Popular GitHub Repositories for Imazing Converter

Easily train a good VC model with voice data <= 10 mins!

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.

An easy to use PyTorch to TensorRT converter

OpenMMLab Model Deployment Framework

将EPUB、PDF和文本文件转换成带同步字幕的有声书。

This is a tool that uses a multimodal LLM to transcribe PDF files into Markdown format. 借助多模态大模型将PDF文件转为Markdown

Open-source platform for extracting structured data from documents using AI.

Self-Created Tools to convert ONNX files (NCHW) to TensorFlow/TFLite/Keras format (NHWC). The purpose of this tool is to solve the massive Transpose extrapolation problem in onnx-tensorflow (onnx-tf). I don't need a Star, but give me a pull request.

Deep learning model converter for PaddlePaddle. (『飞桨』深度学习模型转换工具)

JamTools是一个跨平台的小工具集类软件，支持Windows7/8/10/11、Macos、ubuntu系统(其他系统可以直接从源码编译打包)。包含了(滚动/区域)截屏、录屏、文字识别、多种语言互译、多媒体格式转换、鼠标键盘动作录制播放、局域网文件传输、聊天机器人等功能，完全开源!

Export Hugging Face models to Core ML and TensorFlow Lite

Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

Voice Converter Using CycleGAN and Non-Parallel Data

A multithreaded ?? web crawler that recursively crawls a website and creates a ? markdown file for each page, designed for LLM RAG

Chinese Mandarin Grapheme-to-Phoneme Converter. 中文轉注音或拼音 (INTERSPEECH 2022)

TensorFlow JS models for MIRNet for low-light? image enhancement

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.

Pytorch to Keras/Tensorflow/TFLite conversion made intuitive

A set of simple tools for splitting, merging, OP deletion, size compression, rewriting attributes and constants, OP generation, change opset, change to the specified input order, addition of OP, RGB to BGR conversion, change batch size, batch rename of OP, and JSON convertion for ONNX models.