You will get an object detection system using PyTorch or Hugging Face
Rising Talent
Rising Talent
Project details
I will build a high-quality object detection system using Hugging Face Transformers and modern deep learning techniques. This service is ideal for applications such as image analysis, automation, security systems, and AI-powered computer vision solutions.
I can work with pre-trained models or fine-tune a custom object detection model on your dataset, depending on your requirements. I focus on delivering clean, efficient, and well-documented solutions that are ready for real-world use.
My workflow includes data preparation, model development, evaluation, and optional deployment support. I use tools such as Python, PyTorch, TensorFlow, and Hugging Face libraries to ensure accurate and scalable results.
You will receive:
• Clean and structured source code
• A trained object detection model
• Documentation and usage guidance
• Optional API or application deployment
I aim to provide reliable, efficient, and professional AI solutions tailored to your needs.
I can work with pre-trained models or fine-tune a custom object detection model on your dataset, depending on your requirements. I focus on delivering clean, efficient, and well-documented solutions that are ready for real-world use.
My workflow includes data preparation, model development, evaluation, and optional deployment support. I use tools such as Python, PyTorch, TensorFlow, and Hugging Face libraries to ensure accurate and scalable results.
You will receive:
• Clean and structured source code
• A trained object detection model
• Documentation and usage guidance
• Optional API or application deployment
I aim to provide reliable, efficient, and professional AI solutions tailored to your needs.
Machine Learning Tools
Python, PyTorchWhat's included
| Service Tiers |
Starter
$15
|
Standard
$20
|
Advanced
$25
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 6 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 0 | 1 | 2 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20 - $40
Additional Revision
+$10
Additional Model Variation
(+ 1 Day)
+$20
Additional Scenario
(+ 1 Day)
+$15
Model Deployment
(+ 2 Days)
+$40Frequently asked questions
About Ibrahim
Computer Vision Engineer | Image AI & Object Detection
Doha, Qatar - 4:52 pm local time
Images may need to be classified. Objects may need to be detected. Defects may need to be identified. Visual data may need to be cleaned, organised, labelled, analysed, or used to test whether computer vision can solve a real problem.
That is where I help.
I am Ibrahim, and I provide image-based Computer Vision and Deep Learning services for clients who want to explore, build, or improve practical AI solutions using images.
I focus on clear and realistic computer vision work, including:
- Image classification
- Object detection
- Defect detection and visual inspection
- Image segmentation
- Visual recognition
- Image preprocessing
- Dataset preparation and cleaning
- Annotation review and label quality checks
- Model training and fine-tuning
- Model evaluation and accuracy improvement
- Computer vision prototype development
Typical projects I can support:
- Building a proof of concept for an image-based AI idea
- Training a model on a custom image dataset
- Improving an existing model’s accuracy
- Reviewing image data before model training
- Checking whether labels or annotations are suitable
- Detecting objects, products, defects, or visual features in images
- Classifying images into categories
- Segmenting important areas in an image
- Testing whether computer vision is suitable for a specific use case
How I usually start:
- I first review the project goal, available images, labels or annotations, expected output, and the practical problem the client wants to solve.
Then I identify the main gap:
- Is the data good enough?
- Are the labels consistent?
- Is the model approach suitable?
- Is the output useful for the client’s decision or workflow?
This helps keep the project focused and practical.
My goal is not only to train a model, but to help clients understand whether computer vision can solve their visual problem in a useful and realistic way.
For many projects, the best first step is not a full AI system. It may be a small prototype, a dataset review, a model test, or an accuracy improvement plan. This gives the client a clearer technical direction before investing more time or budget.
I work best with clients who have image data and want to know whether AI can classify, detect, segment, inspect, or analyse it reliably.
If you have an image-based AI idea or an existing computer vision project, I would be happy to review it and suggest the best next step.
Steps for completing your project
After purchasing the project, send requirements so Ibrahim can start the project.
Delivery time starts when Ibrahim receives requirements from you.
Ibrahim works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis
Understand your use case, dataset, object classes, and expected output format.
Data Preprocessing
Clean and preprocess images and annotations for object detection training.