I will integrate deep learning and computer vision models into a web app


About this gig
Turn Your AI Model Into a Fully Functional Web Application!
Are you looking to deploy your Computer Vision project to the real world? I specialize in building end-to-end Image Classification Web Applications using Python, Flask, and Deep Learning models (like MobileNetV2, ResNet, etc.).
Whether you already have a trained .h5 / .tflite model or need one built from scratch, I can wrap it into a clean, responsive, and fast web interface.
My Core Expertise:
AI Integration: Seamlessly connecting Deep Learning models to a backend server.
Multi-Stage Pipelines: I can build complex workflows, such as a Two-Stage Architecture (Model 1: Image Verifier to check if the image is valid -> Model 2: Main Classifier to detect conditions/categories).
Robust Backend: Fast and secure API development using Python Flask.
Frontend UI: Clean and intuitive interface for users to upload images and view prediction results instantly.
What will you get?
Fully functional web application (Frontend + Backend).
Clean, well-documented Python code.
Instructions on how to run the app on your local machine or prepare it for deployment.
Please send me a message before placing an order.
Get to know Farrel
build a custom machine learning web app using python flask
- FromIndonesia
- Member sinceMar 2026
- Avg. response time1 hour
Languages
Indonesian, English
FAQ
What do I need to provide to get started?
If you have an existing pre-trained model, please provide the model file (e.g., .h5 or .tflite). If you need me to train a custom model from scratch, please provide a well-organized and labeled image dataset.
What technologies and frameworks do you use?
I primarily use Python and Flask for the web backend. For the AI and Computer Vision side, I work with TensorFlow/Keras and specialize in efficient architectures like MobileNetV2.
Will I receive the full source code for the web application?
Yes, absolutely! You will receive the complete source code for both the web interface and the Flask backend, along with clear instructions on how to run the application on your local machine.

