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๐Ÿ›ฃ Building an end-to-end Promptable Semantic Segmentation (Computer Vision) project from training to inferencing a model on LandCover.ai data (Satellite Imagery).

License: MIT License

Dockerfile 0.02% Jupyter Notebook 99.19% Python 0.80%
ai-project ai-projects artificial-intelligence computer-vision deep-learning end-to-end image-segmentation landcover machine-learning-project machine-learning-projects ml-project ml-projects neural-network promptable promptable-segmentation pytorch satellite-imagery segmentation-models-pytorch semantic-segmentation unet

land-cover-semantic-segmentation-pytorch's Introduction

Hi there, I'm Souvik Majumder... nice to see you!

A passionate problem solver and dedicated engineer hailing from India, I thrive on unraveling intricate challenges. My software journey revolves around harnessing the power of digital technologies such as Data Science, Artificial Intelligence, and Cloud Computing, transforming bold ideas into reality while generating substantial value for businesses and society. I take great care in the things I build.

  • ๐Ÿ”ญ Currently, I am working as a Machine Learning Engineer at Siemens, where I contribute to innovative projects.
  • ๐ŸŒฑ I am constantly expanding my skills in areas such as Data Science, Computer Vision, Time Series Forecasting, Natural Language Processing, Cloud platforms (Azure, AWS), and MLOps. I am passionate about staying at the forefront of technological advancements.
  • ๐Ÿ In addition to my professional work, I enjoy teaching Python, Data Science, Artificial Intelligence, Machine Learning, and Deep Learning.
  • โšก Fun fact: Since childhood, I have had a deep love for the arts, particularly painting, drawing, and sketching. At one point, I even aspired to become a full-time artist! ๐Ÿ˜…

๐Ÿ“ซ Find me on the web:

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๐Ÿ‘จโ€๐Ÿ’ป Technologies & Tools:

python cpp c conda tensorflow keras pytorch scikit-learn numpy pandas opencv postgresql git docker aws azure

๐Ÿค– GitHub Stats:

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land-cover-semantic-segmentation-pytorch's Issues

testing on own dataset

I tried adding an own tif file to test folder, but showing me an error.
Is there a way to add and test on our own dataset?

File path seems to be correct why is this happening

Built the model successfully! Traceback (most recent call last): File "/home/abhi/Land-Cover-Semantic-Segmentation-PyTorch-main/src/train.py", line 173, in <module> raise e File "/home/abhi/Land-Cover-Semantic-Segmentation-PyTorch-main/src/train.py", line 167, in <module> train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) File "/home/abhi/.conda/envs/python-ml/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 351, in __init__ sampler = RandomSampler(dataset, generator=generator) # type: ignore[arg-type] File "/home/abhi/.conda/envs/python-ml/lib/python3.9/site-packages/torch/utils/data/sampler.py", line 107, in __init__ raise ValueError("num_samples should be a positive integer " ValueError: num_samples should be a positive integer value, but got num_samples=0

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