I'm trying to run the infer script from the "simple usage" section of the documentation, but I keep getting the following error:
"FileNotFoundError: [Errno 2] No such file or directory: 'data/LEVIR-CD/test/A'". (Full terminal log included below).
For refrence, I'm on an M1 mac and I believe have the correct versions of all of the dependencies installed. I've tried creating a directory named data in the "datasets" directory, and populating it with a copy of the LEVIR-CD dataset I downloaded online. No such luck, even though I can cd into the directory that my computer is convinced doesn't exist. I suspect there's an issue with the file_list_from and file_list_two variables, as printing them both directly gives pointers to the same memory address and trying to print as a list gives the same error. (Short snippet included below, everything else in the error message is the exact same):
File "/Users/cole/Desktop/work/rapid_change_detection/open-cd/opencd/datasets/basecddataset.py", line 269, in load_data_list
print(list(file_list_to)).
I can attach my virtual environment if relevant. Would be extraordinarily grateful for any help anyone could provide, whether a fix for the error or just if anyone has gotten this working on an m1 mac please contact me.
Terminal output attached below
(opencd) cole@MacBook-Pro-6 open-cd % python tools/test.py configs/changer/changer_ex_r18_512x512_40k_levircd.py changer_r18_levir_workdir/latest.pth --show-dir tmp_infer
06/18 21:36:48 - mmengine - INFO -
System environment:
sys.platform: darwin
Python: 3.10.11 | packaged by conda-forge | (main, May 10 2023, 19:01:19) [Clang 14.0.6 ]
CUDA available: False
numpy_random_seed: 1230368365
GCC: Apple clang version 14.0.3 (clang-1403.0.22.14.1)
PyTorch: 2.0.1
PyTorch compiling details: PyTorch built with:
-
GCC 4.2
-
C++ Version: 201703
-
clang 13.1.6
-
LAPACK is enabled (usually provided by MKL)
-
NNPACK is enabled
-
CPU capability usage: NO AVX
-
Build settings: BLAS_INFO=accelerate, BUILD_TYPE=Release, CXX_COMPILER=/Applications/Xcode_13.3.1.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -Wno-deprecated-declarations -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DLIBKINETO_NOROCTRACER -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_PYTORCH_METAL_EXPORT -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DUSE_COREML_DELEGATE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=braced-scalar-init -Werror=range-loop-construct -Werror=bool-operation -Winconsistent-missing-override -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wvla-extension -Wno-range-loop-analysis -Wno-pass-failed -Wsuggest-override -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -Wconstant-conversion -Wno-invalid-partial-specialization -Wno-typedef-redefinition -Wno-unused-private-field -Wno-inconsistent-missing-override -Wno-constexpr-not-const -Wno-missing-braces -Wunused-lambda-capture -Wunused-local-typedef -Qunused-arguments -fcolor-diagnostics -fdiagnostics-color=always -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -DUSE_MPS -fno-objc-arc -Wno-unguarded-availability-new -Wno-unused-private-field -Wno-missing-braces -Wno-constexpr-not-const, LAPACK_INFO=accelerate, TORCH_DISABLE_GPU_ASSERTS=OFF, TORCH_VERSION=2.0.1, USE_CUDA=OFF, USE_CUDNN=OFF, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=ON, USE_OPENMP=OFF, USE_ROCM=OFF,
TorchVision: 0.15.2
OpenCV: 4.7.0
MMEngine: 0.7.4
Runtime environment:
cudnn_benchmark: True
mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0}
dist_cfg: {'backend': 'nccl'}
seed: 1230368365
Distributed launcher: none
Distributed training: False
GPU number: 1
06/18 21:36:48 - mmengine - INFO - Config:
norm_cfg = dict(type='SyncBN', requires_grad=True)
data_preprocessor = dict(
type='DualInputSegDataPreProcessor',
mean=[123.675, 116.28, 103.53, 123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375, 58.395, 57.12, 57.375],
bgr_to_rgb=True,
size_divisor=32,
pad_val=0,
seg_pad_val=255,
test_cfg=dict(size_divisor=32))
model = dict(
type='DIEncoderDecoder',
data_preprocessor=dict(
type='DualInputSegDataPreProcessor',
mean=[123.675, 116.28, 103.53, 123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375, 58.395, 57.12, 57.375],
bgr_to_rgb=True,
size_divisor=32,
pad_val=0,
seg_pad_val=255,
test_cfg=dict(size_divisor=32)),
pretrained=None,
backbone=dict(
type='IA_ResNetV1c',
depth=18,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 1, 1),
strides=(1, 2, 2, 2),
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
style='pytorch',
contract_dilation=True,
interaction_cfg=(None, {
'type': 'SpatialExchange',
'p': 0.5
}, {
'type': 'ChannelExchange',
'p': 0.5
}, {
'type': 'ChannelExchange',
'p': 0.5
})),
decode_head=dict(
type='Changer',
in_channels=[64, 128, 256, 512],
in_index=[0, 1, 2, 3],
channels=128,
dropout_ratio=0.1,
num_classes=2,
norm_cfg=dict(type='SyncBN', requires_grad=True),
align_corners=False,
loss_decode=dict(
type='mmseg.CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
sampler=dict(
type='mmseg.OHEMPixelSampler', thresh=0.7, min_kept=100000)),
train_cfg=dict(),
test_cfg=dict(mode='whole'))
default_scope = 'opencd'
env_cfg = dict(
cudnn_benchmark=True,
mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
dist_cfg=dict(backend='nccl'))
vis_backends = [dict(type='CDLocalVisBackend')]
visualizer = dict(
type='CDLocalVisualizer',
vis_backends=[dict(type='CDLocalVisBackend')],
name='visualizer',
alpha=1.0,
save_dir='tmp_infer')
log_processor = dict(by_epoch=False)
log_level = 'INFO'
load_from = 'changer_r18_levir_workdir/latest.pth'
resume = False
tta_model = dict(type='mmseg.SegTTAModel')
dataset_type = 'LEVIR_CD_Dataset'
data_root = 'data/LEVIR-CD'
crop_size = (512, 512)
train_pipeline = [
dict(type='MultiImgLoadImageFromFile'),
dict(type='MultiImgLoadAnnotations'),
dict(
type='MultiImgRandomRotFlip',
rotate_prob=0.5,
flip_prob=0.5,
degree=(-20, 20)),
dict(type='MultiImgRandomCrop', crop_size=(512, 512), cat_max_ratio=0.75),
dict(type='MultiImgExchangeTime', prob=0.5),
dict(
type='MultiImgPhotoMetricDistortion',
brightness_delta=10,
contrast_range=(0.8, 1.2),
saturation_range=(0.8, 1.2),
hue_delta=10),
dict(type='MultiImgPackSegInputs')
]
test_pipeline = [
dict(type='MultiImgLoadImageFromFile'),
dict(type='MultiImgResize', scale=(1024, 1024), keep_ratio=True),
dict(type='MultiImgLoadAnnotations'),
dict(type='MultiImgPackSegInputs')
]
img_ratios = [0.75, 1.0, 1.25]
tta_pipeline = [
dict(type='MultiImgLoadImageFromFile', backend_args=None),
dict(
type='TestTimeAug',
transforms=[[{
'type': 'MultiImgResize',
'scale_factor': 0.75,
'keep_ratio': True
}, {
'type': 'MultiImgResize',
'scale_factor': 1.0,
'keep_ratio': True
}, {
'type': 'MultiImgResize',
'scale_factor': 1.25,
'keep_ratio': True
}],
[{
'type': 'MultiImgRandomFlip',
'prob': 0.0,
'direction': 'horizontal'
}, {
'type': 'MultiImgRandomFlip',
'prob': 1.0,
'direction': 'horizontal'
}], [{
'type': 'MultiImgLoadAnnotations'
}], [{
'type': 'MultiImgPackSegInputs'
}]])
]
train_dataloader = dict(
batch_size=8,
num_workers=4,
persistent_workers=True,
sampler=dict(type='InfiniteSampler', shuffle=True),
dataset=dict(
type='LEVIR_CD_Dataset',
data_root='data/LEVIR-CD',
data_prefix=dict(
seg_map_path='train/label',
img_path_from='train/A',
img_path_to='train/B'),
pipeline=[
dict(type='MultiImgLoadImageFromFile'),
dict(type='MultiImgLoadAnnotations'),
dict(
type='MultiImgRandomRotFlip',
rotate_prob=0.5,
flip_prob=0.5,
degree=(-20, 20)),
dict(
type='MultiImgRandomCrop',
crop_size=(512, 512),
cat_max_ratio=0.75),
dict(type='MultiImgExchangeTime', prob=0.5),
dict(
type='MultiImgPhotoMetricDistortion',
brightness_delta=10,
contrast_range=(0.8, 1.2),
saturation_range=(0.8, 1.2),
hue_delta=10),
dict(type='MultiImgPackSegInputs')
]))
val_dataloader = dict(
batch_size=1,
num_workers=4,
persistent_workers=True,
sampler=dict(type='DefaultSampler', shuffle=False),
dataset=dict(
type='LEVIR_CD_Dataset',
data_root='data/LEVIR-CD',
data_prefix=dict(
seg_map_path='val/label',
img_path_from='val/A',
img_path_to='val/B'),
pipeline=[
dict(type='MultiImgLoadImageFromFile'),
dict(type='MultiImgResize', scale=(1024, 1024), keep_ratio=True),
dict(type='MultiImgLoadAnnotations'),
dict(type='MultiImgPackSegInputs')
]))
test_dataloader = dict(
batch_size=1,
num_workers=4,
persistent_workers=True,
sampler=dict(type='DefaultSampler', shuffle=False),
dataset=dict(
type='LEVIR_CD_Dataset',
data_root='data/LEVIR-CD',
data_prefix=dict(
seg_map_path='test/label',
img_path_from='test/A',
img_path_to='test/B'),
pipeline=[
dict(type='MultiImgLoadImageFromFile'),
dict(type='MultiImgResize', scale=(1024, 1024), keep_ratio=True),
dict(type='MultiImgLoadAnnotations'),
dict(type='MultiImgPackSegInputs')
]))
val_evaluator = dict(type='mmseg.IoUMetric', iou_metrics=['mFscore', 'mIoU'])
test_evaluator = dict(type='mmseg.IoUMetric', iou_metrics=['mFscore', 'mIoU'])
optimizer = dict(type='AdamW', lr=0.005, betas=(0.9, 0.999), weight_decay=0.05)
optim_wrapper = dict(
type='OptimWrapper',
optimizer=dict(
type='AdamW', lr=0.005, betas=(0.9, 0.999), weight_decay=0.05))
param_scheduler = [
dict(
type='LinearLR', start_factor=1e-06, by_epoch=False, begin=0,
end=1000),
dict(
type='PolyLR',
power=1.0,
begin=1000,
end=40000,
eta_min=0.0,
by_epoch=False)
]
train_cfg = dict(type='IterBasedTrainLoop', max_iters=40000, val_interval=4000)
val_cfg = dict(type='ValLoop')
test_cfg = dict(type='TestLoop')
default_hooks = dict(
timer=dict(type='IterTimerHook'),
logger=dict(type='LoggerHook', interval=50, log_metric_by_epoch=False),
param_scheduler=dict(type='ParamSchedulerHook'),
checkpoint=dict(
type='CheckpointHook', by_epoch=False, interval=4000,
save_best='mIoU'),
sampler_seed=dict(type='DistSamplerSeedHook'),
visualization=dict(
type='CDVisualizationHook',
interval=1,
img_shape=(1024, 1024, 3),
draw=True))
launcher = 'none'
work_dir = './work_dirs/changer_ex_r18_512x512_40k_levircd'
/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmseg/models/decode_heads/decode_head.py:120: UserWarning: For binary segmentation, we suggest usingout_channels = 1 to define the outputchannels of segmentor, and use thresholdto convert seg_logits into a predictionapplying a threshold
warnings.warn('For binary segmentation, we suggest using'
/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmseg/models/builder.py:36: UserWarning: build_loss would be deprecated soon, please use mmseg.registry.MODELS.build()
warnings.warn('build_loss would be deprecated soon, please use '
/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmseg/models/losses/cross_entropy_loss.py:235: UserWarning: Default avg_non_ignore is False, if you would like to ignore the certain label and average loss over non-ignore labels, which is the same with PyTorch official cross_entropy, set avg_non_ignore=True.
warnings.warn(
/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmseg/structures/sampler/builder.py:11: UserWarning: build_pixel_sampler would be deprecated soon, please use mmseg.registry.TASK_UTILS.build()
warnings.warn(
06/18 21:36:48 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used.
06/18 21:36:48 - mmengine - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH ) RuntimeInfoHook
(BELOW_NORMAL) LoggerHook
before_train:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(VERY_LOW ) CheckpointHook
before_train_epoch:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(NORMAL ) DistSamplerSeedHook
before_train_iter:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
after_train_iter:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(NORMAL ) CDVisualizationHook
(BELOW_NORMAL) LoggerHook
(LOW ) ParamSchedulerHook
(VERY_LOW ) CheckpointHook
after_train_epoch:
(NORMAL ) IterTimerHook
(LOW ) ParamSchedulerHook
(VERY_LOW ) CheckpointHook
before_val_epoch:
(NORMAL ) IterTimerHook
before_val_iter:
(NORMAL ) IterTimerHook
after_val_iter:
(NORMAL ) IterTimerHook
(NORMAL ) CDVisualizationHook
(BELOW_NORMAL) LoggerHook
after_val_epoch:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(BELOW_NORMAL) LoggerHook
(LOW ) ParamSchedulerHook
(VERY_LOW ) CheckpointHook
after_train:
(VERY_LOW ) CheckpointHook
before_test_epoch:
(NORMAL ) IterTimerHook
before_test_iter:
(NORMAL ) IterTimerHook
after_test_iter:
(NORMAL ) IterTimerHook
(NORMAL ) CDVisualizationHook
(BELOW_NORMAL) LoggerHook
after_test_epoch:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(BELOW_NORMAL) LoggerHook
after_run:
(BELOW_NORMAL) LoggerHook
Traceback (most recent call last):
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/registry/build_functions.py", line 122, in build_from_cfg
obj = obj_cls(**args) # type: ignore
File "/Users/cole/Desktop/work/rapid_change_detection/open-cd/opencd/datasets/levir_cd.py", line 18, in init
super().init(
File "/Users/cole/Desktop/work/rapid_change_detection/open-cd/opencd/datasets/basecddataset.py", line 141, in init
self.full_init()
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/dataset/base_dataset.py", line 296, in full_init
self.data_list = self.load_data_list()
File "/Users/cole/Desktop/work/rapid_change_detection/open-cd/opencd/datasets/basecddataset.py", line 270, in load_data_list
assert sorted(list(file_list_from)) == sorted(list(file_list_to)),
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/fileio/io.py", line 760, in list_dir_or_file
yield from backend.list_dir_or_file(dir_path, list_dir, list_file, suffix,
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/fileio/backends/local_backend.py", line 527, in _list_dir_or_file
for entry in os.scandir(dir_path):
FileNotFoundError: [Errno 2] No such file or directory: 'data/LEVIR-CD/test/A'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/registry/build_functions.py", line 122, in build_from_cfg
obj = obj_cls(**args) # type: ignore
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/runner/loops.py", line 410, in init
super().init(runner, dataloader)
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/runner/base_loop.py", line 26, in init
self.dataloader = runner.build_dataloader(
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/runner/runner.py", line 1346, in build_dataloader
dataset = DATASETS.build(dataset_cfg)
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/registry/registry.py", line 548, in build
return self.build_func(cfg, *args, **kwargs, registry=self)
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/registry/build_functions.py", line 144, in build_from_cfg
raise type(e)(
FileNotFoundError: class LEVIR_CD_Dataset in opencd/datasets/levir_cd.py: [Errno 2] No such file or directory: 'data/LEVIR-CD/test/A'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/cole/Desktop/work/rapid_change_detection/open-cd/tools/test.py", line 114, in
main()
File "/Users/cole/Desktop/work/rapid_change_detection/open-cd/tools/test.py", line 110, in main
runner.test()
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/runner/runner.py", line 1760, in test
self._test_loop = self.build_test_loop(self._test_loop) # type: ignore
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/runner/runner.py", line 1563, in build_test_loop
loop = LOOPS.build(
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/registry/registry.py", line 548, in build
return self.build_func(cfg, *args, **kwargs, registry=self)
File "/opt/homebrew/anaconda3/envs/opencd/lib/python3.10/site-packages/mmengine/registry/build_functions.py", line 144, in build_from_cfg
raise type(e)(
FileNotFoundError: class TestLoop in mmengine/runner/loops.py: class LEVIR_CD_Dataset in opencd/datasets/levir_cd.py: [Errno 2] No such file or directory: 'data/LEVIR-CD/test/A'
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