first commit

lib/facial_recognition/faceRecognizerTrainer.py

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+import os, sys, csv, cv2
+import numpy as np
+
+if 1 == len(sys.argv):
+    print('Try running: FaceRecognizerTrainer.py <path/to/prepared_data.csv>', file = sys.stderr)
+    sys.exit(1)
+
+# Init
+PREPARED_DATA_PATH = sys.argv[1]
+images             = []
+labels             = []
+
+if not os.path.isfile(PREPARED_DATA_PATH):
+    print("No file at '{}'".format(PREPARED_DATA_PATH), file = sys.stderr)
+    sys.exit(1)
+
+with open(PREPARED_DATA_PATH, 'rt') as csvFile:
+    for csvRow in csv.reader(csvFile, delimiter = ';', quotechar = '"'):
+        # Expected row should contain: ['/path/to/file', 'label']
+        if '' != csvRow[0] and '' != csvRow[1]:
+            image = cv2.imread(csvRow[0], 0)
+
+            if image is None:
+                print("Could not read image '{}'".format(csvRow[0]))
+                continue
+
+            images.append(image)
+            labels.append(int(csvRow[1]))
+
+if(0 == len(images)):
+    print('No data found for training!', file = sys.stderr)
+    sys.exit(1)
+
+# Create an LBPH model for face recognition and train it
+# with the images and labels read from the given CSV file
+(major, minor, _) = cv2.__version__.split(".")
+major = int(major)
+minor = int(minor)
+
+if (major<3 and minor<7) or minor<3:
+    model = cv2.createLBPHFaceRecognizer(2, 10, 10, 10)
+elif major == 4 and minor > 2:
+    model = cv2.face.LBPHFaceRecognizer_create(2, 10, 10, 10)
+else:
+    cv2.face
+    model = cv2.face.createLBPHFaceRecognizer(2, 10, 10, 10)
+
+
+#model = cv2.createLBPHFaceRecognizer(2, 10, 10, 10)
+model.train(images, np.array(labels))
+model.save("{}/lbph_model.xml".format(os.path.dirname(PREPARED_DATA_PATH)))
+
+print('Successfully trained FaceRecognizer!')