Chengfang Lu
0b8ade048e
Replace subprocess build with promote_batch SDK, add ADAS cuboid export/fit/validate pipeline, stage normalization, and offline unit tests wired into smoke_labeling_api. Co-authored-by: Cursor <cursoragent@cursor.com>
64 lines
1.6 KiB
YAML
64 lines
1.6 KiB
YAML
# 路径均相对 HSAP/ 根。训练用哪些数据包由 active_packs 控制（add/build 不会自动改这里）
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version: 1
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workspace: .
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platform:
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version: 1
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data:
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batch_meta_schema: as-batch-v1
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drop_zones:
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dms_inbox: "datasets/dms/inbox/{task}/{batch}"
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dms_sources: "datasets/dms/packs/{pack}/{task}/sources/{batch}"
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lane_inbox: "datasets/lane/inbox/{batch}"
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adas_inbox: "data/送标/adas/inbox/{task}/{batch}"
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training:
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tracks:
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local_allowed: true
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platform_require_audit: true
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agents:
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trace_enabled: true
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default_graph: ingest_flow
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automation:
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on_new_sources: notify
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require_eval_before_promote: true
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min_delta_map50: -0.01
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baseline_metrics:
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dam: {map50: null, map50_95: null}
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ddaw: {map50: null}
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projects:
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dms:
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root: datasets/dms
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registry: datasets.registry.yaml
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packs_registry: data_packs.yaml
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base_pack: dms_v1
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active_packs:
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- dms_v1
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lane:
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root: datasets/lane
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registry: datasets_registry.json
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base_pack: lane_v1
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active_packs:
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- lane_v1
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merge:
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train: lists_merged/train_active.txt
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val: lists_merged/val_active.txt
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train:
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workdir: algorithms/lane_ufld/code/UFLD
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config: configs/mufld_lane_multi_pack.py
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adas:
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root: datasets/adas
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# 数据湖：宿主机 DATA/data/送标/adas → inbox/{task}/{batch}/images/
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registry: adas.registry.yaml
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packs_registry: data_packs.yaml
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base_pack: adas_moon3d_v1
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active_packs:
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- adas_moon3d_v1
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merge:
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train: lists/train_stems.txt
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val: lists/val_stems.txt
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