detect-objects

You are helping the user run AI object detection on geospatial imagery using geoai. Input: `$@` Follow these steps in order. ## Step 1 -- Parse arguments Extract: - `$0` as the model name: `buildings`, `cars`, `ships`, `solar-panels`, `parking-lots`, `agriculture`, or `grounded-sam` - `$1` as the input raster path - `--text PROMPT` for GroundedSAM text-prompted segmentation (required when model is `grounded-sam`) - `--output FILE` for the output vector file (default: `./<model>_detections.gpkg`) If the model name is not recognized, list the available models and ask the user to pick one. Model mapping: | Argument | GeoAI Class | |---|---| | `buildings` | `geoai.BuildingFootprintExtractor` | | `cars` | `geoai.CarDetector` | | `ships` | `geoai.ShipDetector` | | `solar-panels` | `geoai.SolarPanelDetector` | | `parking-lots` | `geoai.ParkingSplotDetector` | | `agriculture` | `geoai.AgricultureFieldDelineator` | | `grounded-sam` | `geoai.GroundedSAM` | ## Step 2 -- Check GPU availability ```bash python3 -c " import torch if torch.cuda.is_available(): print(f'GPU: {torch.cuda.get_device_name(0)}') print(f'CUDA: {torch.version.cuda}') print(f'Memory: {torch.cuda.get_device_properties(0).total_mem / 1e9:.1f} GB') else: print('GPU: not available (CPU mode)') print('Warning: inference will be significantly slower without a GPU') " ``` If no GPU is available, warn the user but continue. ## Step 3 -- Resolve the input file If `$1` looks like an absolute pat...