Add instructions for downloading pycocotools to the installation.

PiperOrigin-RevId: 185555440

research/object_detection/g3doc/installation.md

@@ -4,13 +4,14 @@
 
 Tensorflow Object Detection API depends on the following libraries:
 
-* Protobuf 2.6
-* Pillow 1.0
-* lxml
-* tf Slim (which is included in the "tensorflow/models/research/" checkout)
-* Jupyter notebook
-* Matplotlib
-* Tensorflow
+*   Protobuf 2.6
+*   Pillow 1.0
+*   lxml
+*   tf Slim (which is included in the "tensorflow/models/research/" checkout)
+*   Jupyter notebook
+*   Matplotlib
+*   Tensorflow
+*   cocoapi
 
 For detailed steps to install Tensorflow, follow the [Tensorflow installation
 instructions](https://www.tensorflow.org/install/). A typical user can install
@@ -40,6 +41,25 @@ sudo pip install jupyter
 sudo pip install matplotlib
 ```
 
+## COCO API installation
+
+Download the
+<a href="https://github.com/cocodataset/cocoapi" target=_blank>cocoapi</a> and
+copy the pycocotools subfolder to the tensorflow/models/research directory if
+you are interested in using COCO evaluation metrics. The default metrics are
+based on those used in Pascal VOC evaluation. To use the COCO object detection
+metrics add `metrics_set: "coco_detection_metrics"` to the `eval_config` message
+in the config file. To use the COCO instance segmentation metrics add
+`metrics_set: "coco_mask_metrics"` to the `eval_config` message in the config
+file.
+
+```bash
+git clone https://github.com/cocodataset/cocoapi.git
+cd cocoapi/PythonAPI
+make
+cp -r pycocotools <path_to_tensorflow>/models/research/
+```
+
 ## Protobuf Compilation
 
 The Tensorflow Object Detection API uses Protobufs to configure model and