TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @githubtrending · Post #15023 · Aug 2

#dart#android#flutter#flutter_apps#manager#modding#patching#revanced ReVanced Manager is an app for Android that lets you customize and patch other apps, like YouTube, to remove ads and add features without needing subscriptions. It is easy to use, works on both rooted and non-rooted devices, and offers many options to tailor apps to your liking. You download the official app, then apply patches you want, creating a personalized, ad-free experience. This saves you money and improves app use while staying legal and supported by an active community. It is lightweight, regularly updated, and has a simple interface, making app customization safe and convenient[1][3][5]. https://github.com/ReVanced/revanced-manager

Results

3 similar posts found

Search: #sounds

当前筛选 #sounds清除筛选
Interesting Planet 🌍

@interesting_planet_facts · Post #1053 · 11/19/2025, 06:11 PM

🌎 In 1977, the Soviet Venera 14 probe recorded mysterious low-frequency “thunder”-like sounds on Venus. Scientists now attribute these to seismic activity or wind interacting with the planet’s dense atmosphere. Venus’s surface winds move slowly, but thick air carries sound much farther than on Earth. ✨ #Venus⚡#sounds⚡#space 👉subscribe Interesting Planet 👉more Channels ​

djangoproject

@djangoproject · Post #255 · 02/02/2017, 06:57 PM

https://github.com/tyiannak/pyAudioAnalysis #pyAudioAnalysis is a Python library covering a wide range of audio analysis tasks. Through pyAudioAnalysis you can: Extract #audio features and representations (e.g. mfccs, spectrogram, chromagram) Classify unknown #sounds Train, parameter tune and evaluate classifiers of audio segments Detect audio events and exclude silence periods from long recordings Perform supervised segmentation (joint segmentation - classification) Perform unsupervised segmentation (e.g. speaker diarization) Extract audio thumbnails Train and use audio regression models (example application: emotion recognition) Apply dimensionality reduction to visualize audio data and content similarities