Make locations for detectors dir and models dir configurable.

LabGym/config.py

@@ -8,13 +8,14 @@
 
 Notes
 *   Environment variables and command-line options can be used to
-    override the location of the configuration file, so determine the
-    configuration file location before reading it.
+    override the location of the configuration file, so its location is
+    determined (from defaults, environment variables, and command-line
+    options) before reading it.
 
 *   Typical LabGym configdir organization is
         ~/.labgym/config.toml  (optional)
                   logging.yaml  (optional)
-                  registration.done  (created at registration)
+                  registration.yaml  (created at registration)
 
     To use a different configfile only (without changing the references
     to other configdir files),
@@ -66,6 +67,9 @@
         },
 
     'anonymous': False,
+
+    'detectors': str(Path(__file__).parent.joinpath('detectors')),
+    'models': str(Path(__file__).parent.joinpath('models')),
 }
 
 logger = logging.getLogger(__name__)
@@ -129,8 +133,25 @@ def get_config_from_configfile(configfile: Path) -> dict:
     return result
 
 
-def get_config():
-    """Return a cached config dict. Construct it if necessary.
+def get_config(*args) -> dict:
+    """Return a copy of the cached config dict (or a subset of its pairs).
+
+    If args are passed, then return a new dict of only those keys and
+    their values from the cached config dict.
+    """
+
+    fullconfig = get_fullconfig()
+
+    if len(args) == 0:
+        result = fullconfig
+    else:
+        result = {key: fullconfig[key] for key in args}
+
+    return copy.deepcopy(result)
+
+
+def get_fullconfig() -> dict:
+    """Return a copy of the cached config dict. Construct it if necessary.
 
     Strengths
     *   Instead of reconstructing the config dict each time this

LabGym/gui_analyzer.py

@@ -18,8 +18,8 @@
 
 
 # Standard library imports.
-import logging
 import json
+import logging
 import os
 from pathlib import Path
 
@@ -38,11 +38,9 @@
 # Local application/library specific imports.
 from .analyzebehavior import AnalyzeAnimal
 from .analyzebehavior_dt import AnalyzeAnimalDetector
+from LabGym import config
 from .minedata import data_mining
-from .tools import plot_events,parse_all_events_file,calculate_distances
-
-
-the_absolute_current_path=str(Path(__file__).resolve().parent)
+from .tools import plot_events, parse_all_events_file, calculate_distances
 
 
 class ColorPicker(wx.Dialog):
@@ -85,6 +83,10 @@ def __init__(self, parent):
 
 		super().__init__(parent)
 		self.notebook = parent
+
+		# Get all of the values needed from config.get_config().
+		self.config = config.get_config('detectors', 'models')
+
 		self.behavior_mode=0 # 0--non-interactive, 1--interactive basic, 2--interactive advanced, 3--static images
 		self.use_detector=False # whether the Detector is used
 		self.detector_path=None # the 'LabGym/detectors' folder, which stores all the trained Detectors
@@ -247,7 +249,8 @@ def display_window(self):
 	def select_categorizer(self,event):
 
 		if self.model_path is None:
-			self.model_path=os.path.join(the_absolute_current_path,'models')
+			self.model_path = self.config['models']
+			logger.debug('%s: %r', 'self.model_path', self.model_path)
 
 		categorizers=[i for i in os.listdir(self.model_path) if os.path.isdir(os.path.join(self.model_path,i))]
 		if '__pycache__' in categorizers:
@@ -557,7 +560,8 @@ def select_method(self,event):
 			else:
 
 				self.animal_number={}
-				self.detector_path=os.path.join(the_absolute_current_path,'detectors')
+				self.detector_path = self.config['detectors']
+				logger.debug('%s: %r', 'self.detector_path', self.detector_path)
 				self.text_animalnumber.SetLabel('Default: 1.')
 
 				detectors=[i for i in os.listdir(self.detector_path) if os.path.isdir(os.path.join(self.detector_path,i))]

LabGym/gui_categorizer.py

@@ -43,13 +43,11 @@
 from .analyzebehavior_dt import AnalyzeAnimalDetector
 logger.debug('importing %s done', '.analyzebehavior_dt')
 from .categorizer import Categorizers
+from LabGym import config
 from .tools import sort_examples_from_csv
 from .gui_utils import add_or_select_notebook_page
 
 
-the_absolute_current_path=str(Path(__file__).resolve().parent)
-
-
 class PanelLv2_GenerateExamples(wx.Panel):
 
 	'''
@@ -60,6 +58,10 @@ def __init__(self, parent):
 
 		super().__init__(parent)
 		self.notebook = parent
+
+		# Get all of the values needed from config.get_config().
+		self.config = config.get_config('detectors', 'models')
+
 		self.behavior_mode=0 # 0: non-interactive behavior; 1: interact basic; 2: interact advanced; 3: static images
 		self.use_detector=False # whether the Detector is used
 		self.detector_path=None # the 'LabGym/detectors' folder, which stores all the trained Detectors
@@ -376,7 +378,8 @@ def select_method(self,event):
 
 				self.use_detector=True
 				self.animal_number={}
-				self.detector_path=os.path.join(the_absolute_current_path,'detectors')
+				self.detector_path = self.config['detectors']
+				logger.debug('%s: %r', 'self.detector_path', self.detector_path)
 
 				detectors=[i for i in os.listdir(self.detector_path) if os.path.isdir(os.path.join(self.detector_path,i))]
 				if '__pycache__' in detectors:
@@ -1063,6 +1066,10 @@ def __init__(self, parent):
 
 		super().__init__(parent)
 		self.notebook = parent
+
+		# Get all of the values needed from config.get_config().
+		self.config = config.get_config('models')
+
 		self.file_path=None # the folder that stores sorted, unprepared behavior examples (each category is a subfolder)
 		self.new_path=None # the folder that stores prepared behavior examples (contains all examples with a category tag in their names)
 		self.behavior_mode=0 # 0--non-interactive, 1--interactive basic, 2--interactive advanced, 3--static images
@@ -1076,8 +1083,10 @@ def __init__(self, parent):
 		self.aug_methods=[] # the methods for augment training and validation examples
 		self.augvalid=True # whether to perform augmentation for validation data as well
 		self.data_path=None # the folder that stores prepared behavior examples
-		self.model_path=os.path.join(the_absolute_current_path,'models') # the 'LabGym/models' folder, which stores all the trained Categorizers
-		self.path_to_categorizer=os.path.join(the_absolute_current_path,'models','New_model') # path to the Categorizer
+		self.model_path = self.config['models']  # the 'LabGym/models' folder, which stores all the trained Categorizers
+		logger.debug('%s: %r', 'self.model_path', self.model_path)
+		self.path_to_categorizer = os.path.join(self.config['models'], 'New_model')  # path to the Categorizer
+		logger.debug('%s: %r', 'self.path_to_categorizer', self.path_to_categorizer)
 		self.out_path=None # the folder for storing the training reports
 		self.include_bodyparts=False # whether to include body parts in the pattern images
 		self.std=0 # a value between 0 and 255, higher value, less body parts will be included in the pattern images
@@ -1576,8 +1585,13 @@ def __init__(self, parent):
 
 		super().__init__(parent)
 		self.notebook = parent
+
+		# Get all of the values needed from config.get_config().
+		self.config = config.get_config('models')
+
 		self.file_path=None # the folder that stores the ground-truth examples (each subfolder is a behavior category)
-		self.model_path=os.path.join(the_absolute_current_path,'models') # the 'LabGym/models' folder, which stores all the trained Categorizers
+		self.model_path = self.config['models']  # the 'LabGym/models' folder, which stores all the trained Categorizers
+		logger.debug('%s: %r', 'self.model_path', self.model_path)
 		self.path_to_categorizer=None # path to the Categorizer
 		self.out_path=None # for storing the testing reports
 

LabGym/gui_detector.py

@@ -20,8 +20,8 @@
 # Standard library imports.
 import json
 import logging
-from pathlib import Path
 import os
+from pathlib import Path
 import shutil
 
 # Log the load of this module (by the module loader, on first import).
@@ -34,13 +34,11 @@
 import wx
 
 # Local application/library specific imports.
+from LabGym import config
 from .detector import Detector
 from .tools import extract_frames
 
 
-the_absolute_current_path=str(Path(__file__).resolve().parent)
-
-
 class PanelLv2_GenerateImages(wx.Panel):
 
 	'''
@@ -236,11 +234,16 @@ def __init__(self, parent):
 
 		super().__init__(parent)
 		self.notebook = parent
+
+		# Get all of the values needed from config.get_config().
+		self.config = config.get_config('detectors')
+
 		self.path_to_trainingimages=None # the folder that stores all the training images
 		self.path_to_annotation=None # the path to the .json file that stores the annotations in coco format
 		self.inference_size=480 # the Detector inferencing frame size
 		self.iteration_num=200 # the number of training iterations
-		self.detector_path=os.path.join(the_absolute_current_path,'detectors') # the 'LabGym/detectors' folder, which stores all the trained Detectors
+		self.detector_path = self.config['detectors']  # the 'LabGym/detectors' folder, which stores all the trained Detectors
+		logger.debug('%s: %r', 'self.detector_path', self.detector_path)
 		self.path_to_detector=None # path to the Detector
 
 		self.display_window()
@@ -390,9 +393,14 @@ def __init__(self, parent):
 
 		super().__init__(parent)
 		self.notebook = parent
+
+		# Get all of the values needed from config.get_config().
+		self.config = config.get_config('detectors')
+
 		self.path_to_testingimages=None # the folder that stores all the testing images
 		self.path_to_annotation=None # the path to the .json file that stores the annotations in coco format
-		self.detector_path=os.path.join(the_absolute_current_path,'detectors') # the 'LabGym/detectors' folder, which stores all the trained Detectors
+		self.detector_path = self.config['detectors']  # the 'LabGym/detectors' folder, which stores all the trained Detectors
+		logger.debug('%s: %r', 'self.detector_path', self.detector_path)
 		self.path_to_detector=None # path to the Detector
 		self.output_path=None # the folder that stores the testing images with annotations