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test_generate_tfrecord.py
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test_generate_tfrecord.py
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import os
import PIL
import generate_tfrecord
import numpy as np
import pandas as pd
import tensorflow as tf
class CSVToTFExampleTest(tf.test.TestCase):
def _assertProtoEqual(self, proto_field, expectation):
proto_list = [p for p in proto_field]
self.assertListEqual(proto_list, expectation)
def test_csv_to_tf_example_one_raccoon_per_file(self):
"""Generate tf records for one raccoon from one file."""
image_file_name = 'tmp_raccoon_image.jpg'
image_data = np.random.rand(256, 256, 3)
save_path = os.path.join(self.get_temp_dir(), image_file_name)
image = PIL.Image.fromarray(image_data, 'RGB')
image.save(save_path)
column_names = ['filename', 'width', 'height', 'class', 'xmin', 'ymin', 'xmax', 'ymax']
raccoon_data = [('tmp_raccoon_image.jpg', 256, 256, 'raccoon', 64, 64, 192, 192)]
raccoon_df = pd.DataFrame(raccoon_data, columns=column_names)
grouped = generate_tfrecord.split(raccoon_df, 'filename')
for group in grouped:
example = generate_tfrecord.create_tf_example(group, self.get_temp_dir())
self._assertProtoEqual(
example.features.feature['image/height'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/width'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/filename'].bytes_list.value,
[image_file_name.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/source_id'].bytes_list.value,
[image_file_name.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/format'].bytes_list.value, [b'jpg'])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmin'].float_list.value,
[0.25])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymin'].float_list.value,
[0.25])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmax'].float_list.value,
[0.75])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymax'].float_list.value,
[0.75])
self._assertProtoEqual(
example.features.feature['image/object/class/text'].bytes_list.value,
[b'raccoon'])
self._assertProtoEqual(
example.features.feature['image/object/class/label'].int64_list.value,
[1])
def test_csv_to_tf_example_multiple_raccoons_per_file(self):
"""Generate tf records for multiple raccoons from one file."""
image_file_name = 'tmp_raccoon_image.jpg'
image_data = np.random.rand(256, 256, 3)
save_path = os.path.join(self.get_temp_dir(), image_file_name)
image = PIL.Image.fromarray(image_data, 'RGB')
image.save(save_path)
column_names = ['filename', 'width', 'height', 'class', 'xmin', 'ymin', 'xmax', 'ymax']
raccoon_data = [('tmp_raccoon_image.jpg', 256, 256, 'raccoon', 64, 64, 192, 192),
('tmp_raccoon_image.jpg', 256, 256, 'raccoon', 96, 96, 128, 128)]
raccoon_df = pd.DataFrame(raccoon_data, columns=column_names)
grouped = generate_tfrecord.split(raccoon_df, 'filename')
for group in grouped:
example = generate_tfrecord.create_tf_example(group, self.get_temp_dir())
self._assertProtoEqual(
example.features.feature['image/height'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/width'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/filename'].bytes_list.value,
[image_file_name.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/source_id'].bytes_list.value,
[image_file_name.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/format'].bytes_list.value, [b'jpg'])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmin'].float_list.value,
[0.25, 0.375])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymin'].float_list.value,
[0.25, 0.375])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmax'].float_list.value,
[0.75, 0.5])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymax'].float_list.value,
[0.75, 0.5])
self._assertProtoEqual(
example.features.feature['image/object/class/text'].bytes_list.value,
[b'raccoon', b'raccoon'])
self._assertProtoEqual(
example.features.feature['image/object/class/label'].int64_list.value,
[1, 1])
def test_csv_to_tf_example_one_raccoons_multiple_files(self):
"""Generate tf records for one raccoon for multiple files."""
image_file_one = 'tmp_raccoon_image_1.jpg'
image_file_two = 'tmp_raccoon_image_2.jpg'
image_data = np.random.rand(256, 256, 3)
save_path_one = os.path.join(self.get_temp_dir(), image_file_one)
save_path_two = os.path.join(self.get_temp_dir(), image_file_two)
image = PIL.Image.fromarray(image_data, 'RGB')
image.save(save_path_one)
image.save(save_path_two)
column_names = ['filename', 'width', 'height', 'class', 'xmin', 'ymin', 'xmax', 'ymax']
raccoon_data = [('tmp_raccoon_image_1.jpg', 256, 256, 'raccoon', 64, 64, 192, 192),
('tmp_raccoon_image_2.jpg', 256, 256, 'raccoon', 96, 96, 128, 128)]
raccoon_df = pd.DataFrame(raccoon_data, columns=column_names)
grouped = generate_tfrecord.split(raccoon_df, 'filename')
for group in grouped:
if group.filename == image_file_one:
example = generate_tfrecord.create_tf_example(group, self.get_temp_dir())
self._assertProtoEqual(
example.features.feature['image/height'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/width'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/filename'].bytes_list.value,
[image_file_one.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/source_id'].bytes_list.value,
[image_file_one.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/format'].bytes_list.value, [b'jpg'])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmin'].float_list.value,
[0.25])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymin'].float_list.value,
[0.25])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmax'].float_list.value,
[0.75])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymax'].float_list.value,
[0.75])
self._assertProtoEqual(
example.features.feature['image/object/class/text'].bytes_list.value,
[b'raccoon'])
self._assertProtoEqual(
example.features.feature['image/object/class/label'].int64_list.value,
[1])
elif group.filename == image_file_two:
example = generate_tfrecord.create_tf_example(group, self.get_temp_dir())
self._assertProtoEqual(
example.features.feature['image/height'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/width'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/filename'].bytes_list.value,
[image_file_two.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/source_id'].bytes_list.value,
[image_file_two.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/format'].bytes_list.value, [b'jpg'])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmin'].float_list.value,
[0.375])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymin'].float_list.value,
[0.375])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmax'].float_list.value,
[0.5])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymax'].float_list.value,
[0.5])
self._assertProtoEqual(
example.features.feature['image/object/class/text'].bytes_list.value,
[b'raccoon'])
self._assertProtoEqual(
example.features.feature['image/object/class/label'].int64_list.value,
[1])
def test_csv_to_tf_example_multiple_raccoons_multiple_files(self):
"""Generate tf records for multiple raccoons for multiple files."""
image_file_one = 'tmp_raccoon_image_1.jpg'
image_file_two = 'tmp_raccoon_image_2.jpg'
image_data = np.random.rand(256, 256, 3)
save_path_one = os.path.join(self.get_temp_dir(), image_file_one)
save_path_two = os.path.join(self.get_temp_dir(), image_file_two)
image = PIL.Image.fromarray(image_data, 'RGB')
image.save(save_path_one)
image.save(save_path_two)
column_names = ['filename', 'width', 'height', 'class', 'xmin', 'ymin', 'xmax', 'ymax']
raccoon_data = [('tmp_raccoon_image_1.jpg', 256, 256, 'raccoon', 64, 64, 192, 192),
('tmp_raccoon_image_1.jpg', 256, 256, 'raccoon', 32, 32, 96, 96),
('tmp_raccoon_image_2.jpg', 256, 256, 'raccoon', 96, 96, 128, 128)]
raccoon_df = pd.DataFrame(raccoon_data, columns=column_names)
grouped = generate_tfrecord.split(raccoon_df, 'filename')
for group in grouped:
if group.filename == image_file_one:
example = generate_tfrecord.create_tf_example(group, self.get_temp_dir())
self._assertProtoEqual(
example.features.feature['image/height'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/width'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/filename'].bytes_list.value,
[image_file_one.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/source_id'].bytes_list.value,
[image_file_one.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/format'].bytes_list.value, [b'jpg'])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmin'].float_list.value,
[0.25, 0.125])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymin'].float_list.value,
[0.25, 0.125])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmax'].float_list.value,
[0.75, 0.375])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymax'].float_list.value,
[0.75, 0.375])
self._assertProtoEqual(
example.features.feature['image/object/class/text'].bytes_list.value,
[b'raccoon', b'raccoon'])
self._assertProtoEqual(
example.features.feature['image/object/class/label'].int64_list.value,
[1, 1])
elif group.filename == image_file_two:
example = generate_tfrecord.create_tf_example(group, self.get_temp_dir())
self._assertProtoEqual(
example.features.feature['image/height'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/width'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/filename'].bytes_list.value,
[image_file_two.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/source_id'].bytes_list.value,
[image_file_two.encode('utf-8')])
self._assertProtoEqual(
example.features.feature['image/format'].bytes_list.value, [b'jpg'])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmin'].float_list.value,
[0.375])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymin'].float_list.value,
[0.375])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmax'].float_list.value,
[0.5])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymax'].float_list.value,
[0.5])
self._assertProtoEqual(
example.features.feature['image/object/class/text'].bytes_list.value,
[b'raccoon'])
self._assertProtoEqual(
example.features.feature['image/object/class/label'].int64_list.value,
[1])