https://github.com/qengineering/mobilenetv1_ssd_opencv_caffe
MobileNetV1_SSD Caffe with OpenCV on RaspBerry Pi
https://github.com/qengineering/mobilenetv1_ssd_opencv_caffe
caffe cpp dnn mobilenet-ssd mobilenetv1-ssd-caffe opencv raspberry-pi testopencv-caffe
Last synced: 6 months ago
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MobileNetV1_SSD Caffe with OpenCV on RaspBerry Pi
- Host: GitHub
- URL: https://github.com/qengineering/mobilenetv1_ssd_opencv_caffe
- Owner: Qengineering
- License: bsd-3-clause
- Created: 2020-01-16T13:13:18.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2021-12-27T09:57:06.000Z (almost 4 years ago)
- Last Synced: 2025-03-27T09:23:25.810Z (7 months ago)
- Topics: caffe, cpp, dnn, mobilenet-ssd, mobilenetv1-ssd-caffe, opencv, raspberry-pi, testopencv-caffe
- Language: C++
- Homepage: https://qengineering.eu/deep-learning-software-for-raspberry-pi-and-alternatives.html
- Size: 20.1 MB
- Stars: 5
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# MobileNetV1_SSD for the Deep Learning module of OpenCV
## A example of OpenCV dnn framework working on a bare Raspberry Pi with Caffe models.
[](https://opensource.org/licenses/BSD-3-Clause)
Paper: https://arxiv.org/pdf/1612.08242.pdf
Special made for a bare Raspberry Pi 4 see [Q-engineering deep learning examples](https://qengineering.eu/deep-learning-examples-on-raspberry-32-64-os.html)
------------
Training set: VOC2007
Size: 300x300
Frame rate: 3.66 FPS (RPi 4)
------------
## Dependencies.
To run the application, you have to:
- A raspberry Pi 4 with a 32 or 64-bit operating system. It can be the Raspberry 64-bit OS, or Ubuntu 18.04 / 20.04. [Install 64-bit OS](https://qengineering.eu/install-raspberry-64-os.html)
- OpenCV 64 bit installed. [Install OpenCV 4.5](https://qengineering.eu/install-opencv-4.5-on-raspberry-64-os.html)
- Code::Blocks installed. (```$ sudo apt-get install codeblocks```)
------------
## Installing the app.
To extract and run the network in Code::Blocks
$ mkdir *MyDir*
$ cd *MyDir*
$ wget https://github.com/Qengineering/MobileNetV1_SSD_OpenCV_Caffe/archive/refs/heads/master.zip
$ unzip -j master.zip
Remove master.zip and README.md as they are no longer needed.
$ rm master.zip
$ rm README.md
Your *MyDir* folder must now look like this:
04545.jpg
MobileNetSSD_deploy.caffemodel
MobileNetSSD_deploy.prototxt
TestOpenCV_Caffe.cpb
MobileNet.cpp
------------
## Running the app.
To run the application load the project file TestOpenCV_Caffe.cbp in Code::Blocks. More info or
if you want to connect a camera to the app, follow the instructions at [Hands-On](https://qengineering.eu/deep-learning-examples-on-raspberry-32-64-os.html#HandsOn).
------------
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