[UPDATE] upload to PyPi and patch update

README.md

@@ -3,7 +3,7 @@
 imsearch helps to create your own custom, robust & scalable reverse image search engine. This project uses state of the art object detection algorithm ([yolov3](https://pjreddie.com/darknet/yolo/)) at its core to extract the features from an image. It uses an efficient cross-platform similarity search library [NMSLIB](https://github.com/nmslib/nmslib) for similarity search. [Redis](https://redis.io/) is used as a messaging queue between feature extractor and core engine. [MongoDB](https://www.mongodb.com/) is used to store the meta-data of all the indexed images. HD5 file system is used to store the feature vectors extracted from indexed images. 
 
 ## Installation
-For the setup, a simple `install.sh` script can be used.
+For the setup, a simple `install.sh` script can be used or can be installed using `pip`.
 Follow these simple steps to install imsearch library. 
 - Feature extraction is GPU intensive process. So, to make the search real-time, running this engine on GPU enabled machine is recommended. 
 - Install CUDA & NVIDIA graphics drivers ([here](https://medium.com/@taylordenouden/installing-tensorflow-gpu-on-ubuntu-18-04-89a142325138))
@@ -12,6 +12,12 @@ Follow these simple steps to install imsearch library.
 - Install `Redis` ([here](https://www.digitalocean.com/community/tutorials/how-to-install-and-secure-redis-on-ubuntu-18-04))
 - Run following commands 
 ```
+pip install --no-binary :all: nmslib
+pip install imsearch
+```
+
+### Build from source using `install.sh`
+```
 git clone https://github.com/rikenmehta03/imsearch.git
 chmod +x install.sh
 ./install.sh

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name='imsearch',
-    version='0.1.0',
+    version='0.1.1',
     description='A generic framework to build your own reverse image search engine',
     long_description=long_description,
     long_description_content_type="text/markdown",
@@ -16,7 +16,7 @@
     install_requires=['torch', 'torchvision', 'pandas', 'tables', 'redis', 'pymongo', 'nmslib', 'wget', 'opencv-python', 'requests'],
     classifiers=[
         "Programming Language :: Python :: 3",
-        "License :: OSI Approved :: Apache License 2.0",
-        "Operating System :: Linux",
+        "License :: OSI Approved :: Apache Software License",
+        "Operating System :: POSIX :: Linux",
     ]
 )