Skip to main content

A SAM model with GroundingDINO model

Project description

DiagAssistAI

GitHub License Static Badge PyPI - Version

modelo

Installation

GSamNetwork requires python==3.10.12, as well as torch==2.4.0.

Installing PyTorch

Make sure to check the version of Python that is compatible with your CUDA version at the following link: Installing torch locally.

In this project, CUDA 12.1 was used. You can install PyTorch with support for CUDA 12.1 using the following command:

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121

Installing Package

To install the package, use:

pip install groundino-samnet

Version 0.2.1

Added

Added: Detailed function descriptions

Added: Metrics in DataFrames from pandas

Added: Parameter to enable post-processing for GroundingDINO prediction.

Deteled

Deleted: box_xyxy_to_xywh function for utils

Notice

Notice: Notice Regarding the Use of the cleanup() Function for Datasets

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

groundino_samnet-0.2.1.tar.gz (177.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

groundino_samnet-0.2.1-cp310-cp310-win_amd64.whl (494.5 kB view details)

Uploaded CPython 3.10Windows x86-64

File details

Details for the file groundino_samnet-0.2.1.tar.gz.

File metadata

  • Download URL: groundino_samnet-0.2.1.tar.gz
  • Upload date:
  • Size: 177.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.12

File hashes

Hashes for groundino_samnet-0.2.1.tar.gz
Algorithm Hash digest
SHA256 a7edbdda8402010b1043984687306c7c21a86ba77639490d6abe439873daf674
MD5 a56b6a5ca9e3d065f7839c84650566fd
BLAKE2b-256 dd70e1d92e0f97abc2ff9f3eff4025e49f736b3c8d05ada93810ffa562cd5d33

See more details on using hashes here.

File details

Details for the file groundino_samnet-0.2.1-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for groundino_samnet-0.2.1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 ea3806d9adb0d5b3625d17f63528688ea1ab7e6f69828f4486917142aa43dd7f
MD5 eaee9b9d59e71fd5f6ff401b843fe18a
BLAKE2b-256 22188608902b3a35862e6e6fc0f81d2a6fe05c189e53316ae28bcdf3621ffb72

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page