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I will build a custom ai image segmentation model
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Need a reliable image segmentation solution for your computer vision project?
I develop custom image segmentation pipelines using Python, PyTorch, SAM, CLIP, DINO, CNNs, and Vision Transformers. I can help you test pretrained models, fine-tune a model on your labeled dataset, evaluate segmentation quality, and build a reusable inference pipeline.
Services may include:
Semantic or binary image segmentation
Pretrained SAM model testing
Custom model training or fine-tuning
CLIP, SAM, or DINO-based vision pipelines
Data preprocessing and dataset organization
Mask and overlay visualization
Evaluation using IoU, Dice, accuracy, and related metrics
Reusable Python source code
Model weights and technical documentation
I have practical research experience in vision-language models, multi-backbone fusion, zero-shot learning, and underwater image segmentation.
Please contact me before ordering. The final scope depends on dataset size, annotation quality, image resolution, number of classes, model complexity, and available computing resources.
Large-scale annotation, cloud GPU costs, production deployment, and ongoing maintenance are not included unless agreed separately.
API:
Otros
Experiencia:
Procesamiento de imágenes
•
Detección de objetos
Lenguaje de programación:
Python
Herramientas:
PyTorch
Marcos:
Scikit-learn
•
PyTorch
•
Panda
Mi porfolio
Otros servicios de Ciencia de datos y aprendizaje automático que ofrezco
FAQ
Should I contact you before placing an order?
Yes. Please send a brief project description, dataset size, number of classes, annotation status, expected output, and preferred model. I will confirm the suitable package before you order.
Do I need to provide labeled data?
Labeled images and segmentation masks are normally required for model training or fine-tuning. Pretrained-model testing may not require labeled data, but labels are recommended for quantitative evaluation.
Which models and frameworks can you use?
Depending on the task, I can work with PyTorch, SAM, CLIP, DINO, U-Net, DeepLab, CNNs, Vision Transformers, and related open-source computer vision models.
What files will I receive?
Depending on the selected package, delivery may include Python source code, model weights, an inference script, predicted masks, overlay images, evaluation metrics, and technical documentation.
Are cloud deployment and GPU costs included?
No. Standard packages cover model development and local inference code. Cloud deployment, API integration, paid GPU resources, and ongoing monitoring require a separate agreement.
