Update readme.md

readme.md

+# College CV
+
+This repository contains the implementation of a system to detect yield signs from images and videos.
+It is a proof of concept realization based on a course of machine vision at RheinMain University of Applied
+Sciences in 2017. The scope of the task is to implement some operations on images including but not
+restricted to color segmentation, morphological operations, hough transform for lines and highlighting
+found yield signs.
+
+## Installation and Execution
+
+The least stressful way to set this up is probably to create a virtualenv with python 3.5+ and then
+run `pip install -r requirements`. You find two executables: `main.py` for
+the graphical user interface where you can play around with parameters for the different algorithms
+and `video.py`, a script to process video data.
+
+```
+ > ./main.py --help
+usage: main.py [-h] [--fname FNAME]
+
+optional arguments:
+  -h, --help     show this help message and exit
+  --fname FNAME  open a file directly
+```
+
+```
+ > ./video.py --help
+usage: video.py [-h] [--config CONFIG] [--binary] [--edges] [--save-all]
+                f_in f_out
+
+positional arguments:
+  f_in             input file
+  f_out            output file
+
+optional arguments:
+  -h, --help       show this help message and exit
+  --config CONFIG  configuration file
+  --binary         only apply segmentation and morphology
+  --edges          only apply --binary and edge detection
+  --save-all       save not only the result but all intermediate steps
+```
+
+![GUI screenshot](https://github.com/dreadworks/college-cv/raw/docs/docs/src/gui_morph.png)
+![GUI screenshot](https://github.com/dreadworks/college-cv/raw/docs/docs/src/gui_hough.png)
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