Update README.md
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# ardigeos
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dünnschliff applikation
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🚀 Workflow: Subdatasets → echte Overviews
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🔹 Schritt 1: Nur höchste Auflösung extrahieren
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gdal_translate GTIFF_DIR:1:/scans/thinsect/1/101.tif base.tif -co TILED=YES -co COMPRESS=JPEG -co QUALITY=75
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👉 Das ist dein „Masterbild“
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🔹 Schritt 2: Overviews aus vorhandenen Levels bauen
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Gleiche Faktoren wie Subdatasets:
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gdaladdo -r average base.tif 2 4 8 16 32
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👉 entspricht:
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34576 → 17288 → 8644 → … ✔
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💡 Vorteil:
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gleiche Struktur wie Original aber jetzt COG-kompatibel
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🔹 Schritt 3: echtes COG erzeugen
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gdal_translate base.tif cog_final.tif -of COG -co COMPRESS=JPEG -co QUALITY=75 -co COPY_SRC_OVERVIEWS=YES
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Ergebnis 1/3 Dateigröße kleinere Datei als Original, da dort zuvor auch tiles enthalten sind (leider keine COG TIFF Pyramiden)
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für alle Ordner in /scans/thinsect/(1-52)*tif
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nohup bash -c '
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for dir in 49 50 51 52; do
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find /scans/thinsect/$dir -name "*.tif" | parallel \
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--bar \
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--joblog conversion_${dir}.log \
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"
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file={}
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name=\$(basename \"\$file\" .tif)
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gdal_translate \
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\"GTIFF_DIR:1:\$file\" \
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\"/scans/thinsect/cog_out/13/\${name}.tif\" \
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-of COG \
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-co COMPRESS=JPEG \
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-co QUALITY=75 \
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-co RESAMPLING=AVERAGE
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"
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done
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' > conversion.out 2>&1 &
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danach
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``gdalinfo /scans/tninsection/cog_out/1/1.tif``
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NGINX Anpassung und index.html anlegen mit Openlayerunterstützung
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