RobustVideoMatting
coremltools
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RobustVideoMatting | coremltools | |
---|---|---|
16 | 11 | |
8,157 | 4,049 | |
- | 2.5% | |
0.0 | 8.7 | |
22 days ago | 5 days ago | |
Python | Python | |
GNU General Public License v3.0 only | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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
- lineart_coarse + openpose, batch img2img
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Tools For AI Animation and Filmmaking , Community Rules, ect. (**FAQ**)
Robust Video Matting/Background Remover (Remove Background from images and videos, useful for compositing) https://github.com/PeterL1n/RobustVideoMatting (RVM - Remove backgrounds from videos) https://github.com/nadermx/backgroundremover (BackgroundRemover - works well on single images) -------VOICE GENERATION--------
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Adobe After Effects VS Runway AI đź‘€
Looks like runway is packaging a bunch of AI tools like stable diffusion and other opensource tools into a paid package. The matting tools it is using looks like this tool https://github.com/PeterL1n/RobustVideoMatting which can be run off your computer for free if you can figure out the geeky side of installing this stuff. I've tried it out and it sometimes works well but most of the time the results aren't as good as the examples on their github. Still a good tool to have in the toolbox though.
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Rotoscoping a video by comparing images
OR this separate application looks promising, if you can work out Google Collab (I couldn't unfortunately): https://github.com/PeterL1n/BackgroundMattingV2 https://github.com/PeterL1n/RobustVideoMatting
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CatFileCreator in Nuke
I have done a bit of coding and I will use pretrained models only. Looking at things like depth and segmentation. Like this as an example. I am using it on a collab now but its so cumbersome. https://github.com/PeterL1n/RobustVideoMatting
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[Q] Video Editing using AI
I do not know much about Machine learning, and I am not sure if I can ask question here. But if yes, I need help with either choosing best libraries to do Video Editing like Background Removal and similar. Some of the ones that I found is RVM: https://github.com/PeterL1n/RobustVideoMatting (which currently seems like the best choice)
- Is this FOSS ML software safe?
- [D] Is this ML project safe?
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Trying to train videomatting model
First of all I would ask if somebody retrained Robust Video Matting model on own data? I am trying to, but with all the models I end up getting bad quality result as the ones attached to the post. So my data is some objects rotating on 360 and with white backgrounds, The task seems to be pretty simple as the model just has to remove white bgr and keep colorized object. I have masks on every 10th frame of my videos. The masks are 0 - bgr, 255 - fgr. I have tried Robust Video Matting model, MODNet, PaddleSeg and several segmentation models and every of them failed to show consistent results on that data. What should I do in the case?
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Remove Background NO GREENSCREEN?
I have found a github with a project like this but it is tedious to use: https://github.com/PeterL1n/RobustVideoMatting
coremltools
- CoreML commit from Apple mentions iOS17 exclusive features
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Lisa Su Saved AMD. Now She Wants Nvidia's AI Crown
Instead of trying to integrate the whole stack of, say, pytorch, Apple's primary approach has been converting models to work with Apple's stack.
https://github.com/apple/coremltools
Clearly no one is going to be doing training or even fine tuning on Apple hardware at any scale (it competes at the low end, but at scale you invariably will be using nvidia hardware), but once you have a decent model it's a robust way of using it on Apple devices.
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Stable Diffusion for M1 iPad
There is one guy who was able to run it on iOS. See this thread for more information. Basically, the idea is to convert torch models to CoreMl. Only the CLIP tokenizer's implementation is currently missing. I guess this guy will keep modifications private, but he is trying to optimize model for lower RAM requirements.
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MacBook Pro 14” M1 Pro (worth buying for programming)
Afaik (correct me if I’m wrong) both PyTorch and tensorflow only use the gpu when training and not the neural engine. I think the neural engines can be used for inference if the model is in the CoreML format (https://github.com/apple/coremltools)
- Is it possible to convert a yolov5 model to a CoreML/.mlmodel to work in an IOS app?
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ML model conversion
CoreML Tools
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Supreme Court, in a 6–2 ruling in Google v. Oracle, concludes that Google’s use of Java API was a fair use of that material
And Python.
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Apple’s New M1 Chip is a Machine Learning Beast
There's literally an Apple provided tool, called [coremltools[(https://github.com/apple/coremltools) to convert many common PyTorch and TensorFlow models to CoreML.
What are some alternatives?
MODNet - A Trimap-Free Portrait Matting Solution in Real Time [AAAI 2022]
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
BackgroundMattingV2 - Real-Time High-Resolution Background Matting
tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
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.
3d-model-convert-to-gltf - Convert 3d model (STL/IGES/STEP/OBJ/FBX) to gltf and compression
pytorch-deep-image-matting - Pytorch implementation of deep image matting
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.
keras-onnx - Convert tf.keras/Keras models to ONNX
password-manager-resources - A place for creators and users of password managers to collaborate on resources to make password management better.
caer - High-performance Vision library in Python. Scale your research, not boilerplate.
hummingbird - Hummingbird compiles trained ML models into tensor computation for faster inference.