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ModelZoo
ResNet50_tensorflow
Commits
f20630e9
Unverified
Commit
f20630e9
authored
Nov 17, 2017
by
Jonathan Huang
Committed by
GitHub
Nov 17, 2017
Browse files
Merge pull request #2828 from tombstone/minor_updates
minor updates in documentation.
parents
8349eaf8
817eec22
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7 changed files
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17 additions
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15 deletions
+17
-15
research/object_detection/README.md
research/object_detection/README.md
+2
-2
research/object_detection/dataset_tools/create_kitti_tf_record.py
.../object_detection/dataset_tools/create_kitti_tf_record.py
+1
-1
research/object_detection/dataset_tools/create_oid_tf_record.py
...ch/object_detection/dataset_tools/create_oid_tf_record.py
+1
-1
research/object_detection/dataset_tools/create_pascal_tf_record.py
...object_detection/dataset_tools/create_pascal_tf_record.py
+2
-1
research/object_detection/dataset_tools/create_pet_tf_record.py
...ch/object_detection/dataset_tools/create_pet_tf_record.py
+2
-1
research/object_detection/g3doc/installation.md
research/object_detection/g3doc/installation.md
+3
-3
research/object_detection/metrics/offline_eval_map_corloc_test.py
.../object_detection/metrics/offline_eval_map_corloc_test.py
+6
-6
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research/object_detection/README.md
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...
@@ -63,10 +63,10 @@ Extras:
Defining your own model architecture
</a><br>
*
<a
href=
'g3doc/using_your_own_dataset.md'
>
Bringing in your own dataset
</a><br>
*
<a
href=
'g3doc/oid_inference_and_evaluation.md'
>
Inference and evaluation on the Open Images dataset
</a><br>
*
<a
href=
'g3doc/evaluation_protocols.md'
>
Supported object detection evaluation protocols
</a><br>
*
<a
href=
'g3doc/oid_inference_and_evaluation.md'
>
Inference and evaluation on the Open Images dataset
</a><br>
## Getting Help
...
...
research/object_detection/dataset_tools/create_kitti_tf_record.py
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@@ -27,7 +27,7 @@ Converts KITTI detection dataset to TFRecords with a standard format allowing
This can be altered using the flags, see details below.
Example usage:
python create_kitti_tf_record.py \
python
object_detection/dataset_tools/
create_kitti_tf_record.py \
--data_dir=/home/user/kitti \
--output_path=/home/user/kitti.record
"""
...
...
research/object_detection/dataset_tools/create_oid_tf_record.py
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f20630e9
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...
@@ -15,7 +15,7 @@
r
"""Creates TFRecords of Open Images dataset for object detection.
Example usage:
.
/create_oid_tf_record \
python object_detection/dataset_tools
/create_oid_tf_record
.py
\
--input_annotations_csv=/path/to/input/annotations-human-bbox.csv \
--input_images_directory=/path/to/input/image_pixels_directory \
--input_label_map=/path/to/input/labels_bbox_545.labelmap \
...
...
research/object_detection/dataset_tools/create_pascal_tf_record.py
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...
...
@@ -16,7 +16,8 @@
r
"""Convert raw PASCAL dataset to TFRecord for object_detection.
Example usage:
./create_pascal_tf_record --data_dir=/home/user/VOCdevkit \
python object_detection/dataset_tools/create_pascal_tf_record.py \
--data_dir=/home/user/VOCdevkit \
--year=VOC2012 \
--output_path=/home/user/pascal.record
"""
...
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research/object_detection/dataset_tools/create_pet_tf_record.py
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@@ -21,7 +21,8 @@ See: O. M. Parkhi, A. Vedaldi, A. Zisserman, C. V. Jawahar
http://www.robots.ox.ac.uk/~vgg/data/pets/
Example usage:
./create_pet_tf_record --data_dir=/home/user/pet \
python object_detection/dataset_tools/create_pet_tf_record.py \
--data_dir=/home/user/pet \
--output_dir=/home/user/pet/output
"""
...
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research/object_detection/g3doc/installation.md
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@@ -12,9 +12,9 @@ Tensorflow Object Detection API depends on the following libraries:
*
Matplotlib
*
Tensorflow
For detailed steps to install Tensorflow, follow the
[
Tensorflow installation
instructions
](
https://www.tensorflow.org/install/
)
.
A typically user can install
Tensorflow using one of the following commands:
For detailed steps to install Tensorflow, follow the
[
Tensorflow installation
instructions
](
https://www.tensorflow.org/install/
)
.
A typical user can install
Tensorflow using one of the following commands:
```
bash
# For CPU
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research/object_detection/metrics/offline_eval_map_corloc_test.py
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@@ -30,10 +30,10 @@ class OfflineEvalMapCorlocTest(tf.test.TestCase):
result
=
offline_eval
.
_generate_sharded_filenames
(
test_filename
)
self
.
assertEqual
(
result
,
[
test_filename
])
result
=
offline_eval
.
_generate_sharded_filenames
(
'/path/to/@3.
sst
'
)
result
=
offline_eval
.
_generate_sharded_filenames
(
'/path/to/@3.
record
'
)
self
.
assertEqual
(
result
,
[
'/path/to/-00000-of-00003.
sst
'
,
'/path/to/-00001-of-00003.
sst
'
,
'/path/to/-00002-of-00003.
sst
'
'/path/to/-00000-of-00003.
record
'
,
'/path/to/-00001-of-00003.
record
'
,
'/path/to/-00002-of-00003.
record
'
])
result
=
offline_eval
.
_generate_sharded_filenames
(
'/path/to/abc@3'
)
...
...
@@ -46,11 +46,11 @@ class OfflineEvalMapCorlocTest(tf.test.TestCase):
self
.
assertEqual
(
result
,
[
'/path/to/-00000-of-00001'
])
def
test_generateFilenames
(
self
):
test_filenames
=
[
'/path/to/file'
,
'/path/to/@3.
sst
'
]
test_filenames
=
[
'/path/to/file'
,
'/path/to/@3.
record
'
]
result
=
offline_eval
.
_generate_filenames
(
test_filenames
)
self
.
assertEqual
(
result
,
[
'/path/to/file'
,
'/path/to/-00000-of-00003.
sst
'
,
'/path/to/-00001-of-00003.
sst
'
,
'/path/to/-00002-of-00003.
sst
'
'/path/to/file'
,
'/path/to/-00000-of-00003.
record
'
,
'/path/to/-00001-of-00003.
record
'
,
'/path/to/-00002-of-00003.
record
'
])
...
...
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