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The dataset generation failed
Error code: DatasetGenerationError
Exception: UnicodeDecodeError
Message: 'utf-8' codec can't decode byte 0xf8 in position 4: invalid start byte
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1995, in _prepare_split_single
for _, table in generator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/text/text.py", line 90, in _generate_tables
batch = f.read(self.config.chunksize)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1104, in read_with_retries
out = read(*args, **kwargs)
File "/usr/local/lib/python3.9/codecs.py", line 322, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xf8 in position 4: invalid start byte
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1529, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1154, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2038, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
text string |
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from PIL import Image |
import os |
def convert_to_grayscale(image_path): |
image = Image.open(image_path).convert("L") # Convert to grayscale |
return image |
def split_and_save(image_path, output_dir1, output_dir2): |
image = Image.open(image_path) |
width, height = image.size |
half_width = width // 2 |
left_image = image.crop((0, 0, half_width, height)) |
right_image = image.crop((half_width, 0, width, height)) |
left_image.save(os.path.join(output_dir1, os.path.basename(image_path))) |
right_image.save(os.path.join(output_dir2, os.path.basename(image_path))) |
def batch_process(input_dir): |
output_dir1 = os.path.join(input_dir, "cam1") |
output_dir2 = os.path.join(input_dir, "cam2") |
os.makedirs(output_dir1, exist_ok=True) |
os.makedirs(output_dir2, exist_ok=True) |
for filename in os.listdir(input_dir): |
if filename.endswith(".png"): |
image_path = os.path.join(input_dir, filename) |
grayscale_image = convert_to_grayscale(image_path) |
grayscale_image.save(image_path) # Overwrite the original image with grayscale version |
split_and_save(image_path, output_dir1, output_dir2) |
if __name__ == "__main__": |
input_dir = './scan5' |
batch_process(input_dir) |
1、Oridata中存储了原始的视频以及rgb数据(西北工业大学湖面采集) |
2、使用preprocess.py将数据转换成wass支持的格式 |
得到5个文件夹： |
scan1-scan5文件夹下 |
（1）input是wass的输入文件夹，里面包含了左右相机的图像序列 |
（2）config存储了左右相机的内参以及畸变系数 |
（3）output文件夹存储了每个立体pair的wass重建结果 |
点云文件是plane_refinement_inliers.xyz |
3、WASS_TEST 是wass提供的测试数据 |
4、wass_1.11_win32_x64 是windows下wass重建代码 |
<?xml version="1.0"?> |
<opencv_storage> |
<intrinsics_penne type_id="opencv-matrix"> |
<rows>5</rows> |
<cols>1</cols> |
<dt>d</dt> |
<data> |
-3.202059184174811e-002 |
5.484810041960487e-002 |
-2.376797821038721e-004 |
1.957176410761953e-003 |
0 |
</data></intrinsics_penne> |
</opencv_storage> |
<?xml version="1.0"?> |
<opencv_storage> |
<intrinsics_penne type_id="opencv-matrix"> |
<rows>5</rows> |
<cols>1</cols> |
<dt>d</dt> |
<data> |
-3.010775294366006e-002 |
5.207379006686103e-002 |
1.275242537506779e-003 |
6.132156106101780e-005 |
0</data></intrinsics_penne> |
</opencv_storage> |
<?xml version="1.0"?> |
<opencv_storage> |
<ext_R type_id="opencv-matrix"> |
<rows>3</rows> |
<cols>3</cols> |
<dt>d</dt> |
<data> |
9.9854401420328975e-01 2.9595497349581539e-02 -4.5099426109552407e-02 |
-3.0994227401413992e-02 9.9904990776121294e-01 -3.0637226867026929e-02 |
4.4149853528290657e-02 3.1990441368370412e-02 9.9851259486021859e-01 |
</data></ext_R> |
</opencv_storage> |
<?xml version="1.0"?> |
<opencv_storage> |
<ext_T type_id="opencv-matrix"> |
<rows>3</rows> |
<cols>1</cols> |
<dt>d</dt> |
<data> |
9.9960400252946990e-01 |
1.1883594323257373e-02 |
2.5507220801641667e-02 |
</data></ext_T> |
</opencv_storage> |
<?xml version="1.0"?> |
<opencv_storage> |
<intrinsics_penne type_id="opencv-matrix"> |
<rows>3</rows> |
<cols>3</cols> |
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