SegMate package
Project description
This repository is a toolkit for using the Segment Anything Model (SAM) developed by Meta AI. It is capable of accurately “cutting out” any object from an image with just a single click.
SAM is a promptable segmentation system that exhibits zero-shot generalization to unfamiliar objects and images, eliminating the need for additional training. By providing prompts that specify what needs to be segmented in an image, SAM can perform a wide range of segmentation tasks without requiring additional training.
Features
Easy inference with SAM, supporting bounding boxes, points, masks, and text prompts
Automatic mask generation
Finetune SAM on custom datasets
GroundingDINO integration for text prompt segmentation
Training a custom decoder to auto segment a specific type of object
Training a prompt embedding to auto segment a specific type of object
Installation
First, install groundingdino from its repository, this is a dependency for segmate:
NOTE: There is an issue with the setup script in the GroundingDINO repository causing it not able to install torch properly, please manually install PyTorch for now. For other issues, refer to the installation guide:
pip install -U git+https://github.com/IDEA-Research/GroundingDINO.git
Then, install segmate from PyPI:
pip install segmate
Example Usage
To use the provided code snippets, follow the steps below:
Import the required modules and initialize the necessary objects:
import torch
from segmate.segmenter import SAM
from segmate.object_detector import GroundingDINO
import segmate.utils as utils
# Model checkpoint path for GroundingDINO is optional. If no path provided, it will download from HuggingFace
od = GroundingDINO(device='cuda', ckpt_path='PATH_TO_CHECKPOINT')
sm = SAM(model_type='MODEL_TYPE', checkpoint='PATH_to_CHECKPOINT', device='cuda')
Perform segmentation with bounding box prompts:
masks = sm.segment(image=input_image, boxes_prompt=bbox)
utils.show_masks(image, masks)
Documentation
Detailed package documentation: SegMate Docs
If you have any questions or need assistance, please don’t hesitate to reach out to our support team or join our community forum. We hope you find this toolkit valuable and look forward to seeing the incredible applications you create with SAM!
License
The code in this repository is published under 3-Clause BSD license (see LICENSE file).
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
File details
Details for the file segmate-0.3.1.tar.gz
.
File metadata
- Download URL: segmate-0.3.1.tar.gz
- Upload date:
- Size: 24.3 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0cc66ea5a06454b826251c498e4d256ef3f3b34610f5a13c7fc4ebf2910e84fd |
|
MD5 | 2c006257ebf56e1ca7158ce6102dbf79 |
|
BLAKE2b-256 | bf4509eead9cfa24931a2a6ef80a9514675748238e7a5411b24ac79a644bbf66 |
File details
Details for the file segmate-0.3.1-py3-none-any.whl
.
File metadata
- Download URL: segmate-0.3.1-py3-none-any.whl
- Upload date:
- Size: 13.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 68f83c4fa30f805741dec0fe0dd1abba0e4b42498bfe1447889fd709b9c90050 |
|
MD5 | ff3ff4f4b37d4247600872847e06a942 |
|
BLAKE2b-256 | 83081e6a5ceb78d5d3ed35c93c253f81f05950199c5e30e3cfc7d703af0e0d1a |