Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Bases on Leaf images we are trying to predict plant disease using convolutional neural network. PyTorch implementation
| Date | Stars |
|---|---|
| 2026-07-31 | 370 |
| 2026-08-01 | 370 |
| 2026-08-02 | 371 |
| 2026-08-03 | 371 |
| 2026-08-04 | 372 |
| 2026-08-06 | 373 |
Today
+1 stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# ⭐Plant-Disease-Detection
* Plant Disease is necessary for every farmer so we are created Plant disease detection using Deep learning. In which we are using convolutional Neural Network for classifying Leaf images into 39 Different Categories. The Convolutional Neural Code build in Pytorch Framework. For Training we are using Plant village dataset. Dataset Link is in My Blog Section.
## ⭐Run Project in your Machine
* You must have **Python3.8** installed in your machine.
* Create a Python Virtual Environment & Activate Virtual Environment [Link](https://docs.python.org/3/tutorial/venv.html)
* Install all the dependencies using below command
`pip install -r requirements.txt`
* Go to the `Flask Deployed App` folder.
* Download the pre-trained model file `plant_disease_model_1.pt` from [here](https://drive.google.com/drive/folders/1ewJWAiduGuld_9oGSrTuLumg9y62qS6A?usp=share_link)
* Add the downloaded file in `Flask Deployed App` folder.
* Run the Flask app using below command `python3 app.py`
* You can also use downloaded file in `Model` Section and play with it using Jupyter Notebook.
## ⭐Contribution ( Open Source )
* This Project is now open source.
* All the developers who are intrested they can contribute in this project.
* Yo can make UI better , make Deep learning model more powerful , add informative markdown file in section...
* If you will change Deep learning make sure you upload updated markdown file (.md) , .pdf and .ipynb in particular section.
* Make sure your code is working. It will not have any type or error.
* You have to fork this project then make a pull request after you testing will successful.
* How to make pull request : https://opensource.com/article/19/7/create-pull-request-github
## ⭐Testing Images
* If you do not have leaf images then you can use test images located in test_images folder
* Each image has its corresponding disease name, so you can verify whether the model is working perfectly or not
## ⭐Blog Link
<a href="https://medium.com/analytics-vidhya/plant-disease-detection-using-convolutional-neural-networks-and-pytorch-87c00c54c88f" target = "_blank">Plant Disease Detection Using Convolutional Neural Networks with PyTorch</a><br>
## ⭐Deployed App
<a href="https://plant-disease-detection-ai.herokuapp.com/" target = "_blank">Plant-Disease-Detection-AI</a><br>
## ⭐Snippet of Web App :
#### Main page
<img src = "demo_images/1.png" > <br>
#### AI Engine
<img src = "demo_images/2.png"> <br>
#### Results Page
<img src = "demo_images/3.png"> <br>
#### Supplements/Fertilizer Store
<img src = "demo_images/4.JPG"> <br>
#### Contact Us
<img src = "demo_images/5.png"> <br><br>
Excerpt of 2,663 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:07a22ecdfda2dd16, topic:deep-learning, topic:pytorch