"""
Configuration for training Mask R-CNN on the Penn-Fudan dataset.
"""

from configs.base_config import base_config

# Create a copy of the base configuration
config = base_config.copy()

# Update specific values for this experiment
config.update(
    {
        # Core configuration
        "config_name": "pennfudan_maskrcnn_v1",
        "data_root": "data/PennFudanPed",
        "num_classes": 2,  # background + pedestrian
        # Training parameters - modified for memory constraints
        "batch_size": 1,  # Reduced from 2 to 1 to save memory
        "num_epochs": 10,
        # Optimizer settings
        "lr": 0.002,  # Slightly reduced learning rate for smaller batch size
        "momentum": 0.9,
        "weight_decay": 0.0005,
        # Memory optimization settings
        "pin_memory": False,  # Set to False to reduce memory pressure
        "num_workers": 2,  # Reduced from 4 to 2
        # Device settings
        "device": "cuda",
    }
)

# Ensure derived paths or settings are consistent if needed
# (Not strictly necessary with this simple structure)