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Provide AoI shp
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cleherny committed Jan 12, 2024
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24 changes: 12 additions & 12 deletions README.md
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Expand Up @@ -84,24 +84,24 @@ $ pip-compile requirements.in
The folders/files of the project `proj-dqry` (in combination with `object-detector`) is organised as follows. Path names can be customized by the user, and * indicates numbers which may vary:

<pre>.
├── config # configurations files folder
│   ├── config_det.template.yaml # template file for detection workflow over several years
│   ├── config_dt.yaml # detections tracking workflow
│   ├── config_det.yaml # detection workflow
│   ├── config_trne.yaml # training and evaluation workflow
│   ├── detectron2_config_dqry.yaml # detectron 2
│   └── logging.conf # logging configuration
├── images # folder containing the images displayed in the README
├── config # configurations files folder
│   ├── config_det.template.yaml # template file for detection workflow over several years
│   ├── config_dt.yaml # detections tracking workflow
│   ├── config_det.yaml # detection workflow
│   ├── config_trne.yaml # training and evaluation workflow
│   ├── detectron2_config_dqry.yaml # detectron 2
│   └── logging.conf # logging configuration
├── images # folder containing the images displayed in the README
├── input # inputs folders
│   ├── input_dt # detections tracking input
│   │   ├── oth_detections_at_0dot*_threshold_year-*_score-0dot*_area-*_elevation-*_distance-*.geojson # final filtered detections file for a given year
│   ├── input_det # detection inputs
│   │   ├── logs # folder containing trained model
│   │   │   └── model_*.pth # selected model at iteration
│   │   ├── AoI
│ │   │   ├── AoI_*.prj # AoI shapefile projection for a given year
│ │   │   ├── AoI_*.shp # AoI shapefile for a given year
│ │   │   └── AoI_*.shx # AoI shapefile indexes for a given year
│ │   │   ├── swissimage_footprint_*.prj # AoI shapefile projection for a given year
│ │   │   ├── swissimage_footprint_*.shp # AoI shapefile for a given year
│ │   │   └── swissimage_footprint_*.shx # AoI shapefile indexes for a given year
│   └── input_trne # training and evaluation inputs
│   ├── tlm-hr-trn-topo.prj # shapefile projection of the labels
│   ├── tlm-hr-trn-topo.shp # shapefile of the labels
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- images: [_SWISSIMAGE Journey_](https://www.swisstopo.admin.ch/en/maps-data-online/maps-geodata-online/journey-through-time-images.html) is an annual dataset of aerial images of Switzerland. Only RGB images are used, from 1999 to current. It includes [_SWISSIMAGE 10 cm_](https://www.swisstopo.admin.ch/fr/geodata/images/ortho/swissimage10.html), _SWISSIMAGE 25 cm_ and _SWISSIMAGE 50 cm_. The images are downloaded from the [geo.admin.ch](https://www.geo.admin.ch/fr) servor using [XYZ](https://developers.planet.com/docs/planetschool/xyz-tiles-and-slippy-maps/) connector.
- ground truth: MES labels come from [swissTLM3D](https://www.swisstopo.admin.ch/fr/geodata/landscape/tlm3d.html) product. The file _tlm-hr-trn-topo.shp_, used for training, has been reviewed and synchronised with the 2020 _SWISSIMAGE 10 cm_ mosaic.
- AoI: image acquisition footprint by year (AoI_[YEAR].shp) can be found [here](https://map.geo.admin.ch/?lang=fr&topic=ech&bgLayer=ch.swisstopo.pixelkarte-farbe&layers=ch.swisstopo.zeitreihen,ch.bfs.gebaeude_wohnungs_register,ch.bav.haltestellen-oev,ch.swisstopo.swisstlm3d-wanderwege,ch.astra.wanderland-sperrungen_umleitungen,ch.swisstopo.swissimage-product,ch.swisstopo.swissimage-product.metadata&layers_opacity=1,1,1,0.8,0.8,1,0.7&layers_visibility=false,false,false,false,false,true,true&layers_timestamp=18641231,,,,,2021,2021&time=2021). The 2020 AoI shapefile is provided in this repository.
- AoI: image acquisition footprint by year (swissimage_footprint_[YEAR].shp) can be found [here](https://map.geo.admin.ch/?lang=fr&topic=ech&bgLayer=ch.swisstopo.pixelkarte-farbe&layers=ch.swisstopo.zeitreihen,ch.bfs.gebaeude_wohnungs_register,ch.bav.haltestellen-oev,ch.swisstopo.swisstlm3d-wanderwege,ch.astra.wanderland-sperrungen_umleitungen,ch.swisstopo.swissimage-product,ch.swisstopo.swissimage-product.metadata&layers_opacity=1,1,1,0.8,0.8,1,0.7&layers_visibility=false,false,false,false,false,true,true&layers_timestamp=18641231,,,,,2021,2021&time=2021). The shapefiles of _SWISSIMAGE_ acquisition footprint from 2015 to 2020 are provided in this repository.
- DEM: the DEM of Switzerland has been processed by Lukas Martinelli and can be downloaded [here](https://github.com/lukasmartinelli/swissdem).
- trained model: the trained model used to produce the results presented in the [documentation](https://github.com/swiss-territorial-data-lab/stdl-tech-website/tree/master/docs/PROJ-DQRY) and achieving a f1 score of 82% is available on request.

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# Track object in different datasets over years
detections_tracking.py:
years: [YEAR1, YEAR2, YEAR3, ...] # Provide a list of years used for detection
years: [YEAR1, YEAR2, YEAR3,...] # Provide a list of years used for detection
datasets:
detection: ./input/input_dt/oth_detections_at_0dot3_threshold_year-{year}_score-0dot95_area-5000_elevation-1200_distance-10.geojson # Final detection file, produced by detections_filter.py !!! Change value in squared bracket
output_folder: ./output/output_dt/oth_detections_at_0dot3_threshold_score-0dot95_area-5000_elevation-1200_distance-10
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1 change: 1 addition & 0 deletions input/input_det/AoI/swissimage_footprint_2015.prj
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PROJCS["CH1903_LV03",GEOGCS["GCS_CH1903",DATUM["D_CH1903",SPHEROID["Bessel_1841",6377397.155,299.1528128]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Hotine_Oblique_Mercator_Azimuth_Center"],PARAMETER["False_Easting",600000.0],PARAMETER["False_Northing",200000.0],PARAMETER["Scale_Factor",1.0],PARAMETER["Azimuth",90.0],PARAMETER["Longitude_Of_Center",7.43958333333333],PARAMETER["Latitude_Of_Center",46.9524055555556],UNIT["Meter",1.0]]
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PROJCS["CH1903_LV03",GEOGCS["GCS_CH1903",DATUM["D_CH1903",SPHEROID["Bessel_1841",6377397.155,299.1528128]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Hotine_Oblique_Mercator_Azimuth_Center"],PARAMETER["False_Easting",600000.0],PARAMETER["False_Northing",200000.0],PARAMETER["Scale_Factor",1.0],PARAMETER["Azimuth",90.0],PARAMETER["Longitude_Of_Center",7.43958333333333],PARAMETER["Latitude_Of_Center",46.9524055555556],UNIT["Meter",1.0]]
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PROJCS["CH1903+_LV95",GEOGCS["GCS_CH1903+",DATUM["D_CH1903+",SPHEROID["Bessel_1841",6377397.155,299.1528128]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Hotine_Oblique_Mercator_Azimuth_Center"],PARAMETER["False_Easting",2600000.0],PARAMETER["False_Northing",1200000.0],PARAMETER["Scale_Factor",1.0],PARAMETER["Azimuth",90.0],PARAMETER["Longitude_Of_Center",7.43958333333333],PARAMETER["Latitude_Of_Center",46.9524055555556],UNIT["Meter",1.0]]
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PROJCS["CH1903+_LV95",GEOGCS["GCS_CH1903+",DATUM["D_CH1903+",SPHEROID["Bessel_1841",6377397.155,299.1528128]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Hotine_Oblique_Mercator_Azimuth_Center"],PARAMETER["False_Easting",2600000.0],PARAMETER["False_Northing",1200000.0],PARAMETER["Scale_Factor",1.0],PARAMETER["Azimuth",90.0],PARAMETER["Longitude_Of_Center",7.43958333333333],PARAMETER["Latitude_Of_Center",46.9524055555556],UNIT["Meter",1.0]]
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PROJCS["CH1903+_LV95",GEOGCS["GCS_CH1903+",DATUM["D_CH1903+",SPHEROID["Bessel_1841",6377397.155,299.1528128]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Hotine_Oblique_Mercator_Azimuth_Center"],PARAMETER["False_Easting",2600000.0],PARAMETER["False_Northing",1200000.0],PARAMETER["Scale_Factor",1.0],PARAMETER["Azimuth",90.0],PARAMETER["Longitude_Of_Center",7.43958333333333],PARAMETER["Latitude_Of_Center",46.9524055555556],UNIT["Meter",1.0]]
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4 changes: 2 additions & 2 deletions scripts/README.md
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Expand Up @@ -34,7 +34,7 @@ The labels (ground truth) polygons are used for the **Training and evaluation**

A region of Switzerland polygon is used for the **Detection** workflow:

[Label_Shapefile] = AoI_[YEAR].shp
[Label_Shapefile] = swissimage_footprint_[YEAR].shp

The outputs are `tiles.geojson` corresponding to shapefiles of the tiles obtained for the given AoI and `labels.geojson` corresponding to shapefiles of the input labels.

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-**input**: indicates the path to the input file that needs to be filtered, _i.e._ `oth_detections_at_0dot*_threshold.gpkg`

-**labels_shapefile**: AoI of interest is used to remove polygons located partially outside the AoI. _SWISSIMAGE_ acquisition footprint for a given year (AoI_[YEAR].shp) were used for this project.
-**labels_shapefile**: AoI of interest is used to remove polygons located partially outside the AoI. _SWISSIMAGE_ acquisition footprint for a given year (swissimage_footprint_[YEAR].shp) were used for this project.

-**dem**: indicates the path to a DEM of Switzerland. Product derived from SRTM is used and can be downloaded and reprojected with the `get_DEM.sh` script. An elevation threshold is used to discard detections above the given value.

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