Add example script and update pip installation method

Author: salaniz

README.md

@@ -7,19 +7,21 @@ Evaluation codes for MS COCO caption generation.
 This repository provides Python 3 support for the caption evaluation metrics used for the MS COCO dataset.
 
 The code is derived from the original repository that supports Python 2.7: https://github.com/tylin/coco-caption.  
-Caption evaluation depends on the COCO API that natively supports Python 3 (see Requirements).
+Caption evaluation depends on the COCO API that natively supports Python 3.
 
 ## Requirements ##
 - Java 1.8.0
 - Python 3
-- pycocotools (COCO Python API): https://github.com/cocodataset/cocoapi
 
 ## Installation ##
-To install pycocoevalcap and the pycocotools dependency, run:
+To install pycocoevalcap and the pycocotools dependency (https://github.com/cocodataset/cocoapi), run:
 ```
-pip install git+https://github.com/salaniz/pycocoevalcap
+pip install pycocoevalcap
 ```
 
+## Usage ##
+See the example script: [example/coco_eval_example.py](example/coco_eval_example.py)
+
 ## Files ##
 ./
 - eval.py: The file includes COCOEavlCap class that can be used to evaluate results on COCO.

example/captions_val2014.json

@@ -0,0 +1,25 @@
+from pycocotools.coco import COCO
+from pycocoevalcap.eval import COCOEvalCap
+
+annotation_file = 'captions_val2014.json'
+results_file = 'captions_val2014_fakecap_results.json'
+
+# create coco object and coco_result object
+coco = COCO(annotation_file)
+coco_result = coco.loadRes(results_file)
+
+# create coco_eval object by taking coco and coco_result
+coco_eval = COCOEvalCap(coco, coco_result)
+
+# evaluate on a subset of images by setting
+# coco_eval.params['image_id'] = coco_result.getImgIds()
+# please remove this line when evaluating the full validation set
+coco_eval.params['image_id'] = coco_result.getImgIds()
+
+# evaluate results
+# SPICE will take a few minutes the first time, but speeds up due to caching
+coco_eval.evaluate()
+
+# print output evaluation scores
+for metric, score in coco_eval.eval.items():
+    print(f'{metric}: {score:.3f}')

example/captions_val2014_fakecap_results.json

@@ -3,11 +3,20 @@
 # Prepend pycocoevalcap to package names
 package_names = ['pycocoevalcap.'+p for p in find_namespace_packages()]
 
+with open("README.md", "r") as fh:
+    readme = fh.read()
+
 setup(
     name='pycocoevalcap',
-    version=1.1,
+    version=1.2,
+    maintainer='salaniz',
+    description="MS-COCO Caption Evaluation for Python 3",
+    long_description=readme,
+    long_description_content_type="text/markdown",
+    url="https://github.com/salaniz/pycocoevalcap",
     packages=['pycocoevalcap']+package_names,
     package_dir={'pycocoevalcap': '.'},
     package_data={'': ['*.jar', '*.gz']},
-    install_requires=['pycocotools>=2.0.0']
+    install_requires=['pycocotools>=2.0.2'],
+    python_requires='>=3'
 )