1 files changed, 35 insertions, 36 deletions
diff --git a/python/pyarmnn/examples/image_classification/tflite_mobilenetv1_quantized.py b/python/pyarmnn/examples/image_classification/tflite_mobilenetv1_quantized.py
index 229a9b6778..6b35f63a00 100644
--- a/python/pyarmnn/examples/image_classification/tflite_mobilenetv1_quantized.py
+++ b/python/pyarmnn/examples/image_classification/tflite_mobilenetv1_quantized.py
@@ -2,54 +2,53 @@
 # Copyright © 2020 NXP and Contributors. All rights reserved.
 # SPDX-License-Identifier: MIT
 
-import numpy as np
-import pyarmnn as ann
 import example_utils as eu
 import os
 
-args = eu.parse_command_line()
+if __name__ == "__main__":
+    args = eu.parse_command_line()
 
-# names of the files in the archive
-labels_filename = 'labels_mobilenet_quant_v1_224.txt'
-model_filename = 'mobilenet_v1_1.0_224_quant.tflite'
-archive_filename = 'mobilenet_v1_1.0_224_quant_and_labels.zip'
+    # names of the files in the archive
+    labels_filename = 'labels_mobilenet_quant_v1_224.txt'
+    model_filename = 'mobilenet_v1_1.0_224_quant.tflite'
+    archive_filename = 'mobilenet_v1_1.0_224_quant_and_labels.zip'
 
-archive_url = \
-    'https://storage.googleapis.com/download.tensorflow.org/models/tflite/mobilenet_v1_1.0_224_quant_and_labels.zip'
+    archive_url = \
+        'https://storage.googleapis.com/download.tensorflow.org/models/tflite/mobilenet_v1_1.0_224_quant_and_labels.zip'
 
-model_filename, labels_filename = eu.get_model_and_labels(args.model_dir, model_filename, labels_filename,
-                                                          archive_filename, archive_url)
+    model_filename, labels_filename = eu.get_model_and_labels(args.model_dir, model_filename, labels_filename,
+                                                              archive_filename, archive_url)
 
-image_filenames = eu.get_images(args.data_dir)
+    image_filenames = eu.get_images(args.data_dir)
 
-# all 3 resources must exist to proceed further
-assert os.path.exists(labels_filename)
-assert os.path.exists(model_filename)
-assert image_filenames
-for im in image_filenames:
-    assert(os.path.exists(im))
+    # all 3 resources must exist to proceed further
+    assert os.path.exists(labels_filename)
+    assert os.path.exists(model_filename)
+    assert image_filenames
+    for im in image_filenames:
+        assert(os.path.exists(im))
 
-# Create a network from the model file
-net_id, graph_id, parser, runtime = eu.create_tflite_network(model_filename)
+    # Create a network from the model file
+    net_id, graph_id, parser, runtime = eu.create_tflite_network(model_filename)
 
-# Load input information from the model
-# tflite has all the need information in the model unlike other formats
-input_names = parser.GetSubgraphInputTensorNames(graph_id)
-assert len(input_names) == 1  # there should be 1 input tensor in mobilenet
+    # Load input information from the model
+    # tflite has all the need information in the model unlike other formats
+    input_names = parser.GetSubgraphInputTensorNames(graph_id)
+    assert len(input_names) == 1  # there should be 1 input tensor in mobilenet
 
-input_binding_info = parser.GetNetworkInputBindingInfo(graph_id, input_names[0])
-input_width = input_binding_info[1].GetShape()[1]
-input_height = input_binding_info[1].GetShape()[2]
+    input_binding_info = parser.GetNetworkInputBindingInfo(graph_id, input_names[0])
+    input_width = input_binding_info[1].GetShape()[1]
+    input_height = input_binding_info[1].GetShape()[2]
 
-# Load output information from the model and create output tensors
-output_names = parser.GetSubgraphOutputTensorNames(graph_id)
-assert len(output_names) == 1  # and only one output tensor
-output_binding_info = parser.GetNetworkOutputBindingInfo(graph_id, output_names[0])
+    # Load output information from the model and create output tensors
+    output_names = parser.GetSubgraphOutputTensorNames(graph_id)
+    assert len(output_names) == 1  # and only one output tensor
+    output_binding_info = parser.GetNetworkOutputBindingInfo(graph_id, output_names[0])
 
-# Load labels file
-labels = eu.load_labels(labels_filename)
+    # Load labels file
+    labels = eu.load_labels(labels_filename)
 
-# Load images and resize to expected size
-images = eu.load_images(image_filenames, input_width, input_height)
+    # Load images and resize to expected size
+    images = eu.load_images(image_filenames, input_width, input_height)
 
-eu.run_inference(runtime, net_id, images, labels, input_binding_info, output_binding_info)
+    eu.run_inference(runtime, net_id, images, labels, input_binding_info, output_binding_info)