('q'):
		break
cap.release()
cv2.destroyAllWindows()