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CPPND: Capstone Hot Dog Detector in a video feed

This program detects hot dogs in videos (at least it tries as hard as it can).

Here is a rundown on the project's structure:

/src/

    main.cpp              - the starting point and detection logic
    Model.h               - Class that creates a neural network from the Yolo3
    Model.cpp               trained dataset and works with that network
    Detector.h            - Class that process video frames
    Detector.cpp            and opens a video file

/data/

    coco.names            - classifier labels for Yolo3
    hotdogs.mp4           - input video file
    yolov3-tiny.cfg       - Yolo3 configuration
    yolov3-tiny.weights   - Yolo3 trained network

Rubrics I addressed in this project:

  • README
  • Compiling and testing
  • Loops, Functions, I/O
    • The project reads data from a file and process the data: main.cpp:19, model.cpp:15
  • Object Oriented Programming
    • The project uses Object Oriented Programming techniques: Detector.h, Model.h
    • Classes use appropriate access specifiers for class members: Detector.h:7, Detector.h:13, Model.h:7, Model.h:15
    • Class constructors utilize member initialization lists: Detector.h:8, Model.cpp:5
    • Classes abstract implementation details from their interfaces: Detector.h, Detector.cpp, Model.h, Model.cpp
  • Memory Management
    • The project makes use of references in function declarations: Detector.h:11, Model.h:11

Dependencies for Running Locally

Basic Build Instructions

  1. Clone this repo.
  2. Make a build directory in the top level directory: mkdir build && cd build
  3. Compile: cmake .. && make
  4. Run it: ./hotdog_video_detector

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