Project Vi
Project description
"Hey Vi!"
HEYVI: Visym Analytics for Visual AI
docs: https://developer.visym.com/heyvi
HEYVI is a python package for visual AI that provides systems and trained models for activity detection and object tracking in videos.
HEYVI provides:
- Real time activity detection of the MEVA activity classes
- Real time visual object tracking in long duration videos
- Live streaming of annotated videos to youtube live
- Visual AI from RTSP cameras
Requirements
python 3.*
ffmpeg (required for videos)
vipy, torch, pytorch_lightning (for training)
Installation
pip install heyvi
Quickstart
v = heyvi.sensor.rtsp().framerate(5)
T = heyvi.system.Tracker()
with heyvi.system.YoutubeLive(fps=5, encoder='480p') as s:
T(v, frame_callback=lambda im: s(im.pixelize().annotate()))
Create a default RTSP camera and GPU enabled object tracker, then stream the privacy preserving annotated video (e.g. pixelated bounding boxes with captions) to a YouTube live stream.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
heyvi-0.2.23.tar.gz
(459.8 kB
view details)
Built Distribution
heyvi-0.2.23-py3-none-any.whl
(159.8 kB
view details)
File details
Details for the file heyvi-0.2.23.tar.gz
.
File metadata
- Download URL: heyvi-0.2.23.tar.gz
- Upload date:
- Size: 459.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.55.2 CPython/3.6.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2cb082d9db1374110a37dcdd2bc2e82475426109b2f8aaec57c5f945782920f9 |
|
MD5 | 47469c04bb6548cd8519fc757b5cba32 |
|
BLAKE2b-256 | 4adb7635281ee811a98c2dca39e1e440969d374afe422365bd5c887d2b2317a6 |
File details
Details for the file heyvi-0.2.23-py3-none-any.whl
.
File metadata
- Download URL: heyvi-0.2.23-py3-none-any.whl
- Upload date:
- Size: 159.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.55.2 CPython/3.6.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5d6ea0cdb1936bb4fbea33baa29b0674cf72a999672f3d8855bb0f74f5125649 |
|
MD5 | 267b365d1b734386a8cba56b8566f078 |
|
BLAKE2b-256 | f2bc35f3ba3d2fe43420dfc95b6890f3fe1f5afd645e220029daa69ad9ab60e3 |