fair数据集转换

[lxbcoder]

home/lxb/anaconda3/envs/openmmlab/bin/python /home/lxb/Strip-R-CNN-main/tools/data/fair/fair_to_dota.py
processing images
0it [00:00, ?it/s]
Traceback (most recent call last):
File "/home/lxb/Strip-R-CNN-main/tools/data/fair/fair_to_dota.py", line 71, in
src = sys.argv[1]
IndexError: list index out of range

Process finished with exit code 1
博主，您好，我在tools/data/fair/fair_to_dota.py加入下列代码后出现以上错误

[YXB-NKU]

After you modify these few lines of code, you need to comment them out.

[lxbcoder]

您好，我将上述几行代码注释掉后还是会报以下错误
2025-03-17 15:26:42,312 - mmrotate - INFO - workflow: [('train', 1)], max: 12 epochs
2025-03-17 15:26:42,312 - mmrotate - INFO - Checkpoints will be saved to /home/lxb/Strip-R-CNN-main/work_dir/striprcnnf by HardDiskBackend.
2025-03-17 15:26:44,876 - mmrotate - INFO - Saving checkpoint at 1 epochs
completed: 0, elapsed: 0sTraceback (most recent call last):
File "./tools/train.py", line 198, in
main()
File "./tools/train.py", line 187, in main
train_detector(
File "/home/lxb/Strip-R-CNN-main/mmrotate/apis/train.py", line 154, in train_detector
runner.run(data_loaders, cfg.workflow)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run
epoch_runner(data_loaders[i], **kwargs)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 58, in train
self.call_hook('after_train_epoch')
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/base_runner.py", line 317, in call_hook
getattr(hook, fn_name)(self)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/hooks/evaluation.py", line 271, in after_train_epoch
self._do_evaluate(runner)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/core/evaluation/eval_hooks.py", line 126, in _do_evaluate
results = multi_gpu_test(
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/apis/test.py", line 107, in multi_gpu_test
for i, data in enumerate(data_loader):
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 355, in iter
return self._get_iterator()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 301, in _get_iterator
return _MultiProcessingDataLoaderIter(self)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 940, in init
self._reset(loader, first_iter=True)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 971, in _reset
self._try_put_index()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1205, in _try_put_index
index = self._next_index()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 508, in _next_index
return next(self._sampler_iter) # may raise StopIteration
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/sampler.py", line 227, in iter
for idx in self.sampler:
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/datasets/samplers/distributed_sampler.py", line 47, in iter
math.ceil(self.total_size / len(indices)))[:self.total_size]
ZeroDivisionError: division by zero
Traceback (most recent call last):
File "./tools/train.py", line 198, in
main()
File "./tools/train.py", line 187, in main
train_detector(
File "/home/lxb/Strip-R-CNN-main/mmrotate/apis/train.py", line 154, in train_detector
runner.run(data_loaders, cfg.workflow)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run
epoch_runner(data_loaders[i], **kwargs)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 58, in train
self.call_hook('after_train_epoch')
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/base_runner.py", line 317, in call_hook
getattr(hook, fn_name)(self)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/hooks/evaluation.py", line 271, in after_train_epoch
self._do_evaluate(runner)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/core/evaluation/eval_hooks.py", line 126, in _do_evaluate
results = multi_gpu_test(
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/apis/test.py", line 107, in multi_gpu_test
for i, data in enumerate(data_loader):
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 355, in iter
return self._get_iterator()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 301, in _get_iterator
return _MultiProcessingDataLoaderIter(self)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 940, in init
self._reset(loader, first_iter=True)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 971, in _reset
self._try_put_index()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1205, in _try_put_index
index = self._next_index()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 508, in _next_index
return next(self._sampler_iter) # may raise StopIteration
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/sampler.py", line 227, in iter
for idx in self.sampler:
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/datasets/samplers/distributed_sampler.py", line 47, in iter
math.ceil(self.total_size / len(indices)))[:self.total_size]
ZeroDivisionError: division by zero
Killing subprocess 1424497
Killing subprocess 1424498
Traceback (most recent call last):
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/distributed/launch.py", line 340, in
main()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/distributed/launch.py", line 326, in main
sigkill_handler(signal.SIGTERM, None) # not coming back
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/distributed/launch.py", line 301, in sigkill_handler
raise subprocess.CalledProcessError(returncode=last_return_code, cmd=cmd)
subprocess.CalledProcessError: Command '['/home/lxb/anaconda3/envs/openmmlab/bin/python', '-u', './tools/train.py', '--local_rank=1', 'configs/strip_rcnn/strip_rcnn_s_fpn_1x_fair_le90.py', '--seed', '0', '--launcher', 'pytorch', '--work-dir', 'work_dir/striprcnnf']' returned non-zero exit status 1.

[YXB-NKU]

Do you mean after your dataset conversion is complete, running the strip_rcnn_fair file still result in an error?

[lxbcoder]

是的，博主，我怀疑我没转换正确

[lxbcoder]

输入训练指令时报上述错误

[YXB-NKU]

Place a screenshot of the dataset format after conversion, and show what files are included under the dataset directory.

[lxbcoder]

import os
import cv2
from xml.dom.minidom import parse
from tqdm import tqdm
import sys
import random

def solve_xml(src, tar):
domTree = parse(src)
rootNode = domTree.documentElement
objects = rootNode.getElementsByTagName("objects")[0].getElementsByTagName("object")
box_list=[]
for obj in objects:
name=obj.getElementsByTagName("possibleresult")[0].getElementsByTagName("name")[0].childNodes[0].data
points=obj.getElementsByTagName("points")[0].getElementsByTagName("point")
bbox=[]
for point in points[:4]:
x=point.childNodes[0].data.split(",")[0]
y=point.childNodes[0].data.split(",")[1]
bbox.append(float(x))
bbox.append(float(y))
box_list.append({"name":name, "bbox":bbox})

file=open(tar,'w')
print("imagesource:GoogleEarth",file=file)
print("gsd:0.0",file=file)
for box in box_list:
    ss=""
    for f in box["bbox"]:
        ss+=str(f)+" "
    name=  box["name"]
    name = name.replace(" ", "_")
    ss+=name+" 0"
    print(ss,file=file)
file.close()

def fair_to_dota(in_path, out_path):
os.makedirs(out_path, exist_ok=True)
os.makedirs(os.path.join(out_path, "images"), exist_ok=True)

tasks = []
for root, dirs, files in os.walk(os.path.join(in_path, "images")):
    for f in files:
        src=os.path.join(root, f)
        tar="P"+f[:-4].zfill(4)+".png"
        tar=os.path.join(out_path,"images", tar)
        tasks.append((src, tar))
print("processing images")
for task in tqdm(tasks):
    file = cv2.imread(task[0], 1)
    cv2.imwrite(task[1], file)

if (os.path.exists(os.path.join(in_path, "labelXml"))):
    os.makedirs(os.path.join(out_path, "labelTxt"), exist_ok=True)
    tasks = []
    for root, dirs, files in os.walk(os.path.join(in_path, "labelXml")):
        for f in files:
            src=os.path.join(root, f)
            tar="P"+f[:-4].zfill(4)+".txt"
            tar=os.path.join(out_path,"labelTxt", tar)
            tasks.append((src, tar))
    print("processing labels")
    for task in tqdm(tasks):
        solve_xml(task[0], task[1])

fair_dataset_path="/home/data/dataset/data/fair/train/annfiles/"
dota_dataset_path="/home/data1/dota/train/annfiles/"
fair_to_dota(fair_dataset_path,dota_dataset_path)

这是原始的xml标签

博主您好，好像没有转换成功，转后后文件夹是空的，以上是我的fair-to dota.py文件

[lxbcoder]

还有博主，我的fair训练集和测试集的图片格式都是tif

[YXB-NKU]

Dataset Organization Format

The fair_to_dota function requires the input dataset (located in the in_path directory) to have the following structure:

The in_path/ directory should contain at least two subdirectories:

• images/: A subdirectory containing image files.
• labelXml/: A subdirectory containing label files in XML format (this directory is optional, but if it exists, it will be processed).

The specific structure is as follows:

in_path/
├── images/
│   ├── 1.jpg
│   ├── 2.jpg
│   └── ...
└── labelXml/
    ├── 1.xml
    ├── 2.xml
    └── ...

[jqq-coder]

CUDA_VISIBLE_DEVICES=4,5 PORT=29594 ./tools/dist_train.sh configs/strip_rcnn/strip_rcnn_s_fpn_1x_fair_le90.py 2 --work-dir work_dir/striprcnnfair-2ka-45
您好，博主，fair数据集我已经转换成dota格式了，分别是png和txt，但是我输入上述训练指令后还是会报以下错误2025-03-26 10:38:34,833 - mmrotate - INFO - workflow: [('train', 1)], max: 12 epochs
2025-03-26 10:38:34,833 - mmrotate - INFO - Checkpoints will be saved to /home/lxb/Strip-R-CNN-main/work_dir/striprcnnfair-2ka-45 by HardDiskBackend.
2025-03-26 10:38:37,389 - mmrotate - INFO - Saving checkpoint at 1 epochs
completed: 0, elapsed: 0sTraceback (most recent call last):
File "./tools/train.py", line 198, in
main()
File "./tools/train.py", line 187, in main
train_detector(
File "/home/lxb/Strip-R-CNN-main/mmrotate/apis/train.py", line 154, in train_detector
runner.run(data_loaders, cfg.workflow)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run
epoch_runner(data_loaders[i], **kwargs)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 58, in train
self.call_hook('after_train_epoch')
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/base_runner.py", line 317, in call_hook
getattr(hook, fn_name)(self)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/hooks/evaluation.py", line 271, in after_train_epoch
self._do_evaluate(runner)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/core/evaluation/eval_hooks.py", line 126, in _do_evaluate
results = multi_gpu_test(
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/apis/test.py", line 107, in multi_gpu_test
for i, data in enumerate(data_loader):
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 355, in iter
return self._get_iterator()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 301, in _get_iterator
return _MultiProcessingDataLoaderIter(self)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 940, in init
self._reset(loader, first_iter=True)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 971, in _reset
self._try_put_index()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1205, in _try_put_index
index = self._next_index()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 508, in _next_index
return next(self._sampler_iter) # may raise StopIteration
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/sampler.py", line 227, in iter
for idx in self.sampler:
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/datasets/samplers/distributed_sampler.py", line 47, in iter
math.ceil(self.total_size / len(indices)))[:self.total_size]
ZeroDivisionError: division by zero
Error in atexit._run_exitfuncs:
Traceback (most recent call last):
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/multiprocessing/popen_fork.py", line 27, in poll
pid, sts = os.waitpid(self.pid, flag)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/_utils/signal_handling.py", line 66, in handler
_error_if_any_worker_fails()
RuntimeError: DataLoader worker (pid 2551737) is killed by signal: Terminated.
Traceback (most recent call last):
File "./tools/train.py", line 198, in
main()
File "./tools/train.py", line 187, in main
train_detector(
File "/home/lxb/Strip-R-CNN-main/mmrotate/apis/train.py", line 154, in train_detector
runner.run(data_loaders, cfg.workflow)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run
epoch_runner(data_loaders[i], **kwargs)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 58, in train
self.call_hook('after_train_epoch')
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/base_runner.py", line 317, in call_hook
getattr(hook, fn_name)(self)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/hooks/evaluation.py", line 271, in after_train_epoch
self._do_evaluate(runner)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/core/evaluation/eval_hooks.py", line 126, in _do_evaluate
results = multi_gpu_test(
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/apis/test.py", line 107, in multi_gpu_test
for i, data in enumerate(data_loader):
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 355, in iter
return self._get_iterator()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 301, in _get_iterator
return _MultiProcessingDataLoaderIter(self)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 940, in init
self._reset(loader, first_iter=True)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 971, in _reset
self._try_put_index()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1205, in _try_put_index
index = self._next_index()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 508, in _next_index
return next(self._sampler_iter) # may raise StopIteration
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/sampler.py", line 227, in iter
for idx in self.sampler:
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmdet/datasets/samplers/distributed_sampler.py", line 47, in iter
math.ceil(self.total_size / len(indices)))[:self.total_size]
ZeroDivisionError: division by zero
Killing subprocess 2551495
Killing subprocess 2551496
Traceback (most recent call last):
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/distributed/launch.py", line 340, in
main()
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/distributed/launch.py", line 326, in main
sigkill_handler(signal.SIGTERM, None) # not coming back
File "/home/lxb/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/distributed/launch.py", line 301, in sigkill_handler
raise subprocess.CalledProcessError(returncode=last_return_code, cmd=cmd)
subprocess.CalledProcessError: Command '['/home/lxb/anaconda3/envs/openmmlab/bin/python', '-u', './tools/train.py', '--local_rank=1', 'configs/strip_rcnn/strip_rcnn_s_fpn_1x_fair_le90.py', '--seed', '0', '--launcher', 'pytorch', '--work-dir', 'work_dir/striprcnnfair-2ka-45']' returned non-zero exit status 1.
我的fairv1.py文件如下dataset_type = 'FairDataset'
data_root = '/home/data1/dota/fair/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='RResize', img_scale=(1024, 1024)),
dict(type='RRandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1024, 1024),
flip=False,
transforms=[
dict(type='RResize'),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img'])
])
]
data = dict(
samples_per_gpu=1,
workers_per_gpu=2,
train=dict(
type=dataset_type,
ann_file=data_root + 'train/labelTxt/',
img_prefix=data_root + 'train/images/',
pipeline=train_pipeline),
val=dict(
type=dataset_type,
ann_file=data_root + 'train/labelTxt/',
img_prefix=data_root + 'train/images/',
pipeline=test_pipeline),
test=dict(
type=dataset_type,
ann_file=data_root + 'test/images/',
img_prefix=data_root + 'test/images/',
pipeline=test_pipeline))
希望博主百忙之中可以回答我这个问题

[jqq-coder]

已经转换为dota格式

[jqq-coder]

博主，我刚刚确定了一下数据集路径还是跑不起来，还是报上述问题

[jqq-coder]

博主，我看不见您回答的内容