Caffe implementation of Google MobileNet SSD detection network, with pretrained weights on VOC0712 and mAP=0.727.
翻译 - Google MobileNet SSD检测网络的Caffe实施，在VOC0712和mAP = 0.727上具有预训练的权重。
Caffe implementation of SSD and SSDLite detection on MobileNetv2, converted from tensorflow.
Accelerate mobileNet-ssd with tensorRT
Use TensorRT API to implement Caffe-SSD， SSD（channel pruning）， Mobilenet-SSD
[High Performance / MAX 30 FPS] RaspberryPi3(RaspberryPi/Raspbian Stretch) or Ubuntu + Multi Neural Compute Stick(NCS/NCS2) + RealSense D435(or USB Camera or PiCamera) + MobileNet-SSD(MobileNetSSD) + ...
A web app for MobileNet SSD detection
MobileNetV3-SSD for object detection and implementation in PyTorch
Caffe implementation of Mobilenet-SSD face detector (NCS compatible)
mobilenet ssd @ ncnn
Face detection with mobilenet-ssd written by tf.keras.
mobilenet-ssd snpe demo
MobileNets-SSD/SSDLite on VOC/BDD100K Datasets
Caffe implementation of Google VGG/MobileNet/ShuffleNet SSD detection network. Ref: (https://github.com/chuanqi305/MobileNet-SSD) (https://github.com/weiliu89/caffe) SSD QQ交流群：581437405
My own re-implementation of VGG-SSD and MobileNet-SSD based tensorflow 1.8.0
C++ Object Detection (SSD MobileNet) implementation using OpenCV.
An iOS application of Tensorflow Object Detection with different models: SSD with Mobilenet, SSD with InceptionV2, Faster-RCNN-resnet101
Clone from https://github.com/zeusees/Mobilenet-SSD-License-Plate-Detection
Edge TPU Accelerator / Multi-TPU + MobileNet-SSD v2 + Python + Async + LattePandaAlpha/RaspberryPi3/LaptopPC
A mobilenet SSD based face detector, powered by tensorflow object detection api, trained by WIDERFACE dataset.
Sample of Android Things with TensorFlow Lite (coco-ssd-mobilenet-v1 model).
Real-time object-detection using SSD on Mobilenet on iOS using CoreML, exported using tf-coreml
这是一个mobilenet-ssd-keras的源码，可以用于训练自己的轻量级ssd模型。
This repository contains the script and process to create custom SSD Mobilenet model for object detection
Edge TPU Accelerator / Multi-TPU / Multi-Model + Posenet/DeeplabV3/MobileNet-SSD + Python + Sync / Async + LaptopPC / RaspberryPi
