RobustVideoMatting VS keras-onnx

Compare RobustVideoMatting vs keras-onnx and see what are their differences.

RobustVideoMatting

Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML! (by PeterL1n)

keras-onnx

Convert tf.keras/Keras models to ONNX (by onnx)
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RobustVideoMatting keras-onnx
16 2
8,087 329
- -
1.0 4.4
5 months ago over 2 years ago
Python Python
GNU General Public License v3.0 only Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

RobustVideoMatting

Posts with mentions or reviews of RobustVideoMatting. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-10.

keras-onnx

Posts with mentions or reviews of keras-onnx. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-30.

What are some alternatives?

When comparing RobustVideoMatting and keras-onnx you can also consider the following projects:

MODNet - A Trimap-Free Portrait Matting Solution in Real Time [AAAI 2022]

BackgroundMattingV2 - Real-Time High-Resolution Background Matting

PINTO_model_zoo - 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.

pytorch-deep-image-matting - Pytorch implementation of deep image matting

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

onnx-tensorrt - ONNX-TensorRT: TensorRT backend for ONNX

caer - High-performance Vision library in Python. Scale your research, not boilerplate.

MMdnn - 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.

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.

Autonomous-Ai-drone-scripts - State of the art autonomous navigation scripts using Ai, Computer Vision, Lidar and GPS to control an arducopter based quad copter.

pytorch2keras - PyTorch to Keras model convertor

DI-star - An artificial intelligence platform for the StarCraft II with large-scale distributed training and grand-master agents.