我一直在尝试将tensorflow的对象检测api用于学校项目，我已经设法按照他们在文档中的说明进行操作，但我收到此错误，我无法在网上找到任何地方。这是控制台中的输出：
WARNING:tensorflow:Forced number of epochs for all eval validations to be 1.
WARNING:tensorflow:Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.
WARNING:tensorflow:Estimator's model_fn (<function create_model_fn.<locals>.model_fn at 0x7f118aa30e18>) includes params argument, but params are not passed to Estimator.
WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.
WARNING:tensorflow:From /home/pipas/School/tensorflow-models/research/object_detection/builders/dataset_builder.py:80: parallel_interleave (from tensorflow.contrib.data.python.ops.interleave_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.experimental.parallel_interleave(...)`.
WARNING:tensorflow:From /home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/ops/sparse_ops.py:1165: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.
WARNING:tensorflow:From /home/pipas/School/tensorflow-models/research/object_detection/core/preprocessor.py:1218: calling squeeze (from tensorflow.python.ops.array_ops) with squeeze_dims is deprecated and will be removed in a future version.
Instructions for updating:
Use the `axis` argument instead
WARNING:tensorflow:From /home/pipas/School/tensorflow-models/research/object_detection/builders/dataset_builder.py:148: batch_and_drop_remainder (from tensorflow.contrib.data.python.ops.batching) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.Dataset.batch(..., drop_remainder=True)`.
2018-12-28 19:39:31.314235: E tensorflow/core/util/events_writer.cc:108] Write failed because file could not be opened.
2018-12-28 19:39:32.354316: E tensorflow/core/util/events_writer.cc:108] Write failed because file could not be opened.
2018-12-28 19:39:33.177681: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-12-28 19:39:33.246316: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:964] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-12-28 19:39:33.246780: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties:
name: GeForce GTX 960M major: 5 minor: 0 memoryClockRate(GHz): 1.176
pciBusID: 0000:01:00.0
totalMemory: 3.95GiB freeMemory: 3.59GiB
2018-12-28 19:39:33.246813: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
2018-12-28 19:39:33.798306: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-12-28 19:39:33.798331: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
2018-12-28 19:39:33.798337: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
2018-12-28 19:39:33.798491: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3310 MB memory) -> physical GPU (device: 0, name: GeForce GTX 960M, pci bus id: 0000:01:00.0, compute capability: 5.0)
Traceback (most recent call last):
File "object_detection/model_main.py", line 109, in <module>
tf.app.run()
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "object_detection/model_main.py", line 105, in main
tf.estimator.train_and_evaluate(estimator, train_spec, eval_specs[0])
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/estimator/training.py", line 471, in train_and_evaluate
return executor.run()
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/estimator/training.py", line 610, in run
return self.run_local()
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/estimator/training.py", line 711, in run_local
saving_listeners=saving_listeners)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 354, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 1207, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 1241, in _train_model_default
saving_listeners)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 1468, in _train_with_estimator_spec
log_step_count_steps=log_step_count_steps) as mon_sess:
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/training/monitored_session.py", line 504, in MonitoredTrainingSession
stop_grace_period_secs=stop_grace_period_secs)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/training/monitored_session.py", line 921, in __init__
stop_grace_period_secs=stop_grace_period_secs)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/training/monitored_session.py", line 643, in __init__
self._sess = _RecoverableSession(self._coordinated_creator)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/training/monitored_session.py", line 1107, in __init__
_WrappedSession.__init__(self, self._create_session())
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/training/monitored_session.py", line 1112, in _create_session
return self._sess_creator.create_session()
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/training/monitored_session.py", line 807, in create_session
hook.after_create_session(self.tf_sess, self.coord)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/training/basic_session_run_hooks.py", line 559, in after_create_session
"graph.pbtxt")
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/framework/graph_io.py", line 71, in write_graph
text_format.MessageToString(graph_def))
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/lib/io/file_io.py", line 434, in atomic_write_string_to_file
write_string_to_file(temp_pathname, contents)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/lib/io/file_io.py", line 314, in write_string_to_file
f.write(file_content)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/lib/io/file_io.py", line 108, in write
self._prewrite_check()
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/lib/io/file_io.py", line 94, in _prewrite_check
compat.as_bytes(self.__name), compat.as_bytes(self.__mode), status)
File "/home/pipas/.pyenv/versions/vcom/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 528, in __exit__
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.FailedPreconditionError: /home/pipas/School/tensorflow-models/research/porto-recognition/data/labels.pbtxt/graph.pbtxt.tmp13ac703bc82a469eaec2c658091efd80; Not a directory
这就是我正在运行的
PIPELINE_CONFIG_PATH=/home/pipas/School/tensorflow-models/research/porto-recognition/models/ssd_mobilenet_v1_coco_2018_01_28/pipeline.config
MODEL_DIR=/home/pipas/School/tensorflow-models/research/porto-recognition/data/labels.pbtxt
NUM_TRAIN_STEPS=5000
SAMPLE_1_OF_N_EVAL_EXAMPLES=1
python object_detection/model_main.py \
--pipeline_config_path=${PIPELINE_CONFIG_PATH} \
--model_dir=${MODEL_DIR} \
--num_train_steps=${NUM_TRAIN_STEPS} \
--sample_1_of_n_eval_examples=$SAMPLE_1_OF_N_EVAL_EXAMPLES \
--alsolog
这是pipeline.config文件
model {
ssd {
num_classes: 5
image_resizer {
fixed_shape_resizer {
height: 300
width: 300
}
}
feature_extractor {
type: "ssd_mobilenet_v1"
depth_multiplier: 1.0
min_depth: 16
conv_hyperparams {
regularizer {
l2_regularizer {
weight: 3.99999989895e-05
}
}
initializer {
truncated_normal_initializer {
mean: 0.0
stddev: 0.0299999993294
}
}
activation: RELU_6
batch_norm {
decay: 0.999700009823
center: true
scale: true
epsilon: 0.0010000000475
train: true
}
}
}
box_coder {
faster_rcnn_box_coder {
y_scale: 10.0
x_scale: 10.0
height_scale: 5.0
width_scale: 5.0
}
}
matcher {
argmax_matcher {
matched_threshold: 0.5
unmatched_threshold: 0.5
ignore_thresholds: false
negatives_lower_than_unmatched: true
force_match_for_each_row: true
}
}
similarity_calculator {
iou_similarity {
}
}
box_predictor {
convolutional_box_predictor {
conv_hyperparams {
regularizer {
l2_regularizer {
weight: 3.99999989895e-05
}
}
initializer {
truncated_normal_initializer {
mean: 0.0
stddev: 0.0299999993294
}
}
activation: RELU_6
batch_norm {
decay: 0.999700009823
center: true
scale: true
epsilon: 0.0010000000475
train: true
}
}
min_depth: 0
max_depth: 0
num_layers_before_predictor: 0
use_dropout: false
dropout_keep_probability: 0.800000011921
kernel_size: 1
box_code_size: 4
apply_sigmoid_to_scores: false
}
}
anchor_generator {
ssd_anchor_generator {
num_layers: 6
min_scale: 0.20000000298
max_scale: 0.949999988079
aspect_ratios: 1.0
aspect_ratios: 2.0
aspect_ratios: 0.5
aspect_ratios: 3.0
aspect_ratios: 0.333299994469
}
}
post_processing {
batch_non_max_suppression {
score_threshold: 0.300000011921
iou_threshold: 0.600000023842
max_detections_per_class: 100
max_total_detections: 100
}
score_converter: SIGMOID
}
normalize_loss_by_num_matches: true
loss {
localization_loss {
weighted_smooth_l1 {
}
}
classification_loss {
weighted_sigmoid {
}
}
hard_example_miner {
num_hard_examples: 3000
iou_threshold: 0.990000009537
loss_type: CLASSIFICATION
max_negatives_per_positive: 3
min_negatives_per_image: 0
}
classification_weight: 1.0
localization_weight: 1.0
}
}
}
train_config {
batch_size: 24
data_augmentation_options {
random_horizontal_flip {
}
}
data_augmentation_options {
ssd_random_crop {
}
}
optimizer {
rms_prop_optimizer {
learning_rate {
exponential_decay_learning_rate {
initial_learning_rate: 0.00400000018999
decay_steps: 800720
decay_factor: 0.949999988079
}
}
momentum_optimizer_value: 0.899999976158
decay: 0.899999976158
epsilon: 1.0
}
}
fine_tune_checkpoint: "/home/pipas/School/tensorflow-models/research/porto-recognition/models/ssd_mobilenet_v1_coco_2018_01_28/model.ckpt"
from_detection_checkpoint: true
num_steps: 200000
}
train_input_reader {
label_map_path: "/home/pipas/School/tensorflow-models/research/porto-recognition/data/labels.pbtxt"
tf_record_input_reader {
input_path: "/home/pipas/School/tensorflow-models/research/porto-recognition/data/porto_train.record"
}
}
eval_config {
num_examples: 8000
max_evals: 10
use_moving_averages: false
}
eval_input_reader {
label_map_path: "/home/pipas/School/tensorflow-models/research/porto-recognition/data/labels.pbtxt"
shuffle: false
num_readers: 1
tf_record_input_reader {
input_path: "/home/pipas/School/tensorflow-models/research/porto-recognition/data/porto_val.record"
}
}
你有一个指向你的标签文件的MODEL_DIR，它应该指向一个目录。