Add MocapNET

2026-10-16 00:13:07 +00:00 · 2023-12-15 04:22:41 +05:30
parent 8434144ded
commit 65e8934d5e
336 changed files with 100584 additions and 0 deletions
@@ -0,0 +1,112 @@
+
+import numpy as np
+import sys
+import os
+
+from readCSV import readCSVFile,writeCSVFile,splitNumpyArray
+
+def functionThatFiltersOutColumnsWithStandardDeviation0(dataIn):
+    body = dataIn['body']
+    std_deviations = np.std(body, axis=0)
+    columns_to_keep = np.where(std_deviations != 0)[0]
+
+    filtered_body = body[:, columns_to_keep]
+    filtered_labels = [dataIn['label'][i] for i in columns_to_keep]
+    filtered_label_lookup = {label: i for i, label in enumerate(filtered_labels)}
+
+    return {
+        'label': filtered_labels,
+        'labelLookup': filtered_label_lookup,
+        'body': filtered_body
+    }
+
+
+def functionThatAppendsZeroColumnsByLabels(dataIn, labelsToAppendZeroColumns, preFixPadding=0, postFixPadding=0):
+    body = dataIn['body']
+    num_samples, num_columns = body.shape
+    new_num_columns = num_columns + len(labelsToAppendZeroColumns) + preFixPadding + postFixPadding
+
+    new_labels = []
+  
+    paddingNumber = 0
+    # Create the new zero-filled data array
+    new_body = np.zeros((num_samples, new_num_columns), dtype=body.dtype)
+
+    #==========================================================================================
+    for prefixedColumns in range(preFixPadding):
+            print("Add prefixed padding ",paddingNumber)
+            new_labels.append("padding_%u"%paddingNumber)
+            new_body[:, targetColumnIndex] = 0.0  # Fill with zeros
+            targetColumnIndex += 1  # Move to the next column
+            paddingNumber += 1
+    #==========================================================================================
+    # Fill the new array with data from the original array
+    targetColumnIndex = 0
+    for originalColumnIndex in range(num_columns):
+        if  dataIn['label'][originalColumnIndex] in labelsToAppendZeroColumns:
+            print("Add padding ",paddingNumber)
+            new_labels.append("padding_%u"%paddingNumber)
+            new_body[:, targetColumnIndex] = 0.0  # Fill with zeros
+            targetColumnIndex += 1  # Move to the next column
+            paddingNumber += 1
+
+        print("Processing #",originalColumnIndex," -> ",dataIn['label'][originalColumnIndex])
+        new_labels.append(dataIn['label'][originalColumnIndex])
+        new_body[:,targetColumnIndex] = body[:,originalColumnIndex]
+        targetColumnIndex += 1
+    #==========================================================================================
+    for postfixedColumns in range(postFixPadding):
+            print("Add postfixed padding ",paddingNumber)
+            new_labels.append("padding_%u"%paddingNumber)
+            new_body[:, targetColumnIndex] = 0.0  # Fill with zeros
+            targetColumnIndex += 1  # Move to the next column
+            paddingNumber += 1
+    #==========================================================================================
+
+    labelDict = dict()
+    for i in range(0,len(new_labels)):
+       labelDict[new_labels[i]]=i
+
+
+    return {
+        'label':       new_labels,
+        'labelLookup': labelDict,
+        'body':        new_body
+    }
+
+
+
+
+if __name__== "__main__":
+  fileInput = sys.argv[1]
+  data  = readCSVFile(fileInput,1.0,0)
+  data  = functionThatFiltersOutColumnsWithStandardDeviation0(data)
+
+  # Append zero columns at specific labels
+  print("Disabled Paddings, to test all outputs trained together!")
+  #if ("lhand" in fileInput):
+  #  labels_to_append_zero_columns = ['lhand_Wrotation', 'lthumb_Zrotation', 'finger1-2.l_Zrotation', 'finger1-3.l_Zrotation', 'finger1-3.l_Xrotation']
+  #  data = functionThatAppendsZeroColumnsByLabels(data, labels_to_append_zero_columns, postFixPadding = 1)
+  
+  column = 0
+  for label in data['label']:
+     thisColumnData = splitNumpyArray(data['body'],column,1,0) 
+     minimum = np.min(thisColumnData)
+     maximum = np.max(thisColumnData)
+     median  = np.median(thisColumnData)
+     mean    = np.mean(thisColumnData)
+     std     = np.std(thisColumnData)
+     var     = np.var(thisColumnData)
+     title_string="%s : Min/Max=%0.2f/%0.2f,Median=%0.2f,Mean=%0.2f,Std=%0.2f,Var=%0.2f" % (label,minimum,maximum,median,mean,std,var)
+     print(title_string)
+     column = column + 1
+
+  print("Writing New CSV file to : compressed.csv")
+  writeCSVFile("compressed.csv",data)
+  #-----------------------------------------------------------
+  os.system("mv %s %s.uncompressed" % (fileInput,fileInput) )
+  os.system("mv compressed.csv %s" % (fileInput) )
+  print("Moved Old CSV file to : %s.uncompressed "%fileInput)
+  print("Moved New CSV file to : %s "%fileInput)
+  #-----------------------------------------------------------
+