This project generates semantic segmentation maps of images using PyTorch and NumPy. Semantic segmentation is the process of assigning a class label to each pixel in an image, thus dividing the image into regions of interest. This tool utilizes deep learning techniques implemented in PyTorch for efficient and accurate segmentation.
- Semantic Segmentation: Generate pixel-level segmentation maps for input images.
- PyTorch Integration: Leveraging the power of PyTorch for deep learning-based segmentation.
- Efficient Processing: Utilizes NumPy for efficient array manipulation and processing.
Below are some examples of original images and their respective segmentation maps generated by this tool:
