IOPaint
tortoise-tts
IOPaint | tortoise-tts | |
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48 | 145 | |
17,288 | 11,881 | |
- | - | |
9.4 | 8.0 | |
6 days ago | 10 days ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | Apache License 2.0 |
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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.
IOPaint
- IOPaint: Image inpainting tool powered by SOTA. Erase and replace objects/people
- FLaNK Stack Weekly 12 February 2024
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ADetailer signature model
„Inpaint anything“ and „cleaner“ extension can remove text or anything you mark, if you are on A1111 webui, you can install them from extension tab. Standalone , there is lama cleaner , https://github.com/Sanster/lama-cleaner
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OptiClean: A native macOS inpainting app that helps you quickly clean up your images in seconds
This is an app developed from my other open source side project Lama Cleaner.
- Show HN: Open-source background removal in the browser
- ITAP of a bull and a bee
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Few questions about LoRA (face training)
When you're training, the model learns things you don't prompt for, like the face you want, but it also learns things that don't change much, even if prompted. So if there is a necklace there, it'll learn that something goes in the neck area. You might look into Lama Cleaner to remove the necklaces without messing anything else up.
- Câți dintre voi deja folosiți A.I? Si pentru ce?
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Image watermark remover?
I prefer Lamar Cleaner: https://github.com/Sanster/lama-cleaner to anything built into A1111.
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UnpromptedControl: Noprompt ControlNet Image Restoration/Object removal, GitHub link in comments
I use Lama Cleaner for stuff like this. Works great and supports all the SD models + Segment Anything, etc etc etc : https://github.com/Sanster/lama-cleaner
tortoise-tts
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ESpeak-ng: speech synthesizer with more than one hundred languages and accents
The quality also depends on the type of model. I'm not really sure what ESpeak-ng actually uses? The classical TTS approaches often use some statistical model (e.g. HMM) + some vocoder. You can get to intelligible speech pretty easily but the quality is bad (w.r.t. how natural it sounds).
There are better open source TTS models. E.g. check https://github.com/neonbjb/tortoise-tts or https://github.com/NVIDIA/tacotron2. Or here for more: https://www.reddit.com/r/MachineLearning/comments/12kjof5/d_...
- FLaNK Stack Weekly 12 February 2024
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OpenVoice: Versatile Instant Voice Cloning
I use Tortoise TTS. It's slow, a little clunky, and sometimes the output gets downright weird. But it's the best quality-oriented TTS I've found that I can run locally.
https://github.com/neonbjb/tortoise-tts
- [discussion] text to voice generation for textbooks
- DALL-E 3: Improving image generation with better captions [pdf]
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Open Source Libraries
neonbjb/tortoise-tts
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Running Tortoise-TTS - IndexError: List out of range
EDIT: It appears to be the exact same issue as this
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My Deep Learning Rig
It was primarily being used to train TTS models (see https://github.com/neonbjb/tortoise-tts), which largely fit into a single GPUs memory. So, for data parallelism, x8 PCIe isn't that much of a concern.
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PlayHT2.0: State-of-the-Art Generative Voice AI Model for Conversational Speech
Previously TortoiseTTS was associated with PlayHT in some way, although the exact connection is a bit vague [0].
From the descriptions here it sounds a lot like AudioLM / SPEAR TTS / some of Meta's recent multilingual TTS approaches, although those models are not open source, sounds like PlayHT's approach is in a similar spirit. The discussion of "mel tokens" is closer to what I would call the classic TTS pipeline in many ways... PlayHT has generally been kind of closed about what they used, would be interesting to know more.
I assume the key factor here is high quality, emotive audio with good data cleaning processes. Probably not even a lot of data, at least in the scale of "a lot" in speech, e.g. ASR (millions of hours) or TTS (hundreds to thousands). As opposed to some radically new architectural piece never before seen in the literature, there are lots of really nice tools for emotive and expressive TTS buried in recent years of publications.
Tacotron 2 is perfectly capable of this type of stuff as well, as shown by Dessa [1] a few years ago (this writeup is a nice intro to TTS concepts). With the limit largely being, at some point you haven't heard certain phonetic sounds before in a voice, and need to do something to get plausible outcomes for new voices.
[0] Discussion here https://github.com/neonbjb/tortoise-tts/issues/182#issuecomm...
[1] https://medium.com/dessa-news/realtalk-how-it-works-94c1afda...
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Comparing Tortoise and Bark for Voice Synthesis
Tortoise GitHub repo - Source code, documentation, and usage guide
What are some alternatives?
lama - 🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
stable-diffusion-ui - Easiest 1-click way to install and use Stable Diffusion on your computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image. [Moved to: https://github.com/easydiffusion/easydiffusion]
bark - 🔊 Text-Prompted Generative Audio Model
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
cleanup.pictures - Code for https://cleanup.pictures
piper - A fast, local neural text to speech system
OnnxDiffusersUI - UI for ONNX based diffusers
tacotron2 - Tacotron 2 - PyTorch implementation with faster-than-realtime inference
auto-sd-paint-ext - Extension for AUTOMATIC1111 to add custom backend API for Krita Plugin & more
larynx - End to end text to speech system using gruut and onnx