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Commit b0a13bfa authored by derekjchow's avatar derekjchow Committed by Sergio Guadarrama
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Clean up documentation. (#1563)

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object_detection/README.md
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...@@ -34,7 +34,7 @@ https://scholar.googleusercontent.com/scholar.bib?q=info:l291WsrB-hQJ:scholar.go ...@@ -34,7 +34,7 @@ https://scholar.googleusercontent.com/scholar.bib?q=info:l291WsrB-hQJ:scholar.go
Quick Start: Quick Start:
* <a href='object_detection_tutorial.ipynb'> * <a href='object_detection_tutorial.ipynb'>
Quick Start: Jupyter notebook for off-the-shelf inference</a><br> Quick Start: Jupyter notebook for off-the-shelf inference</a><br>
* <a href="g3doc/running_pets.md">Quick Start: Training on a pet detector</a><br> * <a href="g3doc/running_pets.md">Quick Start: Training a pet detector</a><br>
Setup: Setup:
* <a href='g3doc/installation.md'>Installation</a><br> * <a href='g3doc/installation.md'>Installation</a><br>
...@@ -66,7 +66,6 @@ release includes: ...@@ -66,7 +66,6 @@ release includes:
* Region-Based Fully Convolutional Networks (R-FCN) with Resnet 101, * Region-Based Fully Convolutional Networks (R-FCN) with Resnet 101,
* Faster RCNN with Resnet 101, * Faster RCNN with Resnet 101,
* Faster RCNN with Inception Resnet v2 * Faster RCNN with Inception Resnet v2
* Mask R-CNN with Resnet 101.
* Frozen weights (trained on the COCO dataset) for each of the above models to * Frozen weights (trained on the COCO dataset) for each of the above models to
be used for out-of-the-box inference purposes. be used for out-of-the-box inference purposes.
* A [Jupyter notebook](object_detection_tutorial.ipynb) for performing * A [Jupyter notebook](object_detection_tutorial.ipynb) for performing
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object_detection/g3doc/detection_model_zoo.md
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...@@ -16,7 +16,7 @@ In the table below, we list each such pre-trained model including: ...@@ -16,7 +16,7 @@ In the table below, we list each such pre-trained model including:
* detector performance on COCO data as measured by the COCO mAP measure. * detector performance on COCO data as measured by the COCO mAP measure.
Here, higher is better, and we only report bounding box mAP rounded to the Here, higher is better, and we only report bounding box mAP rounded to the
nearest integer. nearest integer.
* Output types (currently only `Boxes` or `Boxes, Masks`) * Output types (currently only `Boxes`)
You can un-tar each tar.gz file via, e.g.,: You can un-tar each tar.gz file via, e.g.,:
...@@ -40,4 +40,3 @@ Inside the un-tar'ed directory, you will find: ...@@ -40,4 +40,3 @@ Inside the un-tar'ed directory, you will find:
| [rfcn_resnet101_coco](http://download.tensorflow.org/models/object_detection/rfcn_resnet101_coco_11_06_2017.tar.gz) | medium | 30 | Boxes | | [rfcn_resnet101_coco](http://download.tensorflow.org/models/object_detection/rfcn_resnet101_coco_11_06_2017.tar.gz) | medium | 30 | Boxes |
| [faster_rcnn_resnet101_coco](http://download.tensorflow.org/models/object_detection/faster_rcnn_resnet101_coco_11_06_2017.tar.gz) | medium | 32 | Boxes | | [faster_rcnn_resnet101_coco](http://download.tensorflow.org/models/object_detection/faster_rcnn_resnet101_coco_11_06_2017.tar.gz) | medium | 32 | Boxes |
| [faster_rcnn_inception_resnet_v2_atrous_coco](http://download.tensorflow.org/models/object_detection/faster_rcnn_inception_resnet_v2_atrous_coco_11_06_2017.tar.gz) | slow | 37 | Boxes | | [faster_rcnn_inception_resnet_v2_atrous_coco](http://download.tensorflow.org/models/object_detection/faster_rcnn_inception_resnet_v2_atrous_coco_11_06_2017.tar.gz) | slow | 37 | Boxes |
| [mask_rcnn_resnet101_coco](http://download.tensorflow.org/models/object_detection/) | medium | | Boxes, Masks |
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