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bulldozer-dtm-1.0.0
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Bulldozer is a DTM extraction tool requiring only a DSM as input
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | bulldozer-dtm-1.0.0 |
| نام | bulldozer-dtm |
| نسخه کتابخانه | 1.0.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | CNES |
| ایمیل نویسنده | pierre.lassalle@cnes.fr,dimitri.lallement@cnes.fr,yannick.ott@thalesgroup.com |
| آدرس صفحه اصلی | https://github.com/CNES/bulldozer |
| آدرس اینترنتی | https://pypi.org/project/bulldozer-dtm/ |
| مجوز | Apache V2.0 |
<div align="center">
<img src="docs/source/images/bulldozer_logo.png" width=256
>
**Bulldozer, a DTM extraction tool requiring only a DSM as input.**
[](https://www.python.org/downloads/release/python-380/)
[](CONTRIBUTING.md)
[](https://opensource.org/licenses/Apache-2.0)
[](https://pypi.org/project/bulldozer/)
<p align="center">
<a href="#key-features">Key Features</a> •
<a href="#installation">Installation</a> •
<a href="#quick-start">Quick Start</a> •
<a href="#documentation">Documentation</a> •
<a href="#contribute">Contribute</a> •
<a href="#licence">Licence</a> •
<a href="#reference">Reference</a>
</p>
</div>
---
## Key features
<div align="center">
<img src="docs/source/images/result_overview.gif" alt="drawing" width="400"/>
</div>
**Bulldozer** is designed as a pipeline of standalone functions that aims to extract a *Digital Terrain Model* (DTM) from a *Digital Surface Model* (DSM).
But you can also use one of the following function without running the full pipeline:
* **DSM preprocessing**
* **Nodata extraction:** a group of methods to differentiate and extract nodata related to failed correlations during the DSM computation and those of the image border
* **Disturbed areas detection:** a method to locate disturbed areas. These noisy areas are mainly related to areas in which the correlator has incorrectly estimated the elevation (water or shadow areas).
* **DTM extraction**
* **DTM computation:** the main method that extracts the DTM from the preprocessed DSM.
* **DTM postprocessing**
* **Pits detection:** a method to detect pits in the provided raster and return the corresponding mask.
* **Pits filling:** a method to fill pits in the generated DTM (or input raster).
* **DHM computation:** a method to extract the *Digital Height Model* (DHM).
For more information about these functions and how to call them, please refer to the <a href="#notebooks">notebook documentation section</a>.
## Installation
### Using Pypi
You can install **Bulldozer** by running the following command:
```sh
pip install bulldozer-dtm
```
### Using Github
It is recommended to install **Bulldozer** into a virtual environment, like [conda](https://docs.conda.io/en/latest/) or [virtualenv](https://virtualenv.pypa.io/en/latest/).
* Installation with `virtualenv`:
```sh
# Clone the project
git clone https://github.com/CNES/bulldozer.git
cd bulldozer/
# Create the environment
python -m venv bulldozer_venv
source bulldozer_venv/bin/activate
# Install the library
pip install .
```
## Quick Start
1. First you have to create a configuration file or edit the `configuration_template.yaml` available in the `conf` directory. You have to update at least the following parameters:
```yaml
# Input DSM path (expected format: "<folder_1>/<folder_2>/<file>.<[tif/tiff]>")
dsmPath : "<input_dsm.tif>"
# Output directory path (if the directory doesn't exist, create it)
outputDir : "<output_dir>"
```
2. Run the pipeline:
* Through CLI *(Command Line Interface)*
```console
bulldozer --conf conf/configuration_template.yaml
```
* Through Python API using the config file
```python
from bulldozer.pipeline.bulldozer_pipeline import dsm_to_dtm
dsm_to_dtm(config_path="conf/configuration_template.yaml")
```
* Through Python API providing directly the input parameters (missing parameters will be replaced by default values)
```python
from bulldozer.pipeline.bulldozer_pipeline import dsm_to_dtm
# Example with a specific number of workers
dsm_to_dtm(dsm_path="<input_dsm.tif>", output_dir="<output_dir>", nb_max_workers=16)
```
3. ✅ Done! Your DTM is available in the *<output_dir>*
## Documentation
### Notebooks
For each section described in <a href="#key-features">Key Features</a> section you can follow one of the tutorial notebook:
* [Running Bulldozer (full pipeline)](docs/notebooks/0_bulldozer_pipeline.ipynb)
* [Preprocessing standalone functions](docs/notebooks/1_preprocess.ipynb)
* [Extraction step](docs/notebooks/2_DTM_extraction.ipynb)
* [Postprocessing standalone functions](docs/notebooks/3_postprocess.ipynb)
### Full documentation (WIP)
**Bulldozer** also has a more detailed documentation.
A high-level overview of how it’s organized will help you know where to look for certain things:
* [Tutorials](docs/tutorials/index.md) take you by the hand through a series of steps to create a DLCooker application. Start here if you’re new to DLCooker.
* [How-to guides](docs/how-to/index.md) are recipes. They guide you through the steps involved in addressing key problems and use-cases. They are more advanced than tutorials and assume some knowledge of how DLCooker works.
* [Explanation guides](docs/explanation/index.md) discuss key topics and concepts at a fairly high level and provide useful background information and explanation.
> **_NOTE:_** The documentation is not available online yet, it needs to be built manually.
To do so, please execute the following command at the root:
```console
mkdocs serve
```
## Contribute
To do a bug report or a contribution, see the [**Contribution Guide**](CONTRIBUTING.md).
for any help or suggestion, feel free to contact the authors:
- Dimitri Lallement : dimitri.lallement@cnes.fr
- Pierre Lassalle : pierre.lassalle@cnes.fr
## Licence
**Bulldozer** has a Apache V2.0 license, as found in the [LICENSE](LICENSE) file.
## Credits
Please refer to the [Authors file](AUTHORS.md).
## Reference
[D. Lallement, P. Lassalle, Y. Ott, R. Demortier, and J. Delvit, 2022. BULLDOZER: AN AUTOMATIC SELF-DRIVEN LARGE SCALE DTM EXTRACTION METHOD FROM DIGITAL SURFACE MODEL. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.](https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2022/409/2022/)
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl bulldozer-dtm-1.0.0:
pip install bulldozer-dtm-1.0.0.whl
نصب پکیج tar.gz bulldozer-dtm-1.0.0:
pip install bulldozer-dtm-1.0.0.tar.gz