Object-Tracking-and-Detection

I pursued my summer intern related to image processing. The aim was to track and count objects(vehicles) in a real time scenario. I used various algorithms such as MOG Background subtraction , Haar cascading , Kalman Filtering , Blob Analysis for tracking purpose. Main objective was to keep track of information of vehicles entering and assign them proper ID's and store/write various informations such as (time stamps, area ,aspect ratio) into a file.

######## To run the code -(code.py) #######

1. Enter Path of video file at the start of program

2. Run the file and then enter the coordinates for two lines to be drawn(NOTE: Coordinates are given as a ratio b.w (0,1)).

3. User can change the parameters to filter out bad blobs by modifying the line 362 in code.py

4. At the end I have displayed the trackedlist which contains ID's of the tracked objects and according to these ID's I have written the output of (time stamp, centerpositions,blobarea,blobaspect ratio) as pairs to file "info.txt" .

####### Opencv(3.1) Installation and its Various dependencies : ########

Follow these steps to install opencv(3.1) with python 2.7 and the required dependencies.

1. $ sudo apt-get install build-essential cmake pkg-config

2. Install Image I/O libraries - $ sudo apt-get install libjpeg8-dev libtiff5-dev libjasper-dev libpng12-dev

3. Packages for processing video streams - $ sudo apt-get install libavcodec-dev libavformat-dev libswscale-devlibv4l-dev $ sudo apt-get install libxvidcore-dev libx264-dev

4. Module for handling GUI operations - $ sudo apt-get install libgtk-3-dev

5. Library for optimising various functionalities inside opencv- $ sudo apt-get install libatlas-base-dev gfortran

6. Install python development headers and libraries - $ sudo apt-get install python2.7-dev python3.5-dev

7. Download the opencv source - $ cd ~ $ wget -O opencv.zip https://github.com/Itseez/opencv/archive/3.1.0.zip $ unzip opencv.zip

8. Download opencv_contrib repo as well - $ wget -O opencv_contrib.zip https://github.com/Itseez/opencv_contrib/archive/3.1.0.zip $ unzip opencv_contrib.zip

9. Setup python environment - $ cd ~ $ wget https://bootstrap.pypa.io/get-pip.py $ sudo python get-pip.py

10. Install numpy ( a Python package for numerical processing) $ pip install numpy

11. Setup and configure our build using cmake - $ cd /opencv-3.1.0/ $ mkdir build $ cd build $ cmake -D CMAKE_BUILD_TYPE=RELEASE
    -D CMAKE_INSTALL_PREFIX=/usr/local
    -D INSTALL_PYTHON_EXAMPLES=ON
    -D INSTALL_C_EXAMPLES=OFF
    -D OPENCV_EXTRA_MODULES_PATH=/opencv_contrib- 3.1.0/modules
    -D PYTHON_EXECUTABLE=~/.virtualenvs/cv/bin/python
    -D BUILD_EXAMPLES=ON ..

Note: If you are getting error related to stdlib.h : No such file or directory during either cmake or make you will need to include the following option to Cmake : -D ENABLE_PRECOMPILED_HEADERS=OFF . In this case, I would suggest deleting your build directory , recreating it and re-run cmake with above options included.

12. Finally execute cmake to configure our build - $ make clean $ make

13. This step is to install opencv - $ sudo make install $ sudo ldconfig

14. After running sudo make install , your Python 2.7 bindings for OpenCV 3 should now be located in /usr/local/lib/python-2.7/site- packages/. You can verify this using the ls command - $ ls -l /usr/local/lib/python2.7/site-packages/

15. Test your opecv installation - $ python $ import cv2 If this doesnt show any error then you have successfully installed opencv

$ cv2.version This shows you the version of opencv installed.