You will get plant disease detection website using Deep Learning


Project details
This AI-powered Plant Disease Detection Web App enables users to upload leaf images and instantly detect plant diseases using a deep learning model. It features secure user authentication, personalized image classification history, and a user-friendly interface. Ideal for farmers, agronomists, or agricultural startups, this solution streamlines disease diagnosis and supports better crop management. Built with Flask, TensorFlow, and SQLite, it's fully functional, customizable, and ready for deployment.
Machine Learning Tools
ChatGPT, Keras, NumPy, OpenCV, pandas, Python, TensorFlowWhat's included $60
These options are included with the project scope.
$60
- Delivery Time 2 days
- Number of Revisions 3
- Number of Model Variations 4
- Number of Scenarios 4
- Number of Graphs/Charts 3
- Model Validation/Testing
- Model Documentation
- Data Source Connectivity
- Source Code
Optional add-ons
You can add these on the next page.
Fast 1 Day Delivery
+$70
Additional Model Variation
+$10About Muhammad
AI/ML Engineer | NLP | AI Agent | Voice AI | LLM | RAG
Mian Channun, Pakistan - 7:24 am local time
-1. Knows Python, TensorFlow, PyTorch, and builts in cloud integration for scalable, and production-ready AI systems.
-2. From data analysis to full implementation, I manage projects with a focus on real-world results.
-3. Clear communication and collaboration are my priorities. I keep clients informed every step of the way.
If you need powerful AI solutions to transform your business, let’s connect!
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Train Model
In this step we will develop our model and train on our dataset. After Training Model we check the accuracy by testing dataset and then we save it.
Develop frontend using HTML and CSS
In this section we develop the frontend in which we have multiple pages like home, login, signup, history and result