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Python detection_inference.build_inference_graph方法代碼示例

本文整理匯總了Python中object_detection.inference.detection_inference.build_inference_graph方法的典型用法代碼示例。如果您正苦於以下問題:Python detection_inference.build_inference_graph方法的具體用法?Python detection_inference.build_inference_graph怎麽用?Python detection_inference.build_inference_graph使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在object_detection.inference.detection_inference的用法示例。


在下文中一共展示了detection_inference.build_inference_graph方法的3個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: main

# 需要導入模塊: from object_detection.inference import detection_inference [as 別名]
# 或者: from object_detection.inference.detection_inference import build_inference_graph [as 別名]
def main(_):
  tf.logging.set_verbosity(tf.logging.INFO)

  required_flags = ['input_tfrecord_paths', 'output_tfrecord_path',
                    'inference_graph']
  for flag_name in required_flags:
    if not getattr(FLAGS, flag_name):
      raise ValueError('Flag --{} is required'.format(flag_name))

  with tf.Session() as sess:
    input_tfrecord_paths = [
        v for v in FLAGS.input_tfrecord_paths.split(',') if v]
    tf.logging.info('Reading input from %d files', len(input_tfrecord_paths))
    serialized_example_tensor, image_tensor = detection_inference.build_input(
        input_tfrecord_paths)
    tf.logging.info('Reading graph and building model...')
    (detected_boxes_tensor, detected_scores_tensor,
     detected_labels_tensor) = detection_inference.build_inference_graph(
         image_tensor, FLAGS.inference_graph)

    tf.logging.info('Running inference and writing output to {}'.format(
        FLAGS.output_tfrecord_path))
    sess.run(tf.local_variables_initializer())
    tf.train.start_queue_runners()
    with tf.python_io.TFRecordWriter(
        FLAGS.output_tfrecord_path) as tf_record_writer:
      try:
        for counter in itertools.count():
          tf.logging.log_every_n(tf.logging.INFO, 'Processed %d images...', 10,
                                 counter)
          tf_example = detection_inference.infer_detections_and_add_to_example(
              serialized_example_tensor, detected_boxes_tensor,
              detected_scores_tensor, detected_labels_tensor,
              FLAGS.discard_image_pixels)
          tf_record_writer.write(tf_example.SerializeToString())
      except tf.errors.OutOfRangeError:
        tf.logging.info('Finished processing records') 
開發者ID:ahmetozlu,項目名稱:vehicle_counting_tensorflow,代碼行數:39,代碼來源:infer_detections.py

示例2: test_simple

# 需要導入模塊: from object_detection.inference import detection_inference [as 別名]
# 或者: from object_detection.inference.detection_inference import build_inference_graph [as 別名]
def test_simple(self):
    create_mock_graph()
    create_mock_tfrecord()

    serialized_example_tensor, image_tensor = detection_inference.build_input(
        [get_mock_tfrecord_path()])
    self.assertAllEqual(image_tensor.get_shape().as_list(), [1, None, None, 3])

    (detected_boxes_tensor, detected_scores_tensor,
     detected_labels_tensor) = detection_inference.build_inference_graph(
         image_tensor, get_mock_graph_path())

    with self.test_session(use_gpu=False) as sess:
      sess.run(tf.global_variables_initializer())
      sess.run(tf.local_variables_initializer())
      tf.train.start_queue_runners()

      tf_example = detection_inference.infer_detections_and_add_to_example(
          serialized_example_tensor, detected_boxes_tensor,
          detected_scores_tensor, detected_labels_tensor, False)

    self.assertProtoEquals(r"""
        features {
          feature {
            key: "image/detection/bbox/ymin"
            value { float_list { value: [0.0, 0.1] } } }
          feature {
            key: "image/detection/bbox/xmin"
            value { float_list { value: [0.8, 0.2] } } }
          feature {
            key: "image/detection/bbox/ymax"
            value { float_list { value: [0.7, 0.8] } } }
          feature {
            key: "image/detection/bbox/xmax"
            value { float_list { value: [1.0, 0.9] } } }
          feature {
            key: "image/detection/label"
            value { int64_list { value: [123, 246] } } }
          feature {
            key: "image/detection/score"
            value { float_list { value: [0.1, 0.2] } } }
          feature {
            key: "image/encoded"
            value { bytes_list { value:
              "\211PNG\r\n\032\n\000\000\000\rIHDR\000\000\000\001\000\000"
              "\000\001\010\002\000\000\000\220wS\336\000\000\000\022IDATx"
              "\234b\250f`\000\000\000\000\377\377\003\000\001u\000|gO\242"
              "\213\000\000\000\000IEND\256B`\202" } } }
          feature {
            key: "test_field"
            value { float_list { value: [1.0, 2.0, 3.0, 4.0] } } } }
    """, tf_example) 
開發者ID:ahmetozlu,項目名稱:vehicle_counting_tensorflow,代碼行數:54,代碼來源:detection_inference_test.py

示例3: test_discard_image

# 需要導入模塊: from object_detection.inference import detection_inference [as 別名]
# 或者: from object_detection.inference.detection_inference import build_inference_graph [as 別名]
def test_discard_image(self):
    create_mock_graph()
    create_mock_tfrecord()

    serialized_example_tensor, image_tensor = detection_inference.build_input(
        [get_mock_tfrecord_path()])
    (detected_boxes_tensor, detected_scores_tensor,
     detected_labels_tensor) = detection_inference.build_inference_graph(
         image_tensor, get_mock_graph_path())

    with self.test_session(use_gpu=False) as sess:
      sess.run(tf.global_variables_initializer())
      sess.run(tf.local_variables_initializer())
      tf.train.start_queue_runners()

      tf_example = detection_inference.infer_detections_and_add_to_example(
          serialized_example_tensor, detected_boxes_tensor,
          detected_scores_tensor, detected_labels_tensor, True)

    self.assertProtoEquals(r"""
        features {
          feature {
            key: "image/detection/bbox/ymin"
            value { float_list { value: [0.0, 0.1] } } }
          feature {
            key: "image/detection/bbox/xmin"
            value { float_list { value: [0.8, 0.2] } } }
          feature {
            key: "image/detection/bbox/ymax"
            value { float_list { value: [0.7, 0.8] } } }
          feature {
            key: "image/detection/bbox/xmax"
            value { float_list { value: [1.0, 0.9] } } }
          feature {
            key: "image/detection/label"
            value { int64_list { value: [123, 246] } } }
          feature {
            key: "image/detection/score"
            value { float_list { value: [0.1, 0.2] } } }
          feature {
            key: "test_field"
            value { float_list { value: [1.0, 2.0, 3.0, 4.0] } } } }
    """, tf_example) 
開發者ID:ahmetozlu,項目名稱:vehicle_counting_tensorflow,代碼行數:45,代碼來源:detection_inference_test.py


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