Replaced Neutral Calibration

Author: RamesTheGeneric

BabbleApp/Models/EFFB0MVE99TIMM/onnx/model.onnx

@@ -161,7 +161,6 @@ def main():
         ],
     ]
 
-
     if config.cam_display_id in [Tab.CAM]:
         cams[0].start()
     if config.cam_display_id in [Tab.SETTINGS]:

BabbleApp/babbleapp.py

@@ -32,7 +32,7 @@ class BabbleSettingsConfig(BaseModel):
     gui_ROSC: bool = False
     gui_osc_location: str = ""
     gui_multiply: int = 1
-    gui_model_file: str = 'Models/ENEXTXXE100D4/'
+    gui_model_file: str = 'Models/EFFB0MVE99TIMM/'
     gui_runtime: str = "ONNX"
     gui_use_gpu: bool = False
     gui_gpu_index: int = 0

BabbleApp/config.py

@@ -1,4 +1,5 @@
 import numpy as np
+from math import log
 from enum import IntEnum
 from utils.misc_utils import PlaySound, SND_FILENAME, SND_ASYNC
 
@@ -7,43 +8,65 @@ class CamId(IntEnum):
     SETTINGS = 1
 
 class cal():
+
     def cal_osc(self, array):
         #print(self.calibration_frame_counter)
         if self.calibration_frame_counter == 0:
+            if not self.config.use_n_calibration:
+                self.calibration_frame_counter = None
+                values = np.array(self.val_list)
 
-            self.calibration_frame_counter = None
-            values = np.array(self.val_list)
+                # Initialize the min_max_array with shape (2, num_outputs)
+                num_outputs = values.shape[1]
+                self.min_max_array = np.zeros((2, num_outputs))
 
-            # Initialize the min_max_array with shape (2, num_outputs)
-            num_outputs = values.shape[1]
-            self.min_max_array = np.zeros((2, num_outputs))
+                # Iterate over each output index
+                for i in range(num_outputs):
+                    # Calculate the lower and upper thresholds for the current index
+                    lower_threshold = np.percentile(values[:, i], 1)
+                    upper_threshold = np.percentile(values[:, i], 99)
 
-            # Iterate over each output index
-            for i in range(num_outputs):
-                # Calculate the lower and upper thresholds for the current index
-                lower_threshold = np.percentile(values[:, i], 1)
-                upper_threshold = np.percentile(values[:, i], 99)
+                    # Filter out values within the thresholds for the current index
+                    filtered_values = values[(values[:, i] >= lower_threshold) & (values[:, i] <= upper_threshold), i]
 
-                # Filter out values within the thresholds for the current index
-                filtered_values = values[(values[:, i] >= lower_threshold) & (values[:, i] <= upper_threshold), i]
+                    # Extract the minimum and maximum values for the current index
+                    min_value = np.min(filtered_values)
+                    max_value = np.max(filtered_values)
+
+                    # Store the min and max values in the min_max_array
+                    self.min_max_array[0, i] = min_value
+                    self.min_max_array[1, i] = max_value
+                self.settings.calib_array = np.array2string(self.min_max_array, separator=',')
+                self.config_class.save()
+                print("[INFO] Calibration completed.")
+
+                PlaySound('Audio/completed.wav', SND_FILENAME | SND_ASYNC)
+
+            if self.config.use_n_calibration:
+                self.calibration_frame_counter = None
+                values = np.array(self.val_list)
+                deadzone_value = -0.01   # Maybe adjust from app????
+                # Initialize the min_max_array with shape (2, num_outputs)
+                num_outputs = values.shape[1]
+                self.min_max_array = np.zeros((2, num_outputs))
+                lower_threshold = np.clip([np.mean(values, axis = 0) + deadzone_value], 0, 1)
+                upper_threshold = np.ones((1, num_outputs)) # We don't need to adjust the max values. 
+                print(lower_threshold)
+                print(upper_threshold)
+                self.min_max_array = np.array([lower_threshold, upper_threshold])
+                self.settings.calib_array = np.array2string(self.min_max_array, separator=',')
+                self.config_class.save()
+                print("[INFO] Calibration completed.")
 
-                # Extract the minimum and maximum values for the current index
-                min_value = np.min(filtered_values)
-                max_value = np.max(filtered_values)
 
-                # Store the min and max values in the min_max_array
-                self.min_max_array[0, i] = min_value
-                self.min_max_array[1, i] = max_value
-            self.settings.calib_array = np.array2string(self.min_max_array, separator=',')
-            self.config_class.save()
-            print("[INFO] Calibration completed.")
 
-            PlaySound('Audio/completed.wav', SND_FILENAME | SND_ASYNC)
 
-        elif self.calibration_frame_counter != None:
 
+
+        elif self.calibration_frame_counter != None:
             self.val_list.append(array)
             self.calibration_frame_counter -= 1
+        
 
         if self.settings.calib_array is not None and self.config.use_calibration:
             self.min_max_array = np.fromstring(self.settings.calib_array.replace('[', '').replace(']', ''), sep=',')
@@ -70,10 +93,10 @@ def cal_osc(self, array):
             for i, value in enumerate(array):
                 min_value = self.min_max_array[0, i]
 
-
                 calibrated_value = (value - min_value) / (1.0 - min_value)
 
                 calibrated_array[i] = calibrated_value
             array = calibrated_array
-
+        print(array[4])
+        #array[4] = log((np.clip(array[4]*10,0,10))+1.0, 11) Log Filter: Move to filter system. 
         return np.clip(array,0,1)   # Clamp outputs between 0-1

BabbleApp/osc_calibrate_filter.py

@@ -1,6 +1,5 @@
 onnxruntime
-onnxruntime-gpu
-onnxruntime-openvino
+onnxruntime-directml
 opencv_python
 Pillow
 pysimplegui

BabbleApp/requirements.txt

@@ -1,9 +1,8 @@
 onnxruntime
-onnxruntime-gpu
-onnxruntime-openvino
+onnxruntime-directml
 opencv_python
 Pillow
-pysimplegui
+PySimpleGUI
 python_osc
 torch
 torchvision

requirements.txt

@@ -1,8 +1,8 @@
 :: Example script to auto build app and make an installer
 :: File paths will all need to be updated to your setup
-cd C:\Users\epicm\OneDrive\Documents\Github\ProjectBabble\BabbleApp
+cd X:\Documents\GitHub\ProjectBabble\BabbleApp
 pyinstaller babbleapp.spec --noconfirm
-cd C:\Users\epicm\OneDrive\Desktop\build
+cd X:\Documents\GitHub\ProjectBabble\BabbleApp
 cd 'C:\Program Files (x86)\Inno Setup 6'
 ./ISCC X:\Documents\GitHub\ProjectBabble\scripts\installer.iss
 ::cls

scripts/example_build_app_and_installer.bat

@@ -24,7 +24,7 @@ OutputDir=C:\Users\epicm\OneDrive\Desktop\build
 ; Uncomment the following line to run in non administrative install mode (install for current user only.)
 ;PrivilegesRequired=lowest
 OutputBaseFilename=Project_Babble-Setup
-SetupIconFile=C:\Users\epicm\OneDrive\Documents\Github\ProjectBabble\BabbleApp\Images\logo.ico
+SetupIconFile=X:\Documents\GitHub\ProjectBabble\BabbleApp\Images\logo.ico
 Compression=lzma/ultra64
 
 SolidCompression=yes
@@ -37,8 +37,8 @@ Name: "english"; MessagesFile: "compiler:Default.isl"
 Name: "desktopicon"; Description: "{cm:CreateDesktopIcon}"; GroupDescription: "{cm:AdditionalIcons}";
 
 [Files]
-Source: "C:\Users\epicm\OneDrive\Documents\Github\ProjectBabble\BabbleApp\dist\Babble_App\{#MyAppExeName}"; DestDir: "{app}"; Flags: ignoreversion
-Source: "C:\Users\epicm\OneDrive\Documents\Github\ProjectBabble\BabbleApp\dist\Babble_App\*"; DestDir: "{app}"; Flags: ignoreversion recursesubdirs createallsubdirs
+Source: "X:\Documents\GitHub\ProjectBabble\BabbleApp\dist\Babble_App\{#MyAppExeName}"; DestDir: "{app}"; Flags: ignoreversion
+Source: "X:\Documents\GitHub\ProjectBabble\BabbleApp\dist\Babble_App\*"; DestDir: "{app}"; Flags: ignoreversion recursesubdirs createallsubdirs
 ; NOTE: Don't use "Flags: ignoreversion" on any shared system files
 
 [Dirs]