Есть ли способ отобразить обнаруженное количество объектов на экране обнаружения?

Question

Я создал собственную модель обнаружения объектов. Мне нужно количество объектов, которые его обнаружение отображать на экране. Приведенный ниже код используется для обнаружения объектов, мне нужно отобразить счет вместе с ним.

# Import packages
import os
import cv2
import numpy as np
import tensorflow as tf
import sys
sys.path.append("..")

# Import utilites
from utils import label_map_util
from utils import visualization_utils as vis_util

MODEL_NAME = 'inference_graph'
IMAGE_NAME = 'rofl.jpg'

# Grab path to current working directory
CWD_PATH = os.getcwd()


PATH_TO_CKPT = 
os.path.join(CWD_PATH,MODEL_NAME,'frozen_inference_graph.pb')

# Path to label map file
PATH_TO_LABELS = os.path.join(CWD_PATH,'training','labelmap.pbtxt')

# Path to image
PATH_TO_IMAGE = os.path.join(CWD_PATH,IMAGE_NAME)

# Number of classes the object detector can identify
NUM_CLASSES = 1


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)

# Load the Tensorflow model into memory.
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)

# Define input and output tensors (i.e. data) for the object detection 
classifier

# Input tensor is the image
image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')

# Output tensors are the detection boxes, scores, and classes
# Each box represents a part of the image where a particular object was 
detected
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)

# Perform the actual detection by running the model with the image as 
input
(boxes, scores, classes, num) = sess.run(
[detection_boxes, detection_scores, detection_classes, num_detections],
feed_dict={image_tensor: image_expanded})

# Draw the results of the detection (aka 'visulaize the results')

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=8,
    min_score_thresh=0.60)

 # All the results have been drawn on image. Now display the image.
 cv2.imshow('Object detector', image)

# Press any key to close the image
cv2.waitKey(0)

# Clean up
cv2.destroyAllWindows()

обнаруженные объекты

На изображении выше показаны обнаруженные объекты. Я хочу отобразить количество обнаруженных объектов на одном экране