Skip to content

IDLabs-Gate/enVision

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

26 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

enVision

Deep Learning Models for Vision Tasks on iOS

sample

Usage

Download dependencies folder tf

Extract all archives in tf/models and tf/lib

Put tf folder in same directory level as enVision project folder

Build and Run

Press screen to change running model

Tap a data slot below to select, then tap a detection box to snap

Tap a data slot with two fingers to remove last snap

Press a data slot to clear

Models

YOLO:

https://arxiv.org/abs/1506.02640

sample2

YOLO 1 tiny (VOC): Best performance on basic classes

YOLO 1 small (VOC): Better accuracy for basic classes

YOLO 1.1 tiny (COCO): Fast on extended classes

YOLO 2 (COCO): Best accuracy on extended classes

YOLO detector + Jetpac feature extractor from snaps + kNN classifier with Euclidean distance

.

FaceNet:

https://arxiv.org/abs/1503.03832

sample3

Inception-Resnet-v1 (FaceScrub and CASIA-Webface)

Native iOS face detector + FaceNet feature extractor from snaps + kNN classifier with Euclidean distance

.

Inception:

https://arxiv.org/abs/1512.00567

Inception v3 (ImageNet)

Can run retrained models instead

.

Jetpac:

https://github.com/jetpacapp/DeepBeliefSDK

Jetpac network (ImageNet)

DeepBeliefSDK framework

.

License

MIT License

Owner: ID Labs L.L.C.

Original Contributor: Muhammad Hilal