[amstrudy]

Here is Team 900's very simple gear detection based off of color and area.

# basic gear detection from HSV
# 1/14/17
# Team 900 Zebracorns
# Author: Anja S

import cv2
import numpy as np

cap = cv2.VideoCapture(1)

kernel = np.ones((5,5),np.uint8)

while(1):

	# Take each frame
	_, frame = cap.read()

	hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

	# Threshold the HSV image
	lower = np.array([20, 55, 124])
	upper = np.array([48, 255, 247])

	mask = cv2.inRange(hsv, lower, upper)

	opening = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
	closing = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel)

	# Contours
	contours = cv2.findContours(closing,cv2.cv.CV_RETR_TREE,cv2.cv.CV_CHAIN_APPROX_SIMPLE)[0]

	# Remove contours that don't fit area and HSV constraints

	gear_contour = []

	for c in contours:

		moments = cv2.moments(c)
		area = cv2.contourArea(c)

		if area < 3000: continue

		perim = cv2.arcLength(c, True)
		approx = cv2.approxPolyDP(c, 0.00005*perim, True)

		if len(approx) > 20:
			gear_contour.append(approx)

		for x in range(0, len(gear_contour)):

			minX = 10000
			minY = 10000
			maxX = 0
			maxY = 0
			cx = (minX + maxX)//2
			cy = (minY + maxY)//2

			# draw box around gear contour

			for y in range(0, len(gear_contour[x])):

				if gear_contour[x][y][0][0] < minX:
					minX = gear_contour[x][y][0][0]
				if gear_contour[x][y][0][1] < minY:
					minY = gear_contour[x][y][0][1]
				if gear_contour[x][y][0][0] > maxX:
					maxX = gear_contour[x][y][0][0]
				if gear_contour[x][y][0][1] > maxY:
					maxY = gear_contour[x][y][0][1]
			if gear_contour:

				cv2.drawContours(frame, gear_contour, -1, (255, 0, 0),3)
				cv2.rectangle(frame,(minX, minY),(maxX, maxY),(255,255,0),3)


	cv2.imshow('frame',frame)

	k = cv2.waitKey(5) & 0xFF
	if k == 27:
		break

cv2.destroyAllWindows()