You will get an build a YOLO object detection web app for your images
Project details
I will build a computer vision web app for object detection using Python, Streamlit, OpenCV, and YOLO.
The app will allow users to upload images, run object detection, view bounding boxes and confidence scores, review detected classes in a results table, and download the annotated output image.
This is useful for computer vision demos, product detection, object counting prototypes, image inspection workflows, traffic/object monitoring demos, and proof-of-concept AI applications.
What I can build:
• Streamlit object detection web app
• Image upload interface
• YOLO object detection inference
• Confidence threshold control
• Bounding box visualization
• Detection results table
• Annotated image download option
• Clean Python code and setup instructions
The default YOLO model detects common object classes. For custom objects, you will need a labeled dataset or an already trained YOLO model.
This project is best for prototypes, demos, internal tools, research experiments, and small computer vision proof-of-concepts. For custom training, deployment, real-time video, CCTV, or large-scale inference, please contact me before ordering.
The app will allow users to upload images, run object detection, view bounding boxes and confidence scores, review detected classes in a results table, and download the annotated output image.
This is useful for computer vision demos, product detection, object counting prototypes, image inspection workflows, traffic/object monitoring demos, and proof-of-concept AI applications.
What I can build:
• Streamlit object detection web app
• Image upload interface
• YOLO object detection inference
• Confidence threshold control
• Bounding box visualization
• Detection results table
• Annotated image download option
• Clean Python code and setup instructions
The default YOLO model detects common object classes. For custom objects, you will need a labeled dataset or an already trained YOLO model.
This project is best for prototypes, demos, internal tools, research experiments, and small computer vision proof-of-concepts. For custom training, deployment, real-time video, CCTV, or large-scale inference, please contact me before ordering.
What's included
| Service Tiers |
Starter
$180
|
Standard
$350
|
Advanced
$600
|
|---|---|---|---|
| Delivery Time | 4 days | 6 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 1 | 2 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | 2 | 3 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
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SJ
Shane J.
Jun 17, 2022
Fix Wordpress Elementor 406 Error (Server Error)
Amazing job! My expectations have been well exceeded! Very collaborative and knowledgeable person. I had a great experience. Thanks.
About Aun
Applied AI & Computer Vision Developer | Python, LLM Apps, Streamlit
Verona, Italy - 5:29 pm local time
My work focuses on AI chatbots, document question-answering apps, customer support assistants, computer vision demos, object detection, Streamlit dashboards, data analysis, and machine learning prototypes.
I have a Bachelor’s background in Computer Science and I am currently completing a Master’s in Computer Intelligent Systems. My thesis research is being conducted at EPFL in Lausanne, where I work with multidimensional biological imaging data, temporal tracking, image analysis workflows, method evaluation, and practical scientific Python development.
What I can help you with:
• AI chatbot and FAQ assistant prototypes
• Document Q&A apps for PDF/TXT files
• LLM-based apps using OpenAI API
• Computer vision apps using OpenCV, YOLO, and image processing
• Object detection demos and model inference workflows
• Streamlit dashboards for ML models, data analysis, and monitoring
• Python data cleaning, analysis, visualization, and automation
• Machine learning prototypes using scikit-learn, TensorFlow, or PyTorch
• Technical documentation, code cleanup, debugging, and reproducible project structure
Recent portfolio projects include:
• AI Customer Support Chatbot — FAQ-based chatbot with lead capture
• AI Document Chatbot — PDF/TXT question-answering app
• YOLO Object Detection Web App — image upload, object detection, confidence scores, and annotated output download
I focus on clear communication, clean code, realistic expectations, and practical delivery. I do not promise fake accuracy or instant results. I build understandable solutions, explain the workflow, and share code that can be tested and improved.
A good first project with me can be an AI chatbot prototype, document Q&A app, Streamlit dashboard, computer vision demo, Python automation script, or ML model evaluation task.
Steps for completing your project
After purchasing the project, send requirements so Aun can start the project.
Delivery time starts when Aun receives requirements from you.
Aun works on your project following the steps below.
Revisions may occur after the delivery date.
YOLO app with custom model support
I will review your image examples, target object classes, expected output, and whether you need a pretrained YOLO model or custom model support.
Set up detection workflow
I will prepare the Python and YOLO detection workflow, including model loading, image upload, confidence threshold, and inference logic.