Tool for generating on-device image test inputs

PiperOrigin-RevId: 292015086
Change-Id: I6dc3b4dddcaadf87027fb51ed31b691ddfd40e7e

tensorflow/lite/tools/BUILD

@@ -38,6 +38,34 @@ py_test(
     ],
 )
 
+py_binary(
+    name = "convert_image_to_csv",
+    srcs = ["convert_image_to_csv.py"],
+    python_version = "PY3",
+    srcs_version = "PY2AND3",
+    deps = [
+        "//tensorflow:tensorflow_py_no_contrib",
+        "//tensorflow/python:platform",
+        "//tensorflow/python/keras",
+        "//third_party/py/numpy",
+        "@six_archive//:six",
+    ],
+)
+
+py_test(
+    name = "convert_image_to_csv_test",
+    srcs = ["convert_image_to_csv_test.py"],
+    data = ["//tensorflow/core:image_testdata"],
+    python_version = "PY3",
+    srcs_version = "PY2AND3",
+    deps = [
+        ":convert_image_to_csv",
+        "//tensorflow/python:client_testlib",
+        "//tensorflow/python:framework_test_lib",
+        "//tensorflow/python:platform",
+    ],
+)
+
 tf_cc_binary(
     name = "generate_op_registrations",
     srcs = ["gen_op_registration_main.cc"],

tensorflow/lite/tools/convert_image_to_csv.py

@@ -0,0 +1,115 @@
+# Lint as: python2, python3
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+r"""This tool converts an image file into a CSV data array.
+
+Designed to help create test inputs that can be shared between Python and
+on-device test cases to investigate accuracy issues.
+
+Example usage:
+
+python convert_image_to_csv.py some_image.jpg --width=16 --height=20 \
+  --want_grayscale
+"""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import argparse
+import sys
+
+from tensorflow.python.client import session
+from tensorflow.python.framework import ops
+from tensorflow.python.framework.errors_impl import NotFoundError
+from tensorflow.python.ops import image_ops
+from tensorflow.python.ops import io_ops
+from tensorflow.python.platform import app
+
+
+def get_image(width, height, want_grayscale, filepath):
+  """Returns an image loaded into an np.ndarray with dims [height, width, (3 or 1)].
+
+  Args:
+    width: Width to rescale the image to.
+    height: Height to rescale the image to.
+    want_grayscale: Whether the result should be converted to grayscale.
+    filepath: Path of the image file..
+
+  Returns:
+    np.ndarray of shape (height, width, channels) where channels is 1 if
+      want_grayscale is true, otherwise 3.
+  """
+  with ops.Graph().as_default():
+    with session.Session():
+      file_data = io_ops.read_file(filepath)
+      channels = 1 if want_grayscale else 3
+      image_tensor = image_ops.decode_image(file_data,
+                                            channels=channels).eval()
+      resized_tensor = image_ops.resize_images_v2(
+          image_tensor, (height, width)).eval()
+  return resized_tensor
+
+
+def array_to_int_csv(array_data):
+  """Converts all elements in a numerical array to a comma-separated string.
+
+  Args:
+    array_data: Numerical array to convert.
+
+  Returns:
+    String containing array values as integers, separated by commas.
+  """
+  flattened_array = array_data.flatten()
+  array_as_strings = [item.astype(int).astype(str) for item in flattened_array]
+  return ','.join(array_as_strings)
+
+
+def run_main(_):
+  """Application run loop."""
+  parser = argparse.ArgumentParser(
+      description='Loads JPEG or PNG input files, resizes them, optionally'
+      ' converts to grayscale, and writes out as comma-separated variables,'
+      ' one image per row.')
+  parser.add_argument(
+      'image_file_names',
+      type=str,
+      nargs='+',
+      help='List of paths to the input images.')
+  parser.add_argument(
+      '--width', type=int, default=96, help='Width to scale images to.')
+  parser.add_argument(
+      '--height', type=int, default=96, help='Height to scale images to.')
+  parser.add_argument(
+      '--want_grayscale',
+      action='store_true',
+      help='Whether to convert the image to monochrome.')
+  args = parser.parse_args()
+
+  for image_file_name in args.image_file_names:
+    try:
+      image_data = get_image(args.width, args.height, args.want_grayscale,
+                             image_file_name)
+      print(array_to_int_csv(image_data))
+    except NotFoundError:
+      sys.stderr.write('Image file not found at {0}\n'.format(image_file_name))
+      sys.exit(1)
+
+
+def main():
+  app.run(main=run_main, argv=sys.argv[:1])
+
+
+if __name__ == '__main__':
+  main()

tensorflow/lite/tools/convert_image_to_csv_test.py

@@ -0,0 +1,85 @@
+# Lint as: python2, python3
+# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests image file conversion utilities."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import os
+
+import numpy as np
+
+from tensorflow.lite.tools import convert_image_to_csv
+from tensorflow.python.framework import test_util
+from tensorflow.python.framework.errors_impl import NotFoundError
+from tensorflow.python.platform import resource_loader
+from tensorflow.python.platform import test
+
+PREFIX_PATH = resource_loader.get_path_to_datafile("../../core/lib/")
+
+
+class ConvertImageToCsvTest(test_util.TensorFlowTestCase):
+
+  def testGetImageRaisesMissingFile(self):
+    image_path = os.path.join(PREFIX_PATH, "jpeg", "testdata", "no_such.jpg")
+    with self.assertRaises(NotFoundError):
+      _ = convert_image_to_csv.get_image(64, 96, False, image_path)
+
+  def testGetImageSizeIsCorrect(self):
+    image_path = os.path.join(PREFIX_PATH, "jpeg", "testdata", "small.jpg")
+    image_data = convert_image_to_csv.get_image(64, 96, False, image_path)
+    self.assertEqual((96, 64, 3), image_data.shape)
+
+  def testGetImageConvertsToGrayscale(self):
+    image_path = os.path.join(PREFIX_PATH, "jpeg", "testdata", "medium.jpg")
+    image_data = convert_image_to_csv.get_image(40, 20, True, image_path)
+    self.assertEqual((20, 40, 1), image_data.shape)
+
+  def testGetImageCanLoadPng(self):
+    image_path = os.path.join(PREFIX_PATH, "png", "testdata", "lena_rgba.png")
+    image_data = convert_image_to_csv.get_image(10, 10, False, image_path)
+    self.assertEqual((10, 10, 3), image_data.shape)
+
+  def testGetImageConvertsGrayscaleToColor(self):
+    image_path = os.path.join(PREFIX_PATH, "png", "testdata", "lena_gray.png")
+    image_data = convert_image_to_csv.get_image(23, 19, False, image_path)
+    self.assertEqual((19, 23, 3), image_data.shape)
+
+  def testGetImageColorValuesInRange(self):
+    image_path = os.path.join(PREFIX_PATH, "jpeg", "testdata", "small.jpg")
+    image_data = convert_image_to_csv.get_image(47, 31, False, image_path)
+    self.assertLessEqual(0, np.min(image_data))
+    self.assertGreaterEqual(255, np.max(image_data))
+
+  def testGetImageGrayscaleValuesInRange(self):
+    image_path = os.path.join(PREFIX_PATH, "jpeg", "testdata", "small.jpg")
+    image_data = convert_image_to_csv.get_image(27, 33, True, image_path)
+    self.assertLessEqual(0, np.min(image_data))
+    self.assertGreaterEqual(255, np.max(image_data))
+
+  def testArrayToIntCsv(self):
+    csv_string = convert_image_to_csv.array_to_int_csv(
+        np.array([[1, 2], [3, 4]]))
+    self.assertEqual("1,2,3,4", csv_string)
+
+  def testArrayToIntCsvRounding(self):
+    csv_string = convert_image_to_csv.array_to_int_csv(
+        np.array([[1.0, 2.0], [3.0, 4.0]]))
+    self.assertEqual("1,2,3,4", csv_string)
+
+
+if __name__ == "__main__":
+  test.main()