ha = ha+1
if(s):
sa = sa+1
if(v):
va = va+1
hue = hue / ha
sat = sat / sa
val = val / va
#ambil ukuran
panjang = 0
lebar = 0
float(panjang)
float(lebar)
panjang, lebar = size.cari_size(hasil)
print('Hasil1/%d/%d_%d.jpg' %(i, i, j))
name = 'Hasil1/%d/%d_%d.jpg' %(i, i, j)
myTomat = '%s, %d, %d, %d, %d, %d, %d, %d, %s' %(name, red, green, blue, hue, sat, val, jumlah_frek, panjang)
myTomat = myTomat + '\n'
#print(myTomat)
csv.write(myTomat)
#cv2.imwrite(name, hasil)
if(j == 15) :
i = i + 1
j = 0
def imageProcess(filename):
os.chdir('/home/ryanazrian/Desktop/PCD/Project/code/CodeFix/WEB')
img = cv2.imread('temp/' + filename)
red = 0
blue = 0
green = 0
hue = 0
sat = 0
val = 0
ha = 0
sa = 0
va = 0
re = 0
gr = 0
bl = 0
hsv = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
gray = cv2.cvtColor(hsv, cv2.COLOR_RGB2GRAY)
#img = cv2.resize(img, (0, 0), fx=0.1, fy=0.1)
#b, g, r = cv2.split()
#b = libs.treshold(libs.substract(r, g))
ret, b = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY)
dilate = cv2.dilate(b, kernel, iterations=10)
final = cv2.erode(dilate, kernel, iterations=10)
hasil = libs.subrgbgray(img, final)
row, col, ch = hasil.shape
for x in range(0, row):
for y in range(0, col):
b, g, r = hasil[x, y]
if (b & g & r):
red = red + r
green = green + g
blue = blue + b
if (b):
bl = bl + 1
if (r):
re = re + 1
if (g):
gr = gr + 1
red = red / re
green = green / gr
blue = blue / bl
jumlah_frek = re + gr + bl
HSV = cv2.cvtColor(hasil, cv2.COLOR_RGB2HSV)
row, col, ch = HSV.shape
for x in range(0, row):
for y in range(0, col):
h, s, v = HSV[x, y]
if (h & s & v):
hue = hue + h
sat = sat + s
val = val + v
if (h):
ha = ha + 1
if (s):
sa = sa + 1
if (v):
va = va + 1
hue = hue / ha
sat = sat / sa
val = val / va
#ambil ukuran
panjang = 0
lebar = 0
float(panjang)
float(lebar)
panjang, lebar = size.cari_size(hasil)
myTomat = '%d, %d, %d, %d, %d, %d, %d, %s' % (red, green, blue, hue, sat,
val, jumlah_frek, panjang)
testMatang = [[red, green, blue, hue, sat, val]]
testBerat = [[jumlah_frek, panjang]]
#test kematangan
filename = 'kematangan1.sav'
loaded_model = pickle.load(open(filename, 'rb'))
matangPredict = loaded_model.predict(
testMatang) #nnti ini test : inputan baru
#Test Berat
filename = 'berat1.sav'
loaded_model = pickle.load(open(filename, 'rb'))
beratPredict = loaded_model.predict(testBerat)
return matangPredict[0], beratPredict[0]
# print('Kematangan: %s' %(matangPredict[0]))
# print('Berat : %.2f' %(beratPredict[0]))