+++ /dev/null
-# -*- coding:utf-8 -*-
-
-from __future__ import absolute_import
-from __future__ import print_function
-from __future__ import division
-
-import os, sys
-import tensorflow as tf
-import time
-import cv2
-import argparse
-import numpy as np
-sys.path.append("../")
-
-from data.io.image_preprocess import short_side_resize_for_inference_data
-from libs.configs import cfgs
-from libs.networks import build_whole_network
-from libs.box_utils import draw_box_in_img
-from help_utils import tools
-
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-
-
-
-def load_graph(frozen_graph_file):
-
- # we parse the graph_def file
- with tf.gfile.GFile(frozen_graph_file, 'rb') as f:
- graph_def = tf.GraphDef()
- graph_def.ParseFromString(f.read())
-
- # we load the graph_def in the default graph
-
- with tf.Graph().as_default() as graph:
- tf.import_graph_def(graph_def,
- input_map=None,
- return_elements=None,
- name="",
- op_dict=None,
- producer_op_list=None)
- return graph
-
-
-def test(frozen_graph_path, test_dir):
-
- graph = load_graph(frozen_graph_path)
- print("we are testing ====>>>>", frozen_graph_path)
-
- img = graph.get_tensor_by_name("input_img:0")
- dets = graph.get_tensor_by_name("DetResults:0")
-
- with tf.Session(graph=graph) as sess:
- for img_path in os.listdir(test_dir):
- a_img = cv2.imread(os.path.join(test_dir, img_path))[:, :, ::-1]
- st = time.time()
- dets_val = sess.run(dets, feed_dict={img: a_img})
-
- show_indices = dets_val[:, 1] >= 0.5
- dets_val = dets_val[show_indices]
- final_detections = draw_box_in_img.draw_boxes_with_label_and_scores(a_img,
- boxes=dets_val[:, 2:],
- labels=dets_val[:, 0],
- scores=dets_val[:, 1])
- cv2.imwrite(img_path,
- final_detections[:, :, ::-1])
- print ("%s cost time: %f" % (img_path, time.time() - st))
-
-if __name__ == '__main__':
- test('/home/yjr/PycharmProjects/Faster-RCNN_Tensorflow/output/Pbs/FasterRCNN_Res101_Pascal_Frozen.pb',
- '/home/yjr/PycharmProjects/Faster-RCNN_Tensorflow/tools/demos')
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