Quantized tflite models for ailia TFLite Runtime

Overview

ailia-models-tflite

Quantized tflite models for ailia TFLite Runtime

About ailia TFLite Runtime

ailia TF Lite Runtime is a TensorFlow Lite compatible inference engine. Written in C99, it supports inference in Non-OS and RTOS. It also supports high-speed inference using Intel MKL on a PC, and operates 29 times faster than the official TensorFlow Lite.

Install

Get the ailia TF Lite Runtime package from ax Inc. Run the following command.

cd ailia_tflite_runtime/python
python3 bootstrap.py
pip3 install .

Models

Face detection

Model Reference Exported From Netron
BlazeFace PINTO_model_zoo TensorFlow Netron

Face recognition

Model Reference Exported From Netron
Face Mesh PINTO_model_zoo TensorFlow Netron

Hand recognition

Model Reference Exported From Netron
Blaze Hand PINTO_model_zoo TensorFlow Netron

Image classification

Model Reference Exported From Netron
MobileNet MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Keras Netron
MobileNetV2 MobileNetV2: Inverted Residuals and Linear Bottlenecks Keras Netron
ResNet50 tf.keras.applications.resnet50.ResNet50 Keras Netron

Image segmentation

Model Reference Exported From Netron
DeepLabv3+ PINTO_model_zoo TensorFlow Netron

Object detection

Model Reference Exported From Netron
MobileNetV2-SSDLite PINTO_model_zoo TensorFlow Netron
YOLOv3 tiny tensorflow-yolov4-tflite TensorFlow Netron

Options

You can benchmark with the -b option. You can use the official TensorFlow Lite with the --tflite option.

Owner
ax Inc.
AI to the power of X
ax Inc.
Awesome Monocular 3D detection

Awesome Monocular 3D detection Paper list of 3D detetction, keep updating! Contents Paper List 2022 2021 2020 2019 2018 2017 2016 KITTI Results Paper

Zhikang Zou 184 Jan 04, 2023
Neural Koopman Lyapunov Control

Neural-Koopman-Lyapunov-Control Code for our paper: Neural Koopman Lyapunov Control Requirements dReal4: v4.19.02.1 PyTorch: 1.2.0 The learning framew

Vrushabh Zinage 6 Dec 24, 2022
Official implementation of the NeurIPS'21 paper 'Conditional Generation Using Polynomial Expansions'.

Conditional Generation Using Polynomial Expansions Official implementation of the conditional image generation experiments as described on the NeurIPS

Grigoris 4 Aug 07, 2022
Deep learning operations reinvented (for pytorch, tensorflow, jax and others)

This video in better quality. einops Flexible and powerful tensor operations for readable and reliable code. Supports numpy, pytorch, tensorflow, and

Alex Rogozhnikov 6.2k Jan 01, 2023
Distilled coarse part of LoFTR adapted for compatibility with TensorRT and embedded divices

Coarse LoFTR TRT Google Colab demo notebook This project provides a deep learning model for the Local Feature Matching for two images that can be used

Kirill 46 Dec 24, 2022
These are the materials for the paper "Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations"

Few-shot-NLEs These are the materials for the paper "Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations". You can find the smal

Yordan Yordanov 0 Oct 21, 2022
Reviving Iterative Training with Mask Guidance for Interactive Segmentation

This repository provides the source code for training and testing state-of-the-art click-based interactive segmentation models with the official PyTorch implementation

Visual Understanding Lab @ Samsung AI Center Moscow 406 Jan 01, 2023
TensorFlow implementation of "Variational Inference with Normalizing Flows"

[TensorFlow 2] Variational Inference with Normalizing Flows TensorFlow implementation of "Variational Inference with Normalizing Flows" [1] Concept Co

YeongHyeon Park 7 Jun 08, 2022
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks

Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks This repository contains the code and data for the corresp

Friederike Metz 7 Apr 23, 2022
Official implementation for Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020

Likelihood-Regret Official implementation of Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020. T

Xavier 33 Oct 12, 2022
Hands-On Machine Learning for Algorithmic Trading, published by Packt

Hands-On Machine Learning for Algorithmic Trading Hands-On Machine Learning for Algorithmic Trading, published by Packt This is the code repository fo

Packt 981 Dec 29, 2022
Official implementation of Protected Attribute Suppression System, ICCV 2021

Official implementation of Protected Attribute Suppression System, ICCV 2021

Prithviraj Dhar 6 Jan 01, 2023
QuanTaichi evaluation suite

QuanTaichi: A Compiler for Quantized Simulations (SIGGRAPH 2021) Yuanming Hu, Jiafeng Liu, Xuanda Yang, Mingkuan Xu, Ye Kuang, Weiwei Xu, Qiang Dai, W

Taichi Developers 120 Jan 04, 2023
A convolutional recurrent neural network for classifying A/B phases in EEG signals recorded for sleep analysis.

CAP-Classification-CRNN A deep learning model based on Inception modules paired with gated recurrent units (GRU) for the classification of CAP phases

Apurva R. Umredkar 2 Nov 25, 2022
[CVPR'21 Oral] Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning

Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning [CVPR'21, Oral] By Zhicheng Huang*, Zhaoyang Zeng*, Yupan H

Multimedia Research 196 Dec 13, 2022
The Official Implementation of the ICCV-2021 Paper: Semantically Coherent Out-of-Distribution Detection.

SCOOD-UDG (ICCV 2021) This repository is the official implementation of the paper: Semantically Coherent Out-of-Distribution Detection Jingkang Yang,

Jake YANG 62 Nov 21, 2022
BERT model training impelmentation using 1024 A100 GPUs for MLPerf Training v1.1

Pre-trained checkpoint and bert config json file Location of checkpoint and bert config json file This MLCommons members Google Drive location contain

SAIT (Samsung Advanced Institute of Technology) 12 Apr 27, 2022
TensorFlow implementation of the paper "Hierarchical Attention Networks for Document Classification"

Hierarchical Attention Networks for Document Classification This is an implementation of the paper Hierarchical Attention Networks for Document Classi

Quoc-Tuan Truong 83 Dec 05, 2022
[2021 MultiMedia] CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval

CONQUER: Contexutal Query-aware Ranking for Video Corpus Moment Retreival PyTorch implementation of CONQUER: Contexutal Query-aware Ranking for Video

Hou zhijian 23 Dec 26, 2022
[ICCV 2021] Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation

ADDS-DepthNet This is the official implementation of the paper Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation I

LIU_LINA 52 Nov 24, 2022