我目前正在学习TensorFlow，这是我的业余爱好，对Python来说还很陌生。

当相机拍摄一张照片并转到TensorFlow目录时（对象检测和tf.session已经完成运行），我正在尝试做一个项目。

它将检测到新图像，而无需再次运行tf.session。我不想使用实时对象检测。感谢您的帮助！

import os
import cv2
import numpy as np
import tensorflow as tf
import sys

sys.path.append("..")
from utils import label_map_util
from utils import visualization_utils as vis_util

IMAGE_NAME = '/home/hazirah/Tensorflow/models/research/object_detection/34.jpg'
MODEL_NAME = 'inference_graph'

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')

NUM_CLASSES = 1
PATH_TO_IMAGE = os.path.join(CWD_PATH,IMAGE_NAME)

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_boxes = detection_graph.get_tensor_by_name('detection_boxes: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')

image = cv2.imread(PATH_TO_IMAGE)
image_expanded = np.expand_dims(image,axis=0)

(boxes,scores,classes,num) = sess.run(
    [detection_boxes,detection_scores,detection_classes,num_detections],feed_dict={image_tensor: image_expanded})

final_score=np.squeeze(scores)
cnt=0
for i in range(100):
    if scores is None or final_score[i]>0.5:
        cnt=cnt+1

vis_util.visualize_boxes_and_labels_on_image_array(
    image,np.squeeze(boxes),np.squeeze(classes).astype(np.int32),np.squeeze(scores),category_index,use_normalized_coordinates=True,line_thickness=1,min_score_thresh=0.60)

while True:
    cv2.imshow('Object detector',image)
    print(cnt)
    cv2.putText(image,"Helmet_count: {}".format(cnt),(10,20),cv2.FONT_HERSHEY_SIMPLEX,0.5,(0,255),2)

按任意键关闭图像

cv2.waitKey(0)

清理

cv2.destroyAllWindows()