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minor updates in documentation.
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research/object_detection/README.md

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Defining your own model architecture</a><br>
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* <a href='g3doc/using_your_own_dataset.md'>
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Bringing in your own dataset</a><br>
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* <a href='g3doc/oid_inference_and_evaluation.md'>
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Inference and evaluation on the Open Images dataset</a><br>
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* <a href='g3doc/evaluation_protocols.md'>
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Supported object detection evaluation protocols</a><br>
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* <a href='g3doc/oid_inference_and_evaluation.md'>
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Inference and evaluation on the Open Images dataset</a><br>
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## Getting Help
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research/object_detection/dataset_tools/create_kitti_tf_record.py

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This can be altered using the flags, see details below.
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Example usage:
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python create_kitti_tf_record.py \
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python object_detection/dataset_tools/create_kitti_tf_record.py \
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--data_dir=/home/user/kitti \
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--output_path=/home/user/kitti.record
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"""

research/object_detection/dataset_tools/create_oid_tf_record.py

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r"""Creates TFRecords of Open Images dataset for object detection.
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Example usage:
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./create_oid_tf_record \
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python object_detection/dataset_tools/create_oid_tf_record.py \
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--input_annotations_csv=/path/to/input/annotations-human-bbox.csv \
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--input_images_directory=/path/to/input/image_pixels_directory \
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--input_label_map=/path/to/input/labels_bbox_545.labelmap \

research/object_detection/dataset_tools/create_pascal_tf_record.py

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r"""Convert raw PASCAL dataset to TFRecord for object_detection.
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Example usage:
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./create_pascal_tf_record --data_dir=/home/user/VOCdevkit \
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python object_detection/dataset_tools/create_pascal_tf_record.py \
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--data_dir=/home/user/VOCdevkit \
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--year=VOC2012 \
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--output_path=/home/user/pascal.record
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"""

research/object_detection/dataset_tools/create_pet_tf_record.py

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http://www.robots.ox.ac.uk/~vgg/data/pets/
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Example usage:
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./create_pet_tf_record --data_dir=/home/user/pet \
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python object_detection/dataset_tools/create_pet_tf_record.py \
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--data_dir=/home/user/pet \
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--output_dir=/home/user/pet/output
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"""
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research/object_detection/g3doc/installation.md

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* Matplotlib
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* Tensorflow
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For detailed steps to install Tensorflow, follow the
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[Tensorflow installation instructions](https://www.tensorflow.org/install/).
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A typically user can install Tensorflow using one of the following commands:
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For detailed steps to install Tensorflow, follow the [Tensorflow installation
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instructions](https://www.tensorflow.org/install/). A typical user can install
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Tensorflow using one of the following commands:
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``` bash
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# For CPU

research/object_detection/metrics/offline_eval_map_corloc_test.py

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result = offline_eval._generate_sharded_filenames(test_filename)
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self.assertEqual(result, [test_filename])
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result = offline_eval._generate_sharded_filenames('/path/to/@3.sst')
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result = offline_eval._generate_sharded_filenames('/path/to/@3.record')
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self.assertEqual(result, [
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'/path/to/-00000-of-00003.sst', '/path/to/-00001-of-00003.sst',
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'/path/to/-00002-of-00003.sst'
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'/path/to/-00000-of-00003.record', '/path/to/-00001-of-00003.record',
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'/path/to/-00002-of-00003.record'
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])
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result = offline_eval._generate_sharded_filenames('/path/to/abc@3')
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self.assertEqual(result, ['/path/to/-00000-of-00001'])
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def test_generateFilenames(self):
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test_filenames = ['/path/to/file', '/path/to/@3.sst']
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test_filenames = ['/path/to/file', '/path/to/@3.record']
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result = offline_eval._generate_filenames(test_filenames)
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self.assertEqual(result, [
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'/path/to/file', '/path/to/-00000-of-00003.sst',
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'/path/to/-00001-of-00003.sst', '/path/to/-00002-of-00003.sst'
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'/path/to/file', '/path/to/-00000-of-00003.record',
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'/path/to/-00001-of-00003.record', '/path/to/-00002-of-00003.record'
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])
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