# readNet(model, config)

# cv2.dnn.readNet

# blobFromImage(image, scalefactor, size, mean, swapRB, crop) -> retval

# blob = cv2.dnn.blobFromImage

# net.setInput(blob)

# prob = net.forward()

########### googLeNet 영상인식

# 입력크기: 224 x 224  (224,224)

# 컬러: BGR

# 밝기평균값: (104, 117, 123)

# filename = ('./googlenet/fig/apple2.png')

filename = ('./googlenet/fig/Cat_November_2010-1a.jpeg')

img_files = glob.glob('./googlenet/fig/*.*')

img_lst = os.listdir('./googlenet/fig')

img_files = []

for i in img_lst:

    img_file = './googlenet/fig/' + i

    img_files.append(img_file)

cv2.namedWindow('img',cv2.WINDOW_NORMAL)

cv2.namedWindow('img',cv2.WINDOW_NORMAL)

cv2.setWindowProperty('img', cv2.WND_PROP_AUTOSIZE,cv2.WINDOW_AUTOSIZE)

img = cv2.imread(filename)

if img is None:

    print('image read failed')

    sys.exit()

#######################################################################################################

## dnn Model

model = './google/bvlc_googlenet.caffemodel'

config = './google/deploy.prototxt.txt'

net = cv2.dnn.readNet(model, config)  # 객체 생성

idx = 0

while True:

    if net.empty():

        print('network fail')

        sys.exit()

    ##클래스 이름 불러오기

    classNames = []

    with open('./google/classification_classes_ILSVRC2012.txt', 'rt') as f:

        classNames = f.read().rstrip('\n').split('\n')

    # print(classNames[200])

    # blobFromImage(image, scalefactor, size, mean, swapRB, crop) -> retval

    blob = cv2.dnn.blobFromImage(img,1,(224,224),(104, 117, 123),swapRB=False)

    net.setInput(blob)

    prob = net.forward()

    #######################################################################################################

    print(prob.shape)  # 2D

    out = prob.flatten()

    print(out.shape)

    classid = np.argmax(out)

    print(classid)

    confidence = out[classid]

    print(confidence)

    category = classNames[classid]

    print(category)

    text = f'{classNames[classid]} ({confidence*100:4.2f})%'

    img = cv2.imread(img_files[idx])

    cv2.putText(img, text, (100,30), cv2.FONT_HERSHEY_COMPLEX, 0.8, (0,0, 255),2, cv2.LINE_AA)    

    cv2.imshow('img', img)

    if cv2.waitKey(2000) == 27:

        break

    idx += 1

    if idx >= len(img_files):

        idx = 0

cv2.waitKey(1)

cv2.destroyAllWindows()

cv2.waitKey(1)