learnopencv/Deep-Learning-with-OpenCV-DNN-Module

Deep Learning with OpenCV's DNN Module

This repsitory contains code for Deep Learning with OpenCV DNN Module: A Definitive Guide blogpost.

Directory Structure

All the code files and folders follow the following structure.

├── cpp
│   ├── classify
│   │   ├── classify.cpp
│   │   └── CMakeLists.txt
│   └── detection
│       ├── detect_img
│       │   ├── CMakeLists.txt
│       │   └── detect_img.cpp
│       └── detect_vid
│           ├── CMakeLists.txt
│           └── detect_vid.cpp
├── input
│   ├── classification_classes_ILSVRC2012.txt
│   ├── DenseNet_121.caffemodel
│   ├── DenseNet_121.prototxt
│   ├── frozen_inference_graph.pb
│   ├── image_1.jpg
│   ├── image_2.jpg
│   ├── object_detection_classes_coco.txt
│   ├── ssd_mobilenet_v2_coco_2018_03_29.pbtxt.txt
│   └── video_1.mp4
├── outputs
│   ├── image_result.jpg
│   ├── result_image.jpg
│   └── video_result.mp4
├── python
│   ├── classification
│   │   ├── classify.py
│   │   └── README.md
│   ├── detection
│   │   ├── detect_img.py
│   │   └── detect_vid.py
│   └── requirements.txt
└── README.md

Instructions

Python

To run the code in Python, please go into the python folder and execute the Python scripts in each of the respective sub-folders.

C++

To run the code in C++, please go into the cpp folder, then go into each of the respective sub-folders and follow the steps below:

mkdir build
cd build
cmake ..
cmake --build . --config Release
cd ..
./build/classify

mkdir build
cd build
cmake ..
cmake --build . --config Release
cd ..
./build/detect_img

mkdir build
cd build
cmake ..
cmake --build . --config Release
cd ..
./build/detect_vid

Outputs

Image Classification

• 

Object Detection

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