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raspi.py
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raspi.py
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import cv2
import numpy as np
import sys
import RPi.GPIO as GPIO
import socket
client = socket.socket() # 声明socket类型，同时生成socket连接对象
client.connect(('192.168.123.26', 50007)) # 开始连接，ip地址为本地，端口号为6961
# open a camera with certain index
frameWidth = 1280
frameHeight = 720
cap = cv2.VideoCapture(0)
cap.set(3, frameWidth) # 宽度
cap.set(4, frameHeight) # 高度
# cap.set(10, 150) # 亮度
# whether the camera is successfully opened
if cap.isOpened():
print("camera ready.")
else:
print("camera open failed. close.")
# stop prg.
sys.exit()
Type = ["WHITE", "YELLOW", "GREEN", "STEM"]
Color = [(255, 255, 255), (51, 255, 255), (0, 204, 0), (0, 204, 0)]
h_min = [68, 39, 68, 40]
h_max = [91, 71, 96, 98]
s_min = [0, 18, 50, 13]
s_max = [21, 82, 255, 69]
v_min = [255, 217, 124, 0]
v_max = [255, 255, 255, 255]
maskleave = cv2.imread("/home/pi/Desktop/maskl0508.jpg")
maskleaveHSV = cv2.cvtColor(maskleave, cv2.COLOR_BGR2HSV)
maskstem = cv2.imread("/home/pi/Desktop/masks0509.jpg")
maskstemHSV = cv2.cvtColor(maskstem, cv2.COLOR_BGR2HSV)
masktarget = cv2.imread("/home/pi/Desktop/target.jpg") # 取包括桩在内的小长方形区域
masktargetHSV = cv2.cvtColor(masktarget, cv2.COLOR_BGR2HSV)
lowermask = np.array([0, 0, 100])
uppermask = np.array([0, 0, 255])
mask_leave = cv2.inRange(maskleaveHSV, lowermask, uppermask)
mask_stem = cv2.inRange(maskstemHSV, lowermask, uppermask)
mask_target = cv2.inRange(masktargetHSV, lowermask, uppermask)
# what if put all of the process into the definition?
def getLeaves(img, i):
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
img_leave = cv2.bitwise_and(imgHSV, imgHSV, mask=mask_leave)
lower = np.array([h_min[i], s_min[i], v_min[i]])
upper = np.array([h_max[i], s_max[i], v_max[i]])
maskcolor = cv2.inRange(img_leave, lower, upper)
kernel = np.ones((3, 3), np.uint8)
maskerode = cv2.erode(maskcolor, kernel, iterations=2)
maskdilate = cv2.dilate(maskerode, kernel, iterations=4)
contours, hierarchy = cv2.findContours(maskdilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
count = 0
for cnt in contours:
area = cv2.contourArea(cnt)
# print(area)
if area > 14000:
# print(area)
cv2.drawContours(imgContour, cnt, -1, (120, 100, 100), 3)
peri = cv2.arcLength(cnt, True)
# print(peri)
approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
# print(len(approx))
objCor = len(approx)
x, y, w, h = cv2.boundingRect(approx)
if objCor > 5:
if area > 28000:
count = count + 2
else:
count = count + 1
cv2.rectangle(imgContour, (x, y), (x + w, y + h), Color[i], 2)
cv2.putText(imgContour, Type[i],
(x + (w // 2) - 10, y + (h // 2) - 10), cv2.FONT_HERSHEY_COMPLEX, 0.7, Color[i],
2)
# cv2.putText(imgContour, number, (500, 50), cv2.FONT_HERSHEY_COMPLEX, 0.7, (0, 0, 255), 2)
# print("end")
return count
def getStems(img, i):
contours, hierarchy = cv2.findContours(image, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
count = 0
for cnt in contours:
area = cv2.contourArea(cnt)
# print(area)
if area > 900:
# print(area)
cv2.drawContours(imgContour, cnt, -1, (120, 100, 100), 3)
peri = cv2.arcLength(cnt, True)
# print(peri)
approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
# print(len(approx))
objCor = len(approx)
# print(objCor)
x, y, w, h = cv2.boundingRect(approx)
# if objCor > 5:
count = count + 1
cv2.rectangle(imgContour, (x, y), (x + w, y + h), Color[i], 2)
return count
def StopTarget(image):
imgHSVtarget = cv2.bitwise_and(image, image, mask=mask_target)
lower = np.array([40, 30, 135])
upper = np.array([90, 210, 255])
mask = cv2.inRange(imgHSVtarget, lower, upper) # 取绿色阈值区域
kernel = np.ones((3, 3), np.uint8)
mask = cv2.dilate(mask, kernel, iterations=2) # 膨胀
contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
for cnt in contours:
area = cv2.contourArea(cnt)
print(area)
if area > 2000:
# peri = cv2.arcLength(cnt, True)
# print(peri)
# approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
# print(len(approx))
return True
else:
return False
def StopStems(image, i):
lower = np.array([h_min[i], s_min[i], v_min[i]])
upper = np.array([h_max[i], s_max[i], v_max[i]])
imgHSVstem = cv2.bitwise_and(image, image, mask=mask_stem)
mask = cv2.inRange(imgHSVstem, lower, upper)
kernel = np.ones((3, 3), np.uint8)
maskerode = cv2.erode(mask, kernel, iterations=0)
maskdilate = cv2.dilate(maskerode, kernel, iterations=2)
contours, hierarchy = cv2.findContours(maskdilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
count = 0
for cnt in contours:
area = cv2.contourArea(cnt)
# print(area)
if area > 900:
# print(area)
# cv2.drawContours(imgContour, cnt, -1, (120, 100, 100), 3)
# peri = cv2.arcLength(cnt, True)
# print(peri)
# approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
# print(len(approx))
# objCor = len(approx)
# print(objCor)
# x, y, w, h = cv2.boundingRect(approx)
# if objCor > 5:
count = count + 1
# cv2.rectangle(imgContour, (x, y), (x + w, y + h), Color[i], 2)
if count >= 6:
return True
else:
return False
message = ['0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0',
'0', '0']
x1 = -2
x2 = -1
complete = 0
while True:
success, img = cap.read()
imgContour = img.copy()
GPIO.setmode(GPIO.BOARD)
GPIO.setwarnings(False)
GPIO.setup(33, GPIO.IN)
GPIO.setup(35, GPIO.IN)
GPIO.setup(37, GPIO.OUT)
GPIO.output(37, 0)
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
if StopTarget(imgHSV) and StopStems(imgHSV, 3):
GPIO.output(37, 1) # stop
sum_allleaves = sum_stems = sum_whiteleaves = 0
x1 += 2
x2 += 2
index = 0
while index < 5:
success, img = cap.read()
imgContour = img.copy()
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
img_leave = cv2.bitwise_and(imgHSV, imgHSV, mask=mask_leave)
img_stem = cv2.bitwise_and(imgHSV, imgHSV, mask=mask_stem)
# get all the leaves
count_allleaves = 0
for i in range(0, 3):
lower = np.array([h_min[i], s_min[i], v_min[i]])
upper = np.array([h_max[i], s_max[i], v_max[i]])
mask = cv2.inRange(img_leave, lower, upper)
kernel = np.ones((3, 3), np.uint8)
newmask1 = cv2.erode(mask, kernel, iterations=2)
newmask2 = cv2.dilate(newmask1, kernel, iterations=4)
count_leaves = getLeaves(newmask2)
count_allleaves += count_leaves
# get white leaves
i = 0
lower = np.array([h_min[i], s_min[i], v_min[i]])
upper = np.array([h_max[i], s_max[i], v_max[i]])
mask = cv2.inRange(img_leave, lower, upper)
kernel = np.ones((3, 3), np.uint8)
newmask3 = cv2.erode(mask, kernel, iterations=2)
newmask4 = cv2.dilate(newmask3, kernel, iterations=4)
count_whiteleaves = getLeaves(newmask4)
# get stems
i = 3
lower = np.array([h_min[i], s_min[i], v_min[i]])
upper = np.array([h_max[i], s_max[i], v_max[i]])
mask = cv2.inRange(img_stem, lower, upper)
kernel = np.ones((3, 3), np.uint8)
newmask5 = cv2.erode(mask, kernel, iterations=0)
newmask6 = cv2.dilate(newmask5, kernel, iterations=2)
count_stems = getStems(newmask6)
sum_allleaves += count_allleaves
sum_whiteleaves += count_whiteleaves
sum_stems += count_stems
index += 1
result_allleaves = round(sum_allleaves/index)
result_whiteleaves = round(sum_whiteleaves/index)
result_stems = round(sum_stems/index)
# if result_stems < 6:
# result_stems = 6
# elif result_stems > 8:
# result_stems = 8
result_flowers = result_stems - result_allleaves
# if result_whiteleaves >= 3:
# result_whiteleaves = 3
# result_flowers = 0
# if result_flowers < 0:
# result_flowers = 0
# elif result_flowers > 4:
# result_flowers = 4
result_text = 'whitelaves: ' + str(result_whiteleaves) + 'flowers: ' + str(result_flowers)
cv2.putText(imgContour, result_text, (50, 50), cv2.FONT_HERSHEY_COMPLEX, 0.7, (0, 0, 0), 2)
message[x1] = str(result_whiteleaves)
message[x2] = str(result_flowers)
cv2.imwrite('/home/pi/' + 'image' + str(x1/2 + 1) + '.png', imgContour)
msg = ''.join(message)
print(msg)
client.send(msg.encode("utf-8")) # 发送信息到服务器
GPIO.output(37, 0)
print("wait for next task")
client.send(msg.encode("utf-8")) # 发送信息到服务器
cv2.imshow("imgContour", imgContour)
cv2.waitKey(1)
if x1 == 22:
cv2.waitKey(1500)
data = client.recv(1024) # 接收服务器发过来的信息
print('client_recv:', data.decode()) # 打印服务器发来的信息
break
GPIO.cleanup()
client.close() # 最后，关闭客户端