File size: 2,352 Bytes
a835b5e 5edee0a 8ab12ce a835b5e 5edee0a a835b5e 5edee0a 8ab12ce b652cdd 5edee0a 8ab12ce 5edee0a 8ab12ce b652cdd 8ab12ce 5edee0a b652cdd 5edee0a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
---
title: README
emoji: 🌿
colorFrom: green
colorTo: blue
sdk: static
pinned: false
license: apache-2.0
short_description: An Open-Source Initiative for AI in Agriculture
---
## 🌿 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.
## Common classical problems we handle
- **Segmentation Masks** – Generate binary or multi-class masks for plant structures
- **Annotations** – Add and manage precise annotation/bounding box
- **Image Processing** – Perform preprocessing tasks such as cropping, resizing, and filtering
- **Plant-Type Labeling** – 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}
}
``` |