Crop Yield Prediction: This project uses various data sources such as weather patterns, temperature, and previous crop yields to predict future crop yields. Advanced statistical and machine learning models are employed to make accurate predictions.
Weld Defect Detection: This project is a scope of computer vision and uses image processing techniques to detect defects in welds. It involves capturing images of welds, analyzing them using computer vision algorithms, and identifying any defects present. This can help improve the quality of the final product and prevent costly failures.
Point Cloud Ground Segmentation: This project works with point clouds, which are 3D representations of a physical environment. The goal of this project is to perform ground segmentation, which involves separating the ground points from the non-ground points in the point cloud data. This can be useful for various applications, such as autonomous navigation and mapping.
Crop Yield Prediction:
Weld Defect Detection:
Point Cloud Ground Segmentation:
Use the requirements file in this repo to create a new environment.
pyenv local 3.9.8
python -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt