diff --git a/export.py b/export.py
index 8d6805893d1e..ea7f1ebd0b1f 100644
--- a/export.py
+++ b/export.py
@@ -33,7 +33,8 @@
 
 FILE = Path(__file__).resolve()
 ROOT = FILE.parents[0]  # yolov5/ dir
-sys.path.append(ROOT.as_posix())  # add yolov5/ to path
+if str(ROOT) not in sys.path:
+    sys.path.append(str(ROOT))  # add ROOT to PATH
 
 from models.common import Conv
 from models.experimental import attempt_load
@@ -174,7 +175,7 @@ def export_pb(keras_model, im, file, prefix=colorstr('TensorFlow GraphDef:')):
         print(f'\n{prefix} export failure: {e}')
 
 
-def export_tflite(keras_model, im, file, tfl_int8, data, ncalib, prefix=colorstr('TensorFlow Lite:')):
+def export_tflite(keras_model, im, file, int8, data, ncalib, prefix=colorstr('TensorFlow Lite:')):
     # YOLOv5 TensorFlow Lite export
     try:
         import tensorflow as tf
@@ -187,7 +188,7 @@ def export_tflite(keras_model, im, file, tfl_int8, data, ncalib, prefix=colorstr
         converter = tf.lite.TFLiteConverter.from_keras_model(keras_model)
         converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS]
         converter.optimizations = [tf.lite.Optimize.DEFAULT]
-        if tfl_int8:
+        if int8:
             dataset = LoadImages(check_dataset(data)['train'], img_size=imgsz, auto=False)  # representative data
             converter.representative_dataset = lambda: representative_dataset_gen(dataset, ncalib)
             converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
@@ -234,7 +235,8 @@ def run(data=ROOT / 'data/coco128.yaml',  # 'dataset.yaml path'
         inplace=False,  # set YOLOv5 Detect() inplace=True
         train=False,  # model.train() mode
         optimize=False,  # TorchScript: optimize for mobile
-        dynamic=False,  # ONNX: dynamic axes
+        int8=False,  # CoreML/TF INT8 quantization
+        dynamic=False,  # ONNX/TF: dynamic axes
         simplify=False,  # ONNX: simplify model
         opset=12,  # ONNX: opset version
         ):
@@ -288,7 +290,7 @@ def run(data=ROOT / 'data/coco128.yaml',  # 'dataset.yaml path'
         if pb or tfjs:  # pb prerequisite to tfjs
             export_pb(model, im, file)
         if tflite:
-            export_tflite(model, im, file, tfl_int8=False, data=data, ncalib=100)
+            export_tflite(model, im, file, int8=int8, data=data, ncalib=100)
         if tfjs:
             export_tfjs(model, im, file)
 
@@ -309,6 +311,7 @@ def parse_opt():
     parser.add_argument('--inplace', action='store_true', help='set YOLOv5 Detect() inplace=True')
     parser.add_argument('--train', action='store_true', help='model.train() mode')
     parser.add_argument('--optimize', action='store_true', help='TorchScript: optimize for mobile')
+    parser.add_argument('--int8', action='store_true', help='CoreML/TF INT8 quantization')
     parser.add_argument('--dynamic', action='store_true', help='ONNX/TF: dynamic axes')
     parser.add_argument('--simplify', action='store_true', help='ONNX: simplify model')
     parser.add_argument('--opset', type=int, default=13, help='ONNX: opset version')