Distinguish behavioral clusters Toolbox
Project description
CASTLE
CASTLE integrates the strengths of visual foundation models trained on large datasets possess open-world visual concepts, including Segment Anything (SA), DeAOT, and DINOv2, for one-shot image segmentation and unsupervised visual feature extraction. Furthermore, CASTLE employs unsupervised multi-stage and/or multi-layer UMAP clustering algorithms to distinguish behavioral clusters with unique temporal variability.
Install
pip install castle-ai
Reference
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
castle_ai-0.0.4.tar.gz
(94.0 kB
view details)
Built Distribution
castle_ai-0.0.4-py2.py3-none-any.whl
(126.1 kB
view details)
File details
Details for the file castle_ai-0.0.4.tar.gz.
File metadata
- Download URL: castle_ai-0.0.4.tar.gz
- Upload date:
- Size: 94.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | dca2a143c120a8bf9cbf2baec357256ae36e88cd0304455d37eb02ee435841e7 |
|
| MD5 | bab5ef7181206a8255ad1b4436600273 |
|
| BLAKE2b-256 | 43a0ebd33b4291a0e3d44dabe2779171733b078f69e26bb89c254f8261f73d59 |
File details
Details for the file castle_ai-0.0.4-py2.py3-none-any.whl.
File metadata
- Download URL: castle_ai-0.0.4-py2.py3-none-any.whl
- Upload date:
- Size: 126.1 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 6711648063cad59099e168c85d4a1ec6a84ebe72c82913084e51784350bcda5a |
|
| MD5 | 9be488b79570f9d24086c5f6b7269e21 |
|
| BLAKE2b-256 | eba6cd5e4afc9264ca6a18245c2c8be06645cf47950b7d0aefe070c024a0072b |
