该程序的目的是从屏幕快照中检测卡，并打印屏幕上检测到的卡数：
jwt_token = jwt.encode(payload, settings.SECRET_KEY)
问题是，当我在屏幕上显示一张卡片时，它会不断向import pyscreenshot as ImageGrab
from win32api import GetSystemMetrics
import os
import cv2
import numpy as np
import tensorflow as tf
import sys
import warnings
import h5py
def UpdateLabels(labels):
for ch in data:
if ch['name'] == "ace":
labels["ace"] += 1
elif ch['name'] == "king":
labels["king"] += 1
elif ch['name'] == "queen":
labels["queen"] += 1
elif ch['name'] == "jack":
labels["jack"] += 1
elif ch['name'] == "ten":
labels["ten"] += 1
elif ch['name'] == "nine":
labels["nine"] += 1
elif ch['name'] == "eight":
labels["eight"] += 1
elif ch['name'] == "seven":
labels["seven"] += 1
elif ch['name'] == "six":
labels["six"] += 1
elif ch['name'] == "five":
labels["five"] += 1
elif ch['name'] == "four":
labels["four"] += 1
elif ch['name'] == "three":
labels["three"] += 1
elif ch['name'] == "two":
labels["two"] += 1
return labels
if __name__ == '__main__':
sys.path.append("..")
from utils import label_map_util
from utils import visualization_utils as vis_util
MODEL_NAME = 'inference_graph'
IMAGE_NAME = 'test1.jpg'
CWD_PATH = os.getcwd()
PATH_TO_CKPT = os.path.join(CWD_PATH,MODEL_NAME,'frozen_inference_graph.pb')
PATH_TO_LABELS = os.path.join(CWD_PATH,'training','labelmap.pbtxt')
PATH_TO_IMAGE = os.path.join(CWD_PATH,IMAGE_NAME)
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
NUM_CLASSES = 13
label_map = label_map_util.load_labelmap(PATH_TO_LABELS)
categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES, use_display_name=True)
category_index = label_map_util.create_category_index(categories)
detection_graph = tf.Graph()
with detection_graph.as_default():
od_graph_def = tf.GraphDef()
with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:
serialized_graph = fid.read()
od_graph_def.ParseFromString(serialized_graph)
tf.import_graph_def(od_graph_def, name='')
sess = tf.Session(graph=detection_graph)
image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')
detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
labels = {"ace" : 0, "king": 0, "queen": 0, "jack": 0, "ten": 0, "nine": 0, "eight": 0,"seven": 0, "six": 0, "five": 0, "four":0, "three": 0, "two": 0}
while True:
with warnings.catch_warnings():
warnings.filterwarnings("ignore",category=FutureWarning)
screenshot=ImageGrab.grab(bbox=(42,42, GetSystemMetrics(0),GetSystemMetrics(1)))
screenshot.save(IMAGE_NAME)
image = cv2.imread(PATH_TO_IMAGE)
image_expanded = np.expand_dims(image, axis=0)
(scores, classes, num) = sess.run(
[detection_scores, detection_classes, num_detections],
feed_dict={image_tensor: image_expanded})
data = [category_index.get(value) for index,value in enumerate(classes[0]) if scores[0,index] > 0.99]
UpdateLabels(labels)
print(labels)
添加同一张卡片，而我只需要跟踪可以识别的新卡片。例如，当我显示ace时，程序的输出将为：
它一直将同一张卡加到labels，它应该继续显示“ 1”王牌
只要识别出一张新卡，例如一张两张，就应该显示“ 1” ace和“ 1”两个，如果识别出另一张一张ace，则应该显示“ 2” ace和“ 1”两个。我该怎么做？
