feat(deployment): centerpoint deployment integration

deployment/projects/centerpoint/__init__.py

@@ -0,0 +1,22 @@
+"""CenterPoint deployment bundle.
+
+This package owns all CenterPoint deployment-specific code (runner/evaluator/loader/pipelines/export).
+It registers a ProjectAdapter into the global `project_registry` so the unified CLI can invoke it.
+"""
+
+from __future__ import annotations
+
+from deployment.projects.centerpoint.cli import add_args
+from deployment.projects.centerpoint.entrypoint import run
+
+# Trigger pipeline factory registration for this project.
+from deployment.projects.centerpoint.pipelines.factory import CenterPointPipelineFactory  # noqa: F401
+from deployment.projects.registry import ProjectAdapter, project_registry
+
+project_registry.register(
+    ProjectAdapter(
+        name="centerpoint",
+        add_args=add_args,
+        run=run,
+    )
+)

deployment/projects/centerpoint/cli.py

@@ -0,0 +1,14 @@
+"""CenterPoint CLI extensions."""
+
+from __future__ import annotations
+
+import argparse
+
+
+def add_args(parser: argparse.ArgumentParser) -> None:
+    """Register CenterPoint-specific CLI flags onto a project subparser."""
+    parser.add_argument(
+        "--rot-y-axis-reference",
+        action="store_true",
+        help="Convert rotation to y-axis clockwise reference (CenterPoint ONNX-compatible format)",
+    )

deployment/projects/centerpoint/config/deploy_config.py

@@ -2,12 +2,6 @@
 CenterPoint Deployment Configuration
 """
 
-# ============================================================================
-# Task type for pipeline building
-# Options: 'detection2d', 'detection3d', 'classification', 'segmentation'
-# ============================================================================
-task_type = "detection3d"
-
 # ============================================================================
 # Checkpoint Path - Single source of truth for PyTorch model
 # ============================================================================
@@ -38,16 +32,15 @@
 # ============================================================================
 # Unified Component Configuration (Single Source of Truth)
 #
+# Component key is the unique identifier (used for config lookup, filenames, logs).
 # Each component defines:
-#   - name: Component identifier used in export
 #   - onnx_file: Output ONNX filename
 #   - engine_file: Output TensorRT engine filename
 #   - io: Input/output specification for ONNX export
 #   - tensorrt_profile: TensorRT optimization profile (min/opt/max shapes)
 # ============================================================================
 components = dict(
-    voxel_encoder=dict(
-        name="pts_voxel_encoder",
+    pts_voxel_encoder=dict(
         onnx_file="pts_voxel_encoder.onnx",
         engine_file="pts_voxel_encoder.engine",
         io=dict(
@@ -70,8 +63,7 @@
             ),
         ),
     ),
-    backbone_head=dict(
-        name="pts_backbone_neck_head",
+    pts_backbone_neck_head=dict(
         onnx_file="pts_backbone_neck_head.onnx",
         engine_file="pts_backbone_neck_head.engine",
         io=dict(
@@ -111,7 +103,7 @@
 # ============================================================================
 runtime_io = dict(
     # This should be a path relative to `data_root` in the model config.
-    info_file="info/t4dataset_j6gen2_infos_val.pkl",
+    info_file="info/t4dataset_j6gen2_base_infos_test.pkl",
     sample_idx=1,
 )
 
@@ -128,6 +120,7 @@
 
 # ============================================================================
 # TensorRT Build Settings (shared across all components)
+# Supports `auto`, `fp16`, `fp32_tf32`, and `strongly_typed`
 # ============================================================================
 tensorrt_config = dict(
     precision_policy="auto",
@@ -161,10 +154,11 @@
 
 # ============================================================================
 # Verification Configuration
+# Note that fp16 can failed in this tolerance (max difference > tolerance)
 # ============================================================================
 verification = dict(
-    enabled=False,
-    tolerance=1e-1,
+    enabled=True,
+    tolerance=1,
     num_verify_samples=1,
     devices=devices,
     scenarios=dict(

deployment/projects/centerpoint/entrypoint.py

@@ -0,0 +1,79 @@
+"""CenterPoint deployment entrypoint invoked by the unified CLI."""
+
+from __future__ import annotations
+
+import argparse
+import logging
+
+from mmengine.config import Config
+
+from deployment.cli.args import setup_logging
+from deployment.configs import BaseDeploymentConfig
+from deployment.core.contexts import CenterPointExportContext
+from deployment.projects.centerpoint.eval.evaluator import CenterPointEvaluator
+from deployment.projects.centerpoint.eval.metrics_utils import extract_t4metric_v2_config
+from deployment.projects.centerpoint.io.data_loader import CenterPointDataLoader
+from deployment.projects.centerpoint.runner import CenterPointDeploymentRunner
+
+_REQUIRED_COMPONENTS = ("pts_voxel_encoder", "pts_backbone_neck_head")
+
+
+def _validate_required_components(components_cfg) -> None:
+    """Validate that all CenterPoint required components exist in the config.
+
+    Args:
+        components_cfg: Components config with get_component(name).
+
+    Raises:
+        KeyError or similar: If any of _REQUIRED_COMPONENTS is missing.
+    """
+    for component_name in _REQUIRED_COMPONENTS:
+        components_cfg.get_component(component_name)
+
+
+def run(args: argparse.Namespace) -> int:
+    """Run the CenterPoint deployment workflow for the unified CLI.
+
+    Args:
+        args: Parsed command-line arguments containing deploy_cfg and model_cfg paths.
+
+    Returns:
+        Exit code (0 for success).
+    """
+    logger = setup_logging(args.log_level)
+
+    deploy_cfg = Config.fromfile(args.deploy_cfg)
+    model_cfg = Config.fromfile(args.model_cfg)
+    config = BaseDeploymentConfig(deploy_cfg)
+
+    _validate_required_components(config.components_cfg)
+
+    logger.info("=" * 80)
+    logger.info("CenterPoint Deployment Pipeline (Unified CLI)")
+    logger.info("=" * 80)
+
+    data_loader = CenterPointDataLoader(
+        info_file=config.runtime_config.info_file,
+        model_cfg=model_cfg,
+    )
+    logger.info(f"Loaded {data_loader.num_samples} samples")
+
+    metrics_config = extract_t4metric_v2_config(model_cfg, logger=logger)
+
+    evaluator = CenterPointEvaluator(
+        model_cfg=model_cfg,
+        metrics_config=metrics_config,
+        components_cfg=config.components_cfg,
+    )
+
+    runner = CenterPointDeploymentRunner(
+        data_loader=data_loader,
+        evaluator=evaluator,
+        config=config,
+        model_cfg=model_cfg,
+        logger=logger,
+    )
+
+    context = CenterPointExportContext(rot_y_axis_reference=bool(getattr(args, "rot_y_axis_reference", False)))
+    runner.run(context=context)
+    return 0