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src/velocity_prediction/config.py

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+"""
+Global configuration for velocity prediction.
+"""
+
+from dataclasses import dataclass, field
+from pathlib import Path
+
+
+# ──────────────────────────── Dataset paths ────────────────────────────
+
+DATASET_ROOT = Path(__file__).resolve().parents[2] / "dataset"
+
+# Velocity normalization stats (computed from training set)
+VELOCITY_MEAN = [0.859184, -0.783945]   # [vx, vy]
+VELOCITY_STD  = [2.244513,  1.088335]   # [vx, vy]
+
+# TRAIN_SCENES = [
+#     "indoor_forward_3", "indoor_forward_5", "indoor_forward_6",
+#     "indoor_forward_7", "indoor_forward_9", "indoor_forward_10",
+#     "indoor_45_2", "indoor_45_4", "indoor_45_9", "indoor_45_12",
+# ]
+# VAL_SCENES = [
+#     "indoor_45_13", "indoor_45_14",
+# ]
+# TEST_SCENES = [
+#     "outdoor_forward_1", "outdoor_forward_3", "outdoor_forward_5",
+#     "outdoor_45_1",
+# ]
+
+TRAIN_SCENES = [
+    "indoor_forward_3", "indoor_forward_9", "indoor_forward_10",  # Easy
+    "indoor_forward_5", "indoor_forward_6",                       # Medium
+    "outdoor_forward_3"                                           # Medium 室外
+]
+VAL_SCENES = [
+    "indoor_forward_7",      # Hard 室内
+    "outdoor_forward_1"      # Easy 室外
+    # "indoor_forward_3", "indoor_forward_9", "indoor_forward_10",  # Easy
+]
+TEST_SCENES = [
+    "indoor_forward_7",      # Hard 室内
+    "outdoor_forward_1",     # Easy 室外
+    "outdoor_forward_5"      # Hard 室外
+    # "indoor_forward_3", "indoor_forward_9", "indoor_forward_10",  # Easy
+]
+
+
+# ──────────────────────────── Model architecture ────────────────────────────
+
+@dataclass
+class CNNConfig:
+    in_channels: int = 1
+    channels: tuple = (32, 64, 128, 256)       # per-layer output channels
+    kernel_size: int = 3
+    pool_size: int = 2
+    use_bn: bool = True
+
+
+@dataclass
+class PoseMLPConfig:
+    input_dim: int = 3
+    hidden_dim: int = 32
+    output_dim: int = 64
+
+
+@dataclass
+class GRUConfig:
+    input_size: int = 320       # CNN(256) + PoseMLP(64)
+    hidden_size: int = 128
+    num_layers: int = 1
+    dropout: float = 0.0
+
+
+@dataclass
+class HeadConfig:
+    input_dim: int = 128        # GRU hidden_size
+    hidden_dim: int = 64
+    output_dim: int = 2         # [vx_body, vy_body]
+
+
+@dataclass
+class ModelConfig:
+    cnn: CNNConfig = field(default_factory=CNNConfig)
+    pose_mlp: PoseMLPConfig = field(default_factory=PoseMLPConfig)
+    gru: GRUConfig = field(default_factory=GRUConfig)
+    head: HeadConfig = field(default_factory=HeadConfig)
+
+
+# ──────────────────────────── Training ────────────────────────────
+
+@dataclass
+class TrainConfig:
+    seq_len: int = 8                    # frames per training sequence
+    batch_size: int = 32
+    epochs: int = 100
+    lr: float = 1e-3
+    weight_decay: float = 1e-5
+    lr_scheduler_step: int = 30
+    lr_scheduler_gamma: float = 0.5
+    num_workers: int = 4
+    seed: int = 42
+
+    # Event simulation
+    event_threshold: float = 0.1
+    event_use_log: bool = True
+    event_auto_threshold: bool = False
+
+    # Logging / checkpoint
+    log_dir: str = "logs"
+    checkpoint_dir: str = "checkpoints"
+    log_interval: int = 10
+    save_interval: int = 10
+
+
+# ──────────────────────────── Singleton instances ────────────────────────────
+
+model_cfg = ModelConfig()
+train_cfg = TrainConfig()