Add BirdNET-Geomodel 3.0

.github/workflows/ci.yml

@@ -34,7 +34,7 @@ jobs:
 
     steps:
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 2
 
@@ -56,7 +56,7 @@ jobs:
           choco install libsndfile
 
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
 
@@ -92,7 +92,38 @@ jobs:
 
       - name: Upload results to Codecov
         if: matrix.os == 'ubuntu-24.04' && matrix.python-version == '3.12'
-        uses: codecov/codecov-action@v5
+        uses: codecov/codecov-action@v6
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
           slug: birdnet-team/birdnet
+
+      - name: Extract log path
+        id: extract-log-path
+        shell: pwsh
+        run: |
+          $logPaths = @()
+
+          if (Test-Path output.log) {
+            $output = Get-Content output.log -Raw
+            $pattern = '(?<path>(?:[A-Za-z]:\\|/)[^\r\n]*?\.log)'
+            $logPaths = [regex]::Matches($output, $pattern) |
+              ForEach-Object { $_.Groups['path'].Value } |
+              Sort-Object -Unique |
+              Where-Object { Test-Path $_ -PathType Leaf }
+          }
+
+          if ($logPaths.Count -gt 0) {
+            "log_paths<<EOF" | Out-File -FilePath $env:GITHUB_OUTPUT -Append -Encoding utf8
+            $logPaths | Out-File -FilePath $env:GITHUB_OUTPUT -Append -Encoding utf8
+            "EOF" | Out-File -FilePath $env:GITHUB_OUTPUT -Append -Encoding utf8
+          }
+          else {
+            "log_paths=" | Out-File -FilePath $env:GITHUB_OUTPUT -Append -Encoding utf8
+          }
+
+      - name: Upload log file
+        if: failure() && steps.extract-log-path.outputs.log_paths != ''
+        uses: actions/upload-artifact@v7
+        with:
+          name: birdnet-log
+          path: ${{ steps.extract-log-path.outputs.log_paths }}

.github/workflows/documentation.yml

@@ -16,9 +16,9 @@ jobs:
   build:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
 
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: "3.12"
 
@@ -31,7 +31,7 @@ jobs:
         run: sphinx-build -b html docs/ docs/_build/html -j auto
 
       - name: Upload pages artifact
-        uses: actions/upload-pages-artifact@v3
+        uses: actions/upload-pages-artifact@v5
         with:
           path: docs/_build/html
 
@@ -55,4 +55,4 @@ jobs:
     steps:
       - name: Deploy to GitHub Pages
         id: deployment
-        uses: actions/deploy-pages@v4
+        uses: actions/deploy-pages@v5

docs/benchmarking.rst

@@ -1,8 +1,13 @@
 Benchmarking using command-line tool
-============
+====================================
 
 This page provides information on benchmarking BirdNET's performance on different hardware configurations. For some real world benchmark results, see :doc:`Comparative benchmarking results <benchmarking_results>`.
 
+.. toctree::
+  :hidden:
+
+  benchmarking_results
+
 .. note::
 
    The information provided here is not up-to-date with the latest developments in the BirdNET library.
@@ -20,7 +25,8 @@ Example usage
 - Use Protobuf backend: ``birdnet-benchmark soundscape.wav -b "pb"``
 - Output predictions for top 10 species: ``birdnet-benchmark soundscape.wav --top-k 10 --confidence -100``
 - Run on GPU: ``birdnet-benchmark soundscape.wav --backend "pb" --worker 1 --device "GPU" --batch-size 1000``
-  - To determine the largest possible batch size, you must experiment with several values. On a GPU with 24 GB of VRAM, a batch size of roughly 1,000 usually works well. If the batch size is set too high, the pipeline will abort with a runtime error ("Analysis was cancelled due to an error."), and the log will state that the GPU ran out of memory.
+
+  To determine the largest possible batch size, you must experiment with several values. On a GPU with 24 GB of VRAM, a batch size of roughly 1,000 usually works well. If the batch size is set too high, the pipeline will abort with a runtime error ("Analysis was cancelled due to an error."), and the log will state that the GPU ran out of memory.
 - Run on three GPUs: ``birdnet-benchmark soundscape.wav --backend "pb" --worker 3 --device "GPU:0" "GPU:1" "GPU:2" --batch-size 1000``
 - Increase amount of *Producers*: ``birdnet-benchmark soundscape.wav --producers 2``
 - Increase *Buffer* size to 3 * *Worker*: ``birdnet-benchmark soundscape.wav --prefetch-ratio 2``
@@ -70,7 +76,7 @@ Example output on Linux:
 
 
 Interpretation of runtime metrics
---------------------------------
+---------------------------------
 
 During analysis, performance indicators are updated and printed once per second.
 
@@ -109,15 +115,15 @@ Example log line::
 
 
 Typical bottlenecks and mitigation measures
-^^^^
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 * **High WAIT values or empty buffer** – Increase the number of *Producers*. If insufficient, use faster storage (NVMe/SSD) or reduce *Workers*.
 * **BUSY < Worker count** – Typically an I/O bottleneck. Apply steps above.
 * **Cache effect** – OS file caching boosts SPEED significantly on the second pass. For benchmarking, use only runs starting from the second pass.
 
 
 Metrics after completion
------
+------------------------
 
 After analysis completes, the benchmark tool reports:
 

docs/benchmarking_results.rst

@@ -1,5 +1,5 @@
 Comparative benchmarking results
-===================
+================================
 
 .. contents::
    :local:
@@ -14,7 +14,7 @@ Run 10 h WAV-files on Intel i7-8565U (4-Core, 16 GB RAM, Windows 10)
 
 **Result:** 49 × real-time (RTF: 0.02047110)
 
-.. code-block:: txt
+.. code-block:: text
 
    $ birdnet-benchmark test-dataset/test_dataset_100x60min -p 5
 
@@ -52,7 +52,7 @@ Run 100 h WAV-files on AMD Ryzen 7 3800X (8-Core, 64 GB RAM, Linux)
 
 **Result:** 416 × real-time (RTF: 0.00240288)
 
-.. code-block:: txt
+.. code-block:: text
 
    $ birdnet-benchmark test-dataset/test_dataset_100x60min -f
 
@@ -92,13 +92,13 @@ Run 100 h WAV-files on NVIDIA Titan RTX (24 GB, Linux)
 
 Disk speed:
 
-.. code-block:: txt
+.. code-block:: text
 
    $ sudo hdparm -tT /dev/nvme0n1
      Timing cached reads: 27324 MB in 1.99 seconds = 13707.90 MB/sec
      Timing buffered disk reads: 6880 MB in 3.00 seconds = 2293.17 MB/sec
 
-.. code-block:: txt
+.. code-block:: text
 
    $ birdnet-benchmark test-dataset/test_dataset_100x60min --device GPU --backend pb -w 1 -p 5 -s 1025 --prefetch-ratio 5
 
@@ -137,7 +137,7 @@ Run 100 h FLAC-files on NVIDIA Titan RTX (24 GB, Linux)
 
 **Result:** 2487 × real-time (RTF: 0.00040214)
 
-.. code-block:: txt
+.. code-block:: text
 
    $ birdnet-benchmark test-dataset/test_dataset_100x60min_flac --device GPU --backend pb -w 1 -p 5 -s 1025
 

docs/birdnet.acoustic.inference.core.encoding.rst

@@ -0,0 +1,45 @@
+birdnet.acoustic.inference.core.encoding package
+================================================
+
+Submodules
+----------
+
+birdnet.acoustic.inference.core.encoding.encoding\_benchmarking module
+----------------------------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.encoding.encoding_benchmarking
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.encoding.encoding\_result module
+----------------------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.encoding.encoding_result
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.encoding.encoding\_tensor module
+----------------------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.encoding.encoding_tensor
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.encoding.encoding\_worker module
+----------------------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.encoding.encoding_worker
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+Module contents
+---------------
+
+.. automodule:: birdnet.acoustic.inference.core.encoding
+   :members:
+   :show-inheritance:
+   :undoc-members:

docs/birdnet.acoustic.inference.core.prediction.rst

@@ -0,0 +1,45 @@
+birdnet.acoustic.inference.core.prediction package
+==================================================
+
+Submodules
+----------
+
+birdnet.acoustic.inference.core.prediction.prediction\_benchmarking module
+---------------------------------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.prediction.prediction_benchmarking
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.prediction.prediction\_result module
+---------------------------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.prediction.prediction_result
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.prediction.prediction\_tensor module
+---------------------------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.prediction.prediction_tensor
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.prediction.prediction\_worker module
+---------------------------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.prediction.prediction_worker
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+Module contents
+---------------
+
+.. automodule:: birdnet.acoustic.inference.core.prediction
+   :members:
+   :show-inheritance:
+   :undoc-members:

docs/birdnet.acoustic.inference.core.rst

@@ -0,0 +1,86 @@
+birdnet.acoustic.inference.core package
+=======================================
+
+Subpackages
+-----------
+
+.. toctree::
+   :maxdepth: 4
+
+   birdnet.acoustic.inference.core.encoding
+   birdnet.acoustic.inference.core.prediction
+
+Submodules
+----------
+
+birdnet.acoustic.inference.core.benchmarking module
+---------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.benchmarking
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.consumer module
+-----------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.consumer
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.input\_analyzer module
+------------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.input_analyzer
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.perf\_tracker module
+----------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.perf_tracker
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.producer module
+-----------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.producer
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.result\_base module
+---------------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.result_base
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.tensor module
+---------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.tensor
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+birdnet.acoustic.inference.core.worker module
+---------------------------------------------
+
+.. automodule:: birdnet.acoustic.inference.core.worker
+   :members:
+   :show-inheritance:
+   :undoc-members:
+
+Module contents
+---------------
+
+.. automodule:: birdnet.acoustic.inference.core
+   :members:
+   :show-inheritance:
+   :undoc-members: