我正在尝试将Aleju的Imgaug-to-TFOD API实现。注意到在图形模式下不能迭代张量。我查找了解决方案，并尝试了许多建议，但都不适用于我的情况。你知道附近有什么工作吗？
import imgaug.augmenters as iaa
from imgaug.augmentables.bbs import BoundingBox, BoundingBoxesOnImage
from tensorflow.python.framework.ops import EagerTensor
import tensorflow.compat.v1 as tf
import numpy as np
augseq = iaa.Sequential([# augmentation options], random_order=True)
@tf.function
def augment(image, boxes):
image_np = image.numpy().astype(np.uint8) if type(image) == EagerTensor else image
boxes_np = boxes.numpy() if type(boxes) == EagerTensor else boxes
width, height, _ = image_np.shape
bbs = []
for i in range(len(boxes_np)):
box = boxes_np[i]
ymin, xmin, ymax, xmax = box.numpy()
bbs.append(BoundingBox(
x1=xmin*width, y1=ymin*height,
x2=xmax*width, y2=ymax*height,))
bbs = BoundingBoxesOnImage(bbs, shape=image_np.shape)
image_aug, bbs_aug = augseq(image=image_np, bounding_boxes=bbs) # float np.ndarray
bbs_aug = bbs_aug.remove_out_of_image().clip_out_of_image()
boxes_aug = []
for bb in bbs_aug:
boxes_aug.append([bb.y1/height, bb.x1/width, bb.y2/height, bb.x2/width])
boxes_aug = np.array(boxes_aug)
return image_aug, boxes_aug
堆栈跟踪：
raceback (most recent call last):
File "/content/models/research/object_detection/model_main_tf2.py", line 115, in <module>
tf.compat.v1.app.run()
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/platform/app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "/usr/local/lib/python3.7/dist-packages/absl/app.py", line 303, in run
_run_main(main, args)
File "/usr/local/lib/python3.7/dist-packages/absl/app.py", line 251, in _run_main
sys.exit(main(argv))
File "/content/models/research/object_detection/model_main_tf2.py", line 112, in main
record_summaries=FLAGS.record_summaries)
File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 558, in train_loop
train_dataset_fn)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/util/deprecation.py", line 348, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py", line 1199, in experimental_distribute_datasets_from_function
return self.distribute_datasets_from_function(dataset_fn, options)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py", line 1191, in distribute_datasets_from_function
dataset_fn, options)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/tpu_strategy.py", line 979, in _distribute_datasets_from_function
options=options)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/input_lib.py", line 181, in get_distributed_datasets_from_function
build=build,
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/input_lib.py", line 1618, in __init__
self.build()
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/input_lib.py", line 1639, in build
self._input_contexts, self._input_workers, self._dataset_fn))
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/input_lib.py", line 2350, in _create_datasets_from_function_with_input_context
dataset = dataset_fn(ctx)
File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 553, in train_dataset_fn
input_context=input_context)
File "/usr/local/lib/python3.7/dist-packages/object_detection/inputs.py", line 906, in train_input
reduce_to_frame_fn=reduce_to_frame_fn)
File "/usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py", line 258, in build
batch_size, input_reader_config)
File "/usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py", line 237, in dataset_map_fn
fn_to_map, num_parallel_calls=num_parallel_calls)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/util/deprecation.py", line 348, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 3886, in map_with_legacy_function
use_legacy_function=True))
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 5505, in __init__
use_legacy_function=use_legacy_function)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 4540, in __init__
self._function.add_to_graph(ops.get_default_graph())
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/function.py", line 544, in add_to_graph
self._create_definition_if_needed()
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/function.py", line 380, in _create_definition_if_needed
self._create_definition_if_needed_impl()
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/function.py", line 407, in _create_definition_if_needed_impl
capture_resource_var_by_value=self._capture_resource_var_by_value)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/function.py", line 970, in func_graph_from_py_func
outputs = func(*func_graph.inputs)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 4458, in wrapped_fn
ret = wrapper_helper(*args)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 4440, in wrapper_helper
ret = autograph.tf_convert(self._func, ag_ctx)(*nested_args)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py", line 699, in wrapper
raise e.ag_error_metadata.to_exception(e)
AttributeError: in user code:
File "/usr/local/lib/python3.7/dist-packages/object_detection/inputs.py", line 886, in transform_and_pad_input_data_fn *
tensor_dict = pad_input_data_to_static_shapes(
File "/usr/local/lib/python3.7/dist-packages/object_detection/inputs.py", line 272, in transform_input_data *
out_tensor_dict = data_augmentation_fn(out_tensor_dict)
File "/usr/local/lib/python3.7/dist-packages/object_detection/inputs.py", line 623, in augment_input_data *
tensor_dict = preprocessor.preprocess(
File "/usr/local/lib/python3.7/dist-packages/object_detection/core/preprocessor.py", line 4812, in preprocess *
results = func(*args, **params)
File "/usr/local/lib/python3.7/dist-packages/object_detection/core/preprocessor.py", line 4422, in _adjust_imgaug *
adjusted_image, adjusted_boxes = tf.cast(imgaug_utils.augment(image,boxes), tf.float32)
File "/usr/local/lib/python3.7/dist-packages/object_detection/core/imgaug_utils.py", line 24, in augment *
ymin, xmin, ymax, xmax = box.numpy()
AttributeError: 'Tensor' object has no attribute 'numpy'
以下是我尝试过但没有成功的：
- 启用紧急执行(这是tf 2.x中的默认值(
- 使用@tf.function装饰/不装饰功能
- 创建Tf会话并尝试eval((或run((：
- InvalidArgumentError：必须为dtype为int32的占位符张量"while/placeholder"提供值
- 在TPU和CPU上都尝试过
现在存在tf.range((
的简要示例
# here is a 3d tensor.
x = tf.convert_to_tensor(np.array([[1,1],[1,1],[1,1]],[[2,2],[2,2],[2,2]]))
#Now loop over its largest parts
length = x.shape[0]
for n in tf.range(length):
do_some_naugty_things(x[n])