34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
"""
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Configuration for training Mask R-CNN on the Penn-Fudan dataset.
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"""
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from configs.base_config import base_config
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# Create a copy of the base configuration
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config = base_config.copy()
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# Update specific values for this experiment
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config.update(
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{
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# Core configuration
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"config_name": "pennfudan_maskrcnn_v1",
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"data_root": "data/PennFudanPed",
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"num_classes": 2, # background + pedestrian
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# Training parameters - modified for memory constraints
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"batch_size": 1, # Reduced from 2 to 1 to save memory
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"num_epochs": 10,
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# Optimizer settings
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"lr": 0.002, # Slightly reduced learning rate for smaller batch size
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"momentum": 0.9,
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"weight_decay": 0.0005,
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# Memory optimization settings
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"pin_memory": False, # Set to False to reduce memory pressure
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"num_workers": 2, # Reduced from 4 to 2
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# Device settings
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"device": "cuda",
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}
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)
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# Ensure derived paths or settings are consistent if needed
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# (Not strictly necessary with this simple structure)
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