AffectNet Pipeline

projectmood/datasets/affectnet.py

@@ -7,7 +7,7 @@ from shutil import copyfile
 
 import pandas as pd
 
-logfile = '../logs/affectnet.log'
+logfile = 'affectnet.log'
 
 # Erstellt und konfiguriert die Logdatei
 logging.basicConfig(level=logging.NOTSET, format='%(asctime)s %(levelname)-8s %(message)s',
@@ -45,14 +45,6 @@ csv = os.path.join(curdir, arguments.csv)
 source = os.path.join(curdir, arguments.source)
 destination = os.path.join(curdir, arguments.destination)
 
-if os.path.exists(destination):
-    delete = input(destination + ' existiert. Durch diesen Prozess werden die Daten gelöscht. Fortfahren (y/n): ')
-    if delete == 'y':
-        shutil.rmtree(destination)
-    else:
-        logging.info('process aborted')
-        sys.exit()
-
 def generate_records(csvfile):
     data = pd.read_csv(csvfile, delimiter=',', dtype='a')
 
@@ -65,10 +57,20 @@ def generate_records(csvfile):
         dest = os.path.join(destination, e)
         if not os.path.exists(dest):
             os.makedirs(dest)
+        else:
+            counter[e] = len(os.listdir(dest))
 
     data = zip(labels, imagepaths, valence, arousal)
 
     for d in data:
+        if all(count >= arguments.limit for count in counter.values()):
+            break
+
+        emotion = emodict.get(d[0])
+
+        if emotion not in arguments.emotions or d[2] < arguments.valence or d[3] < arguments.arousal or counter[emotion] >= arguments.limit:
+            continue
+
         img = d[1]
         pathfrom = os.path.join(source, img)
 
@@ -76,20 +78,14 @@ def generate_records(csvfile):
             logging.info(img + ' not found')
             continue
 
-        if all(count == arguments.limit for count in counter.values()):
-            break
-
-        emotion = emodict.get(d[0])
-
-        if emotion not in arguments.emotions or d[2] < float(arguments.valence) or d[3] < float(arguments.arousal) or counter[emotion] == arguments.limit:
-            continue
-
         parent = os.path.join(destination, emotion)
 
         pathto = os.path.join(parent, img.split('/')[1])
-        copyfile(pathfrom, pathto)
-        logging.info('wrote file ' + pathto)
-        counter[emotion] += 1
+
+        if not os.path.isfile(pathto):
+            copyfile(pathfrom, pathto)
+            logging.info('wrote file ' + pathto)
+            counter[emotion] += 1
 
 
 if __name__ == '__main__':