我有这个问题,我在 google colab 中使用 tensorflow 2,我相信该错误与配置文件中的路径有关。我使用了“./”和“//”,我也给出了完整路径,但我无法摆脱这个错误。
<块引用>tensorflow.python.framework.errors_impl.NotFoundError:不成功 TensorSliceReader 构造函数:找不到任何匹配的文件 /content/models/research/object_detection/centernet_resnet50_v1_fpn_512x512_coco17_tpu-8/model.ckpt
我修改了配置文件
# CenterNet meta-architecture from the "Objects as Points" [1] paper
# with the ResNet-v2-101 backbone. The ResNet backbone has a few differences
# as compared to the one mentioned in the paper, hence the performance is
# slightly worse. This config is TPU comptatible.
# [1]: https://arxiv.org/abs/1904.07850
#
model {
center_net {
num_classes: 2
feature_extractor {
type: "resnet_v1_50_fpn"
}
image_resizer {
keep_aspect_ratio_resizer {
min_dimension: 512
max_dimension: 512
pad_to_max_dimension: true
}
}
object_detection_task {
task_loss_weight: 1.0
offset_loss_weight: 1.0
scale_loss_weight: 0.1
localization_loss {
l1_localization_loss {
}
}
}
object_center_params {
object_center_loss_weight: 1.0
min_box_overlap_iou: 0.7
max_box_predictions: 100
classification_loss {
penalty_reduced_logistic_focal_loss {
alpha: 2.0
beta: 4.0
}
}
}
}
}
train_config: {
batch_size: 128
num_steps: 250000
data_augmentation_options {
random_horizontal_flip {
}
}
data_augmentation_options {
random_crop_image {
min_aspect_ratio: 0.5
max_aspect_ratio: 1.7
random_coef: 0.25
}
}
data_augmentation_options {
random_adjust_hue {
}
}
data_augmentation_options {
random_adjust_contrast {
}
}
data_augmentation_options {
random_adjust_saturation {
}
}
data_augmentation_options {
random_adjust_brightness {
}
}
data_augmentation_options {
random_absolute_pad_image {
max_height_padding: 200
max_width_padding: 200
pad_color: [0, 0, 0]
}
}
optimizer {
adam_optimizer: {
epsilon: 1e-7 # Match tf.keras.optimizers.Adam's default.
learning_rate: {
cosine_decay_learning_rate {
learning_rate_base: 1e-3
total_steps: 250000
warmup_learning_rate: 2.5e-4
warmup_steps: 5000
}
}
}
use_moving_average: false
}
max_number_of_boxes: 100
unpad_groundtruth_tensors: false
fine_tune_checkpoint_version: V2
fine_tune_checkpoint: "/content/models/research/object_detection/centernet_resnet50_v1_fpn_512x512_coco17_tpu-8/model.ckpt"
fine_tune_checkpoint_type: "classification"
}
train_input_reader: {
label_map_path: "/content/models/research/object_detection/training/labelmap.pbtxt"
tf_record_input_reader {
input_path: "/content/models/research/object_detection/train.record"
}
}
eval_config: {
metrics_set: "coco_detection_metrics"
use_moving_averages: false
batch_size: 1;
}
eval_input_reader: {
label_map_path: "/content/models/research/object_detection/training/labelmap.pbtxt"
shuffle: false
num_epochs: 1
tf_record_input_reader {
input_path: "/content/models/research/object_detection/test.record"
}
}
答案 0 :(得分:0)
问题出在模型上,我在其配置管道文件中使用了不同的模型,并且可以正常工作。