Tflite Python Packages

optimum

🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools

onnx2tf

A tool for converting ONNX files to LiteRT/TFLite/TensorFlow, PyTorch native code (nn.Module), TorchScript (.pt), state_dict (.pt), Exported Program (.pt2), and Dynamo ONNX. It also supports direct conversion from LiteRT to PyTorch.

tf2onnx

Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX

tflite

Parse TFLite models (*.tflite) EASILY with Python. Check the API at https://zhenhuaw.me/tflite/docs/

openvino2tensorflow

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.

tflite2onnx

Convert TensorFlow Lite models (*.tflite) to ONNX.

tflite2tensorflow

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.

tensorflowasr

:zap: TensorFlowASR: Almost State-of-the-art Automatic Speech Recognition in Tensorflow 2. Supported languages that can use characters or subwords

nobuco

Pytorch to Tensorflow conversion made intuitive

yolov4

YOLOv4 Implemented in Tensorflow 2.

onnxifier

Convert ANY IR to ONNX format

fovux-mcp

Local-first YOLO workbench for edge-AI computer vision: MCP server + VS Code Studio for dataset inspection, training, evaluation, export, and RTSP inference.

ultralytics-yolov5

No description available

tfhelper

Your friendly Tensorflow 2.x neighbor.

openvino2onnx

Convert ANY IR to ONNX format

yolov5-inference

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

swiss-army-keras

A library to help with the development of AI models with Keras, with a focus on edge / IoT applications. Based originally on https://github.com/yingkaisha/keras-unet-collection

tensorflowtts

:stuck_out_tongue_closed_eyes: TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2 (supported including English, French, Korean, Chinese, German and Easy to adapt for other languages)

dpdfnet

DPDFNet: causal single-channel speech enhancement that boosts DeepFilterNet2 with dual-path RNN blocks for stronger long-range temporal and cross-band modeling. Repo includes PyTorch implementation + checkpoints, ONNX & TFLite models with inference code, and a real-time demo.

wai-tfimageclass

Image classification using tensorflow.

tfliteiorewriter

This tool displays tflite signatures and rewrites the input/output OP name to the name of the signature. There is no need to install TensorFlow or TFLite.

fovea-mcp

Fovea — local-first, edge-AI computer-vision workbench. MCP server (Python) + VS Code extension covering the full YOLO lifecycle: dataset → train → eval → export → benchmark.

wai-tflite-model-maker

Various applications using tensorflow.

runlocal-hub

Python client for benchmarking and validating ML models on real devices via RunLocal API