Getting Started with CitySeg¶
This guide will help you set up and run your first semantic segmentation task using CitySeg.
Installation¶
Install CitySeg using pip:
Basic Usage¶
Here's a simple example to get you started:
import cityseg as cs
# Load configuration from a YAML file
config = cs.Config.from_yaml("path/to/your/config.yaml")
# Create processor
processor = cs.create_processor(config)
# Process input
processor.process()
Configuration¶
CitySeg uses a YAML configuration file to set up the segmentation pipeline. Here's a basic example:
input: path/to/your/input/file_or_directory
output_prefix: path/to/your/output/directory/output
model:
name: shi-labs/oneformer_cityscapes_swin_large
max_size: 1920 # Set to null to maintain original resolution
device: cuda # or cpu or mps
frame_step: 5 # For video processing, process every 5th frame
save_raw_segmentation: true
save_colored_segmentation: true
save_overlay: true
visualization:
alpha: 0.5
colormap: default
For more detailed information on configuration options, see the Configuration section in the User Guide.
Next Steps¶
- Learn about Image Processing
- Explore Video Processing
- Check out the Examples for more advanced usage