Embedded Files
'Openpose', human pose estimation algorithm, have been implemented using Tensorflow. It also provides several variants that have some changes to the network structure for real-time processing on the CPU or low-power embedded devices.
You can even run this on your PC with a descent FPS!
MobileNets
MobileNets
- Based on the mobilenet paper, 12 convolutional layers are used as feature-extraction layers.
- To improve on small person, minor modification on the architecture have been made.
- Three models were learned according to network size parameters.
- mobilenet
- 368x368
- mobilenet_fast
- mobilenet_accurate
- mobilenet
MobileNets are small, low-latency, low-power models parameterized to meet the resource constraints of a variety of use cases. They can be built upon for classification, detection, embeddings and segmentation similar to how other popular large scale models, such as Inception, are used. MobileNets can be run efficiently on mobile devices with TensorFlow Mobile.
MobileNets trade off between latency, size and accuracy while comparing favorably with popular models from the literature.
Google Sites
Report abuse