YOLOv5
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Updated
Apr 27, 2022 - Python
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YOLOv5
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
is:issue is:open 请问,方便提供一下onnx文件导出的代码文件吗?用model文件夹里面跟随的文件输出结果用ncnn推理结果不对
An awesome list of TensorFlow Lite models, samples, tutorials, tools and learning resources.
Android TensorFlow Lite Machine Learning Example
TFLite are now up to 2.6.1 (stable) and beyond in testing releases: https://github.com/tensorflow/tensorflow/releases
These may offer fixes for newer toolchains (GCC 11+, Clang 12+), in particular on more bleeding edge distros such as Manjaro.
Ticket here is to try these later versions of TFLite against newer toolchains, and ensure backscrub still actually works
See also: #93
虚拟爱抖露(アイドル)共享计划, 是基于单目RGB摄像头的人眼与人脸特征点检测算法, 在实时3D面部捕捉以及模型驱动领域的应用.
A Wide Range of Custom Functions for YOLOv4, YOLOv4-tiny, YOLOv3, and YOLOv3-tiny Implemented in TensorFlow, TFLite, and TensorRT.
Prebuilt binary with Tensorflow Lite enabled. For RaspberryPi / Jetson Nano. Support for custom operations in MediaPipe. XNNPACK, XNNPACK Multi-Threads, FlexDelegate.
GPU accelerated deep learning inference applications for RaspberryPi / JetsonNano / Linux PC using TensorflowLite GPUDelegate / TensorRT
Creating a software for automatic monitoring in online proctoring
Demo on adding virtual background to a live video stream in the browser
React Native library for TensorFlow Lite
Create a project that does not link in any of the TFLM library or models. It would provide a starting point for software for non-TFLM based experimentation with CFUs.
hair segmentation in mobile device
This script converts the ONNX/OpenVINO IR model to Tensorflow's saved_model, tflite, h5, tfjs, tftrt(TensorRT), CoreML, EdgeTPU, ONNX and pb. PyTorch (NCHW) -> ONNX (NCHW) -> OpenVINO (NCHW) -> openvino2tensorflow -> Tensorflow/Keras (NHWC/NCHW) -> TFLite (NHWC/NCHW). And the conversion from .pb to saved_model and from saved_model to .pb and from .pb to .tflite and saved_model to .tflite and saved_model to onnx. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support.
Multi-Person Pose Estimation project for Tensorflow 2.0 with a small and fast model based on MobilenetV3
Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support. Supports inverse quantization of INT8 quantization model.
Prebuilt binary for TensorFlowLite's standalone installer. For RaspberryPi. A very lightweight installer. I provide a FlexDelegate, MediaPipe Custom OP and XNNPACK enabled binary.
A Dart interface to TensorFlow Lite (tflite) through dart:ffi
TensorFlow Lite models for MIRNet for low-light image enhancement.
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how to use gui in the AidLearning?how to custom the gui?