Models pertaining to the paper, Introducing SSBD+ Dataset with a Convolutional Pipeline for detecting Self-Stimulatory Behaviours in Children using raw videos
Project description
SSBD+
Code and material relevant to the paper, "Introducing SSBD+ Dataset with a Convolutional Pipeline for detecting Self-Stimulatory Behaviours in Children using raw videos"
All relevant links can be found here:
Installation and Usage: INSTALL.md
pip install --upgrade ssbdplus
Models and their descriptions: MODELS.md
from ssbdplus.pipeline import SSBDPipeline
model = SSBDPipeline()
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file ssbdplus-2.2.0.tar.gz.
File metadata
- Download URL: ssbdplus-2.2.0.tar.gz
- Upload date:
- Size: 5.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.9.2 readme-renderer/37.3 requests/2.28.1 requests-toolbelt/0.10.1 urllib3/1.26.14 tqdm/4.64.1 importlib-metadata/4.12.0 keyring/18.0.1 rfc3986/1.5.0 colorama/0.4.6 CPython/3.8.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9477bd1a5569e39d7fdf5a94d411f8e4cdb4fae9a8a4e5216a3cf8ac07ff0970
|
|
| MD5 |
928219632df0d22b2475943db1dd4adf
|
|
| BLAKE2b-256 |
cf913485896b4ab0234069182f2b9664a653afb7534ff72fe08bbbd86d7e4bed
|
File details
Details for the file ssbdplus-2.2.0-py3-none-any.whl.
File metadata
- Download URL: ssbdplus-2.2.0-py3-none-any.whl
- Upload date:
- Size: 6.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.9.2 readme-renderer/37.3 requests/2.28.1 requests-toolbelt/0.10.1 urllib3/1.26.14 tqdm/4.64.1 importlib-metadata/4.12.0 keyring/18.0.1 rfc3986/1.5.0 colorama/0.4.6 CPython/3.8.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1d31c5b1a945683a1959499348dd48e6f60d19a0820dea3a8621e2a3ee656f63
|
|
| MD5 |
1fc0adf1535d10752aa11793e9e3e44f
|
|
| BLAKE2b-256 |
1db05168be45be65a0f6fd054f7f7647da1ac0902f74f543cbf209b448b0613c
|