| EdjeElectronics/TensorFlow-Object-Detection-on-the-Raspberry-Pi |
834 |
|
0 |
0 |
over 6 years ago |
0 |
|
48 |
apache-2.0 |
Python |
| A tutorial showing how to set up TensorFlow's Object Detection API on the Raspberry Pi |
| jinfagang/thor |
256 |
|
0 |
0 |
almost 4 years ago |
0 |
|
8 |
other |
C++ |
| thor: C++ helper library, for deep learning purpose |
| PINTO0309/MobileNet-SSDLite-RealSense-TF |
43 |
|
0 |
0 |
about 7 years ago |
0 |
|
2 |
mit |
Python |
| RaspberryPi3(Raspbian Stretch) + MobileNetv2-SSDLite(Tensorflow/MobileNetv2SSDLite) + RealSense D435 + Tensorflow1.11.0 + without Neural Compute Stick(NCS) |
| iwatake2222/play_with_mnn |
19 |
|
0 |
0 |
over 3 years ago |
0 |
|
0 |
apache-2.0 |
C++ |
| Sample projects to use MNN. PoseNet, SemanticSegmentation, etc. |
| HjyTiger/AutoPilot-Tool |
18 |
|
0 |
0 |
over 5 years ago |
0 |
|
2 |
apache-2.0 |
C++ |
| This is a tool for software engineers to view,record and analyse data(sensor data and module data) In the process of software development. |
| P-Chao/RVAF |
15 |
|
0 |
0 |
almost 8 years ago |
0 |
|
0 |
bsd-2-clause |
C++ |
| Robot Vision Algorithm Framework |
| mikeroberts3000/EfficientHierarchicalGraphBasedVideoSegmentationExporter |
11 |
|
0 |
0 |
over 10 years ago |
0 |
|
0 |
|
C++ |
| This repository contains C++ code to export the video segmentations from the system described in the paper Efficient Hierarchical Graph-Based Video Segmentation. The system described in this paper returns segmentations as Protocol Buffer files. The exporter contained in this repository converts these Protocol Buffer files into image sequences. |
| yangfly/face.ncnn |
10 |
|
0 |
0 |
about 7 years ago |
0 |
|
0 |
|
C++ |
| 基于 ncnn 框架搭建 win 及 android 端的人脸检测工程 |
| hqli/caffe_install |
7 |
|
0 |
0 |
almost 10 years ago |
0 |
|
0 |
|
Shell |
| caffe在Ubuntu14.04和CentOS6.7上的自动安装脚本。 |
| yash42828/Gender-and-Age-detection-using-OpenCV |
5 |
|
0 |
0 |
almost 6 years ago |
0 |
|
0 |
|
Python |
| Automatically predict age and gender in static image files and real-time video streams with reasonably high accuracy. |
