diff --git a/README.md b/README.md
index f9cbe85547..14c3d6127f 100644
--- a/README.md
+++ b/README.md
@@ -160,12 +160,7 @@ Contributions to this repository are welcome. Examples of things you can contrib
 You can also [join our team](https://matterport.com/careers/) and help us build even more projects like this one.
 
 ## Requirements
-* Python 3.4+
-
-All required packages are listed in standard file:
-```bash
-pip3 install -r requirements.txt
-```
+Python 3.4, TensorFlow 1.3, Keras 2.0.8 and other common packages listed in `requirements.txt`.
 
 ### MS COCO Requirements:
 To train or test on MS COCO, you'll also need:
@@ -180,12 +175,17 @@ If you use Docker, the code has been verified to work on
 
 
 ## Installation
-1. Clone this repository. The installation as possible using following command:
+1. Install dependencies
+   ```bash
+   pip3 install -r requirements.txt
+   ```
+2. Clone this repository
+3. Run setup from the repository root directory
     ```bash
     python3 setup.py install
     ``` 
-2. Download pre-trained COCO weights (mask_rcnn_coco.h5) from the [releases page](https://github.com/matterport/Mask_RCNN/releases).
-3. (Optional) To train or test on MS COCO install `pycocotools` from one of these repos. They are forks of the original pycocotools with fixes for Python3 and Windows (the official repo doesn't seem to be active anymore).
+3. Download pre-trained COCO weights (mask_rcnn_coco.h5) from the [releases page](https://github.com/matterport/Mask_RCNN/releases).
+4. (Optional) To train or test on MS COCO install `pycocotools` from one of these repos. They are forks of the original pycocotools with fixes for Python3 and Windows (the official repo doesn't seem to be active anymore).
 
     * Linux: https://github.com/waleedka/coco
     * Windows: https://github.com/philferriere/cocoapi.
diff --git a/setup.py b/setup.py
index 57b1e59f7c..7ccc97a8b6 100644
--- a/setup.py
+++ b/setup.py
@@ -3,26 +3,14 @@
 
 >> pip install -r requirements.txt
 >> python setup.py install
-
-For uploading to PyPi follow instructions
-http://peterdowns.com/posts/first-time-with-pypi.html
-
-Pre-release package
->> python setup.py sdist upload -r pypitest
->> pip install --index-url https://test.pypi.org/simple/ your-package
-Release package
->> python setup.py sdist upload -r pypi
->> pip install your-package
 """
 import pip
 import logging
 import pkg_resources
 try:
-    from setuptools import setup, Extension # , Command, find_packages
-    from setuptools.command.build_ext import build_ext
+    from setuptools import setup
 except ImportError:
-    from distutils.core import setup, Extension # , Command, find_packages
-    from distutils.command.build_ext import build_ext
+    from distutils.core import setup
 
 
 def _parse_requirements(file_path):
@@ -43,22 +31,18 @@ def _parse_requirements(file_path):
     logging.warning('Fail load requirements file, so using default ones.')
     install_reqs = []
 
-
 setup(
-    name='mrcnn',
+    name='mask-rcnn',
     version='2.1',
     url='https://github.com/matterport/Mask_RCNN',
-
     author='Matterport',
-    author_email='',  # todo
+    author_email='waleed.abdulla@gmail.com',
     license='MIT',
-    description='Mask R-CNN: object detection & classification & segmentation',
-
+    description='Mask R-CNN for object detection and instance segmentation',
     packages=["mrcnn"],
-    cmdclass={'build_ext': build_ext},
     install_requires=install_reqs,
     include_package_data=True,
-
+    python_requires='>=3.4',
     long_description="""This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. 
 The model generates bounding boxes and segmentation masks for each instance of an object in the image. 
 It's based on Feature Pyramid Network (FPN) and a ResNet101 backbone.""",
@@ -72,11 +56,13 @@ def _parse_requirements(file_path):
         "License :: OSI Approved :: MIT License",
         "Natural Language :: English",
         "Operating System :: OS Independent",
-        "Topic :: Scientific/Engineering :: Image object detection",
+        "Topic :: Scientific/Engineering :: Artificial Intelligence",
         "Topic :: Scientific/Engineering :: Image Recognition",
+        "Topic :: Scientific/Engineering :: Visualization",
         "Topic :: Scientific/Engineering :: Image Segmentation",
         'Programming Language :: Python :: 3.4',
         'Programming Language :: Python :: 3.5',
         'Programming Language :: Python :: 3.6',
     ],
+    keywords="image instance segmentation object detection mask rcnn r-cnn tensorflow keras",
 )