fix windows install

README.md

@@ -366,6 +366,7 @@ privileges:
     > $tbpath="<path-to-unzipped-executable>"
     > [Environment]::SetEnvironmentVariable("SONGEXPLORER_BIN",
             $tbpath + ";" +
+            $tbpath + "\bin\songexplorer\src;" +
             $tbpath + "\Library\mingw-w64\bin;" +
             $tbpath + "\Library\usr\bin;" +
             $tbpath + "\Library\bin;" +
@@ -1925,7 +1926,7 @@ Then build:
 To install directly from this local build:
 
     $ conda create --name songexplorer
-    $ conda install -n songexplorer --use-local songexplorer -c conda-forge
+    $ conda install -n songexplorer --use-local songexplorer -c conda-forge -c nvidia
 
 Pay attention to the notice at the end demarcated with "*** IMPORTANT
 !!! ***".  Follow the directions therein to install platform-specific

app/DROP-FILES-HERE.bat

@@ -2,7 +2,7 @@ setlocal
 
 set tbpath=%~dp0\songexplorer
 
-SET PATH=%tbpath%;%tbpath%\Library\mingw-w64\bin;%tbpath%\Library\usr\bin;%tbpath%\Library\bin;%tbpath%\Scripts;%tbpath%\bin;%PATH%
+SET PATH=%tbpath%;%tbpath%\bin\songexplorer\src;%tbpath%\Library\mingw-w64\bin;%tbpath%\Library\usr\bin;%tbpath%\Library\bin;%tbpath%\Scripts;%tbpath%\bin;%PATH%
 
 python.exe %~dp0\make-predictions.py %*
 

app/make-predictions.py

@@ -18,13 +18,14 @@
 
 use_aitch = True
 
+_, *wavpaths = sys.argv
+print("wavepaths = ", *wavpaths)
+
 __dir__ = os.path.dirname(__file__)
 
 sys.path.append(os.path.join(__dir__, "songexplorer", "bin", "songexplorer", "test"))
 from libtest import wait_for_job
 
-_, *wavpaths = sys.argv
-
 sys.path.append(os.path.join(__dir__, "songexplorer", "bin", "songexplorer", "src", "gui"))
 import model as M
 import view as V
@@ -75,7 +76,7 @@ def do_it(wavfile):
     V.waitfor.active = True
     asyncio.run(C.ethogram_actuate())
 
-    logfile = wavfile+"-post-process.log"
+    logfile = M.trim_ext(wavfile)+"-post-process.log"
     ncpu_cores, ngpu_cards, ngigabyes_memory  = 1, 0, 8
     localdeps = ["-d "+M.waitfor_job.pop()]
     kwargs = {"process_group": 0} if sys.version_info.major == 3 and sys.version_info.minor >= 11 else {}

install/conda/songexplorer/meta.yaml

@@ -14,11 +14,11 @@ build:
 requirements:
   run:
     - python <=3.10
-    - numpy
+    - numpy <2
     - tensorflow >=2.8,<2.14  # [linux]
-    - cudatoolkit  # [win]
-    - cudnn  # [win]
-    - cuda-nvcc  # [win]
+    - cudatoolkit=11  # [win]
+    - cudnn=8  # [win]
+    - cuda-nvcc=12  # [win]
     - bokeh >=2,<3
     - matplotlib-base
     - natsort 

src/activations

@@ -75,6 +75,10 @@ from lib import log_nvidia_smi_output, select_GPUs
 FLAGS = None
 
 def main():
+  flags = vars(FLAGS)
+  for key in sorted(flags.keys()):
+    print('%s = %s' % (key, flags[key]))
+
   os.environ['TF_DETERMINISTIC_OPS']=FLAGS.deterministic
   os.environ['TF_DISABLE_SPARSE_SOFTMAX_XENT_WITH_LOGITS_OP_DETERMINISM_EXCEPTIONS']=FLAGS.deterministic
   if FLAGS.deterministic:
@@ -88,10 +92,6 @@ def main():
   sys.path.append(os.path.dirname(FLAGS.video_findfile))
   video_findfile = importlib.import_module(os.path.basename(FLAGS.video_findfile)).video_findfile
 
-  flags = vars(FLAGS)
-  for key in sorted(flags.keys()):
-    print('%s = %s' % (key, flags[key]))
-
   audio_read_plugin_kwargs = eval(FLAGS.audio_read_plugin_kwargs)
   video_read_plugin_kwargs = eval(FLAGS.video_read_plugin_kwargs)
 

src/classify

@@ -65,6 +65,12 @@ from lib import compute_background
 FLAGS = None
 
 def main():
+  flags = vars(FLAGS)
+  for key in sorted(flags.keys()):
+    print('%s = %s' % (key, flags[key]))
+
+  audio_tic_rate = FLAGS.audio_tic_rate
+
   os.environ['TF_DETERMINISTIC_OPS']=FLAGS.deterministic
   os.environ['TF_DISABLE_SPARSE_SOFTMAX_XENT_WITH_LOGITS_OP_DETERMINISM_EXCEPTIONS']=FLAGS.deterministic
 
@@ -87,11 +93,6 @@ def main():
       return video_read_module.video_read(fullpath, start_frame, stop_frame,
                                           **FLAGS.video_read_plugin_kwargs)
 
-  audio_tic_rate = FLAGS.audio_tic_rate
-
-  print('model = '+str(FLAGS.model))
-  print('audio_tic_rate = '+str(audio_tic_rate))
-
   with open(FLAGS.model_labels, 'r') as fid:
     model_labels = fid.read().splitlines()