PyArmNN Updates

* Updated setup.py to raise error on mandatory ext
* Updated examples section of main readme
* Added readme to img class
* Moved img class to new subdir

Change-Id: Iea5f6d87c97e571b8ca5636268231506538840c7
Signed-off-by: Éanna Ó Catháin <eanna.ocathain@arm.com>
Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>

1 files changed, 55 insertions, 0 deletions

diff --git a/python/pyarmnn/examples/image_classification/tflite_mobilenetv1_quantized.py b/python/pyarmnn/examples/image_classification/tflite_mobilenetv1_quantized.py
new file mode 100644
index 0000000000..229a9b6778
--- /dev/null
+++ b/python/pyarmnn/examples/image_classification/tflite_mobilenetv1_quantized.py
@@ -0,0 +1,55 @@
+#!/usr/bin/env python3
+# 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()
+
+# 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'
+
+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)
+
+# 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)
+
+# 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]
+
+# 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 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)