tflite_model_maker if obj['困难'] == '未指定'：KeyError：'困难'

Question

我正在尝试仅使用 coco 数据集中的人来训练 tflite 模型。 我正在使用 tflite 模型制作器来训练，并使用五十一来处理数据集。

运行训练文件 .py 时出现以下错误。

root@85ac26b47f92:/external# root@85ac26b47f92:/external# python demofie.py
2022-11-01 21:02:01.059188: E tensorflow/stream_executor/cuda/cuda_driver.cc:271] failed call to cuInit: UNKNOWN ERROR (34)
2022-11-01 21:02:01.059234: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: 85ac26b47f92
2022-11-01 21:02:01.059242: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: 85ac26b47f92
2022-11-01 21:02:01.059324: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: NOT_FOUND: was unable to find libcuda.so DSO loaded into this program
2022-11-01 21:02:01.059381: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 470.141.3
2022-11-01 21:02:01.059821: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Traceback (most recent call last):
  File "demofie.py", line 20, in <module>
    train_data = object_detector.DataLoader.from_pascal_voc(images_dir='/external/train/data',annotations_dir='/external/train/labels', label_map=['person'],ignore_difficult_instances= False,num_shards = 100)
  File "/usr/local/lib/python3.8/dist-packages/tensorflow_examples/lite/model_maker/core/data_util/object_detector_dataloader.py", line 217, in from_pascal_voc
    cache_writer.write_files(
  File "/usr/local/lib/python3.8/dist-packages/tensorflow_examples/lite/model_maker/core/data_util/object_detector_dataloader_util.py", line 252, in write_files
    tf_example = create_pascal_tfrecord.dict_to_tf_example(
  File "/usr/local/lib/python3.8/dist-packages/tensorflow_examples/lite/model_maker/third_party/efficientdet/dataset/create_pascal_tfrecord.py", line 162, in dict_to_tf_example
    if obj['difficult'] == 'Unspecified':
KeyError: 'difficult'

导致错误的代码。任何比我拥有更好编码知识的人都可以阐明我可能犯的任何错误吗？ 我在下面添加了五十一个代码（没有错误）

import numpy as np
import os

from tflite_model_maker.config import QuantizationConfig
from tflite_model_maker.config import ExportFormat
from tflite_model_maker import model_spec
from tflite_model_maker import object_detector

import tensorflow as tf
assert tf.__version__.startswith('2')

tf.get_logger().setLevel('ERROR')
from absl import logging
logging.set_verbosity(logging.ERROR)


spec = model_spec.get('efficientdet_lite1')


train_data = object_detector.DataLoader.from_pascal_voc(images_dir='/external/train/data',annotations_dir='/external/train/labels', label_map=['person'],ignore_difficult_instances= False,num_shards = 100)

validation_data = object_detector.DataLoader.from_pascal_voc(images_dir='/external/val/data',annotations_dir='/external/val/labels',label_map= ['person'],ignore_difficult_instances= False,num_shards = 100)

test_data = object_detector.DataLoader.from_pascal_voc(images_dir='/external/test/data',annotations_dir='/external/test/labels',label_map= ['person'],ignore_difficult_instances= False,num_shards = 100)


model = object_detector.create(train_data, model_spec=spec, batch_size=8,epochs=2000, train_whole_model=True, validation_data=validation_data)



model.evaluate(test_data)



model.export(export_dir='/external/')

**数据集生成代码 **

import fiftyone.zoo as foz
import fiftyone as fo
from fiftyone import ViewField as F


cocodataset_test = foz.load_zoo_dataset(
    "coco-2017",
    splits="test",
    label_types=["detections"],
    classes=["person"],
    only_matching=True,
    # max_samples=50,
)
cocodataset_validation = foz.load_zoo_dataset(
    "coco-2017",
    splits="validation",
    label_types=["detections"],
    classes=["person"],
    only_matching=True,
    # max_samples=50
)

cocodataset_train = foz.load_zoo_dataset(
    "coco-2017",
    splits="train",
    label_types=["detections"],
    classes=["person"],
    only_matching=True,
    # max_samples=50,
)


cocodataset_validation.export(
    '/external/val',
    fo.types.VOCDetectionDataset,
)
cocodataset_train.export(
    '/external/train/',
    fo.types.VOCDetectionDataset,
)
cocodataset_test.export(
    '/external/test/',
    fo.types.VOCDetectionDataset,
)

Answer 1

voc 数据集在导出之前需要一些附加属性：

    values = dataset.values("ground_truth.detections")
    for detections in values:
        if detections:
            for d in detections:
                d.set_attribute_value("difficult", "Unspecified")
                d.set_attribute_value("truncated", "Unspecified")
                d.set_attribute_value("pose", "Unspecified")
    dataset.set_values("ground_truth.detections", values)