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Tags: Machine learning

1.ocrmypdf / OCRmyPDF

OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched

python
ocr
pdf
image-processing
tesseract

Python MPL-2.035K total2.4K forks

+332 stars

from 34,903 · score 5.81

2.coqui-ai / TTS

🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

python
text-to-speech
deep-learning
speech
pytorch
tts
+13 more

Python MPL-2.046K total6.2K forks

+147 stars

from 46,034 · score 5.00

3.Const-me / Whisper

High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model

C++MPL-2.011K total979 forks

+38 stars

from 10,665 · score 3.66

4.mkiol / dsnote

Speech Note Linux app. Note taking, reading and translating with offline Speech to Text, Text to Speech and Machine translation.

asr
sailfishos
stt
tts
flatpak-applications
linux-desktop
+9 more

C++MPL-2.01.7K total76 forks

+31 stars

from 1,678 · score 3.47

5.mozilla / TTS

:robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)

deep-learning
text-to-speech
python
pytorch
tacotron
tts
+10 more

Jupyter Notebook MPL-2.010K total1.3K forks

+15 stars

from 10,165 · score 2.77

6.mozilla / DeepSpeechArchived

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

deep-learning
machine-learning
neural-networks
tensorflow
speech-recognition
speech-to-text
+4 more

C++MPL-2.027K total4.1K forks

+8 stars

from 26,764 · score 2.20

7.wildmeshing / fTetWild

Fast Tetrahedral Meshing in the Wild

C++MPL-2.0614 total123 forks

+8 stars

from 606 · score 2.20

8.ZigRazor / CXXGraph

Header-Only C++ Library for Graph Representation and Algorithms

search-algorithm
dijkstra-algorithm
graph
graph-algorithms
graph-theory-algorithms
graph-analysis
+14 more

C++MPL-2.0738 total144 forks

+6 stars

from 732 · score 1.95

9.danforthcenter / plantcv

Plant phenotyping with image analysis

science
bioinformatics
image-analysis
plant-phenotyping
plantcv

Python MPL-2.0839 total300 forks

+5 stars

from 834 · score 1.79

10.wildmeshing / TriWild

TriWild: Robust Triangulation with Curve Constraints

traingulation
meshing
geometry-processing

C++MPL-2.0265 total30 forks

+1 stars

from 264 · score 0.69

Order: Attention Score

Most net stars gained in the window first. The score only puts this gain on a log scale, so the order is the order of the gain.

How the ranking works

Ranked by stars gained in the window. The score is the natural log of one plus that gain, so a repository's rank is exactly its star gain's rank.

score = log1p(net stars gained in the trailing T complete UTC days)

A repository is ranked only when its Star History covers every day of the window and its latest Observation is not missing.

The longest window is 180 days. Star History from the Repository Host goes back at most 180 days before the first daily record that AwesomeRepos made for the repository. A longer window needs more of these daily records first. A repository younger than the window does not rank in it.

The filters select from the same eligible repositories. A repository matches the topics when it has any of them. Total stars is the count now. Last push and creation on the Repository Host count back from the start of today (UTC). The counts beside the languages, licenses, and topics include all ranked repositories in the window. A Tag holds the repositories that have it. See Tags.

A new repository enters the index when it gains stars faster than the published admission threshold, whatever its size. A repository stays in the index after it enters. Thus an archived repository can still rank.

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