README / README.md
Subh775's picture
Update README.md
2449ae8 verified
---
title: README
emoji: ๐ŸŒฟ
colorFrom: green
colorTo: blue
sdk: static
pinned: false
license: apache-2.0
short_description: An Open-Source Initiative for AI in Agriculture
---
## ๐ŸŒฟ AgriVision
The **AgriVision** is a dedicated group for Research in Agriculture, We utilizes `Computer Vision` and `Deep Learning` for solving problems in agricultural field, such as leaf annotation, labelling, detection, segmentation, classification, etc.
We provide resources and tools for researchers to explore and apply **Computer Vision** and **Image processing techniques** for advancing plant science.
The primary challenge in agricultural tasks is - `In-The-Wild` problems, where even a highly accurate model fail, due to unstructured environment, illumination, noise, occlusion, etc.
**AgriVision** focuses on making Vision based services to handle In-The-Wild barriers.
## Common classical problems we handle
- **Segmentation Masks** โ€“ Mask Overlay, or polygon figures localizing an object/instance perfectly.
- **Annotations** โ€“ Add and manage precise annotation/bounding box
- **Image Processing** โ€“ Perform preprocessing tasks such as cropping, resizing, and filtering
- **Plant-Type Labeling** โ€“ Classify and organize images by species (e.g., basil, tomato, etc.)
> We utilizes pretrained models, tools like CVAT, and platforms like Roboflow for ease in solving problems.
## Mission
To empower the plant pathology community with accessible, reliable, and standardized **image processing techniques**, enabling faster research, improved dataset quality, and better insights into plant health.
## Vision
A collaborative platform that bridges the gap between **plant health** and **computer vision**, fostering innovation in agriculture, sustainability, and plant sciences.
## Get Involved & Collaborate
We are an open group and welcome collaboration from anyone passionate about AI in agriculture.
* **Contribute to Datasets:** Help us annotate and expand our public datasets.
* **Develop Models:** Share your notebooks and train new models on our data.
* **Provide Feedback:** Use our models and tools, and provide feedback to help us improve.
Feel free to open an issue in our project repositories or start a discussion to share your ideas!
---
## Citing Our Work
If you use any of our datasets, models, or code in your research, please consider citing us:
```bibtex
@misc{agrivision_2025,
author = {AgriVision Community},
title = {AgriVision: An Open-Source Initiative for AI in Agriculture},
year = {2025},
publisher = {Hugging Face},
journal = {Hugging Face repository}
}
```