From 666c0056a177c4ebf1d1e486581123069e1a2c7a Mon Sep 17 00:00:00 2001 From: Clemence Herny Date: Fri, 12 Jan 2024 08:56:13 +0000 Subject: [PATCH] Provide AoI shp --- README.md | 24 +++++++++--------- config/config_dt.yaml | 2 +- .../AoI/swissimage_footprint_2015.dbf | Bin 0 -> 2119 bytes .../AoI/swissimage_footprint_2015.prj | 1 + .../AoI/swissimage_footprint_2015.shp | Bin 0 -> 7028 bytes .../AoI/swissimage_footprint_2015.shx | Bin 0 -> 108 bytes .../AoI/swissimage_footprint_2016.dbf | Bin 0 -> 2119 bytes .../AoI/swissimage_footprint_2016.prj | 1 + .../AoI/swissimage_footprint_2016.shp | Bin 0 -> 4832 bytes .../AoI/swissimage_footprint_2016.shx | Bin 0 -> 108 bytes .../AoI/swissimage_footprint_2017.dbf | Bin 0 -> 2129 bytes ...2020.prj => swissimage_footprint_2017.prj} | 0 .../AoI/swissimage_footprint_2017.shp | Bin 0 -> 19660 bytes .../AoI/swissimage_footprint_2017.shx | Bin 0 -> 108 bytes .../AoI/swissimage_footprint_2018.dbf | Bin 0 -> 2129 bytes .../AoI/swissimage_footprint_2018.prj | 1 + .../AoI/swissimage_footprint_2018.shp | Bin 0 -> 19084 bytes .../AoI/swissimage_footprint_2018.shx | Bin 0 -> 108 bytes .../AoI/swissimage_footprint_2019.dbf | Bin 0 -> 2129 bytes .../AoI/swissimage_footprint_2019.prj | 1 + .../AoI/swissimage_footprint_2019.shp | Bin 0 -> 17132 bytes .../AoI/swissimage_footprint_2019.shx | Bin 0 -> 108 bytes ...2020.dbf => swissimage_footprint_2020.dbf} | Bin .../AoI/swissimage_footprint_2020.prj | 1 + ...2020.shp => swissimage_footprint_2020.shp} | Bin ...2020.shx => swissimage_footprint_2020.shx} | Bin scripts/README.md | 4 +-- 27 files changed, 20 insertions(+), 15 deletions(-) create mode 100755 input/input_det/AoI/swissimage_footprint_2015.dbf create mode 100755 input/input_det/AoI/swissimage_footprint_2015.prj create mode 100755 input/input_det/AoI/swissimage_footprint_2015.shp create mode 100755 input/input_det/AoI/swissimage_footprint_2015.shx create mode 100755 input/input_det/AoI/swissimage_footprint_2016.dbf create mode 100755 input/input_det/AoI/swissimage_footprint_2016.prj create mode 100755 input/input_det/AoI/swissimage_footprint_2016.shp create mode 100755 input/input_det/AoI/swissimage_footprint_2016.shx create mode 100755 input/input_det/AoI/swissimage_footprint_2017.dbf rename input/input_det/AoI/{AoI_2020.prj => swissimage_footprint_2017.prj} (100%) create mode 100755 input/input_det/AoI/swissimage_footprint_2017.shp create mode 100755 input/input_det/AoI/swissimage_footprint_2017.shx create mode 100755 input/input_det/AoI/swissimage_footprint_2018.dbf create mode 100755 input/input_det/AoI/swissimage_footprint_2018.prj create mode 100755 input/input_det/AoI/swissimage_footprint_2018.shp create mode 100755 input/input_det/AoI/swissimage_footprint_2018.shx create mode 100755 input/input_det/AoI/swissimage_footprint_2019.dbf create mode 100755 input/input_det/AoI/swissimage_footprint_2019.prj create mode 100755 input/input_det/AoI/swissimage_footprint_2019.shp create mode 100755 input/input_det/AoI/swissimage_footprint_2019.shx rename input/input_det/AoI/{AoI_2020.dbf => swissimage_footprint_2020.dbf} (100%) create mode 100755 input/input_det/AoI/swissimage_footprint_2020.prj rename input/input_det/AoI/{AoI_2020.shp => swissimage_footprint_2020.shp} (100%) rename input/input_det/AoI/{AoI_2020.shx => swissimage_footprint_2020.shx} (100%) diff --git a/README.md b/README.md index 9092c3b..cfb00c9 100644 --- a/README.md +++ b/README.md @@ -84,14 +84,14 @@ $ 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: 
.
-├── 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
@@ -99,9 +99,9 @@ The folders/files of the project `proj-dqry` (in combination with `object-detect
 │   │   ├── 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 
@@ -191,7 +191,7 @@ Below, the description of input data (to be adapted as required) used for this p
 
 - 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.
 
diff --git a/config/config_dt.yaml b/config/config_dt.yaml
index 572bbac..59ab7f1 100644
--- a/config/config_dt.yaml
+++ b/config/config_dt.yaml
@@ -3,7 +3,7 @@
 
 # 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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diff --git a/input/input_det/AoI/swissimage_footprint_2015.prj b/input/input_det/AoI/swissimage_footprint_2015.prj
new file mode 100755
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new file mode 100755
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new file mode 100755
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diff --git a/input/input_det/AoI/swissimage_footprint_2019.shx b/input/input_det/AoI/swissimage_footprint_2019.shx
new file mode 100755
index 0000000000000000000000000000000000000000..1e1c769f21121a0dca2063cedbfce4cd74616aec
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