tensorflow - 如何使用 tensorflow 对象检测 API 计算检测到的对象(在边界框中)的数量
问题描述
我使用来自 edje Electronics 的教程和 Faster R-CNN,它有效,但我想改进它。我想计算问题的对象.......我怎样才能删除准确率百分比并将其替换为计数边界框的数量。
我不知道我必须添加哪个并将其删除以计算边界框这里是代码
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
MODEL_NAME = 'inference_graph'
VIDEO_NAME = 'animal.mov'
# Grab path to current working directory
CWD_PATH = os.getcwd()
# Path to frozen detection graph .pb file, which contains the model that is used
# for object detection.
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_VIDEO = os.path.join(CWD_PATH,VIDEO_NAME)
NUM_CLASSES = 6
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)
# Define input and output tensors (i.e. data) for the object detection classifier
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')
video = cv2.VideoCapture(PATH_TO_VIDEO)
while(video.isOpened()):
ret, frame = video.read()
frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
frame_expanded = np.expand_dims(frame_rgb, axis=0)
(boxes, scores, classes, num) = sess.run(
[detection_boxes, detection_scores, detection_classes, num_detections],
feed_dict={image_tensor: frame_expanded})
vis_util.visualize_boxes_and_labels_on_image_array(
frame,
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)
cv2.imshow('Object detector', frame)
if cv2.waitKey(1) == ord('q'):
break
video.release()
cv2.destroyAllWindows()
解决方案
您必须修改 utils/visualization_utils.py 中的 visible_boxes_and_labels_on_image_array() 函数以删除 conf 分数显示并显示 box 数组的长度
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