abhishekrs4/htsm_oil_spill_segmentation

HTSM Masterwork

Hey there , I am Abhishek

👨‍💻 About Me

• 👨🏽‍🎓 I am a graduate Artificial Intelligence (AI) Engineer from the University of Groningen. I am a motivated, talented, hardworking, and fast-learning professional. I believe that change is the only constant. In this bold new era of the AI world, I'm always open to upgrading my real human intelligence with new skills be it related to any one of the following --- technology, social, life, personality.
• I am from 🇮🇳, currently living in 🇳🇱
• 📧 If you would like to contact me, you can always reach me - [email protected],

Portfolio and contact info

Projects with application deployments

• HTSM_Oil_Spill_Segmentation Streamlit application has been deployed to HuggingFace
• image_colourization_CGAN FastAPI application has been deployed to HuggingFace with a streamlit frontend application HuggingFace
• Handwriting Recognition Flask application has been deployed to HuggingFace with a streamlit frontend application HuggingFace
• Cassava Leaf Disease Classification Flask application has been deployed to HuggingFace with a streamlit frontend application HuggingFace
• ML_water_potability FastAPI application has been deployed to HuggingFace
• overhead_mnist FastAPI application has been deployed to HuggingFace with a streamlit frontend application HuggingFace
• ML_multi_app_deployment is a project with multi-application deployment, a Streamlit frontend and a FastAPI backend

🛠️ Tech and Programming Language Skills

• Core skills - Computer Vision Algorithms, Machine Learning and Deep Learning Algorithms, MLOps, Model Optimization, Model Inference and Evaluation, Embedded / Edge ML, Containerization and Model Deployment, Data Pipelines
• Programming languages - Python, C++, C, Matlab
• Packages and frameworks - Numpy, Pandas, Scipy, Scikit, Matplotlib, Seaborn, PyTorch, TensorFlow, OpenCV, Streamlit, FastAPI, Flask etc...
• Version control (CI / CD) - Git, GitHub, GitLab
• Miscellaneous tech - Linux, TensorRT, MLFlow, Docker, Kubernetes, HuggingFace, Microsoft Azure, AWS, SQL, SQLite, MySQL
• ML on embedded computing hardware / edge devices - Raspberry Pi, Intel Movidius, Nvidia Jetson, Nvidia Xavier

Areas of Interests

• Interested in areas of Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, and Data Science.

Hobbies

• Playing badminton, playing chess, watching technology videos, listening to music, going for walks etc.

htsm_oil_spill_segmentation's Issues

HTSM_Oil_Spill_Segmentation_task_1

• use black for code formatting

HTSM_Oil_Spill_Segmentation_task_2

The original images padded with patches

Hello sir. In the data preprocessing step, the original images, in 1250 × 650 dimensions, were padded with patches on all 4 sides of the image to produce resulting images of 1280 × 672. The patch padding was done in such a way as to select a patch of pixels with the sea surface. May I ask what is the benefit of padding the original images with patches?