DaftJun commited on
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85237c9
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Add 1 synchronized three-view uint16 NumPy training samples

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README.md ADDED
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+ ---
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+ language:
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+ - zh
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+ - en
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+ task_categories:
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+ - other
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+ tags:
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+ - radio-propagation
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+ - world-model
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+ - sionna
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+ - multimodal
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+ pretty_name: Low-altitude RF world-model training episodes
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+ ---
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+
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+ # Low-altitude RF world-model training data
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+
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+ 推荐下载 **compact_uint16** 完整 NumPy 训练包。当前清单含 **1 条**(动态 UAV RF 实体 1 条,历史辅助 0 条)。统计范围:`committed_on_huggingface`,正在增量上传,尚不是全量完成声明。
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+
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+ 完整下载清单:[`compact_uint16/manifests/train.jsonl`](https://huggingface.co/datasets/DaftJun/RFWM/resolve/main/compact_uint16/manifests/train.jsonl)。每行含仓库内路径、字节数、SHA256、城市、物理场景组、版本及训练用途。每个 `.tar.gz` 是可独立读取的完整样本,包含:
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+
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+ - `rss_dbm_uint16.npy`:RSS,逻辑形状 `[30,24,512,512]`,轴为时间、高度、y、x;NumPy Fortran 存储布局用于压缩。
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+ - `quantization.json`:0.01 dB 步长,偏移 32768,无效码 0。解码结果单位仍为 **dBm**。相对现有 centi-dBm 训练数据可精确还原,无额外量化损失,不截断有效值。
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+ - `states.npz`、`array_schema.json`、`heights_m.npy`、`timestamps_s.npy`:保留原训练文件的状态、动作、链路、材料、掩码、属性和字段映射;以实际样本字段为准。
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+ - `visual/bs/`、`visual/topdown/`、`visual/elevated/`:每路 30 张 PNG,共 90 张;`visual/synchronization.json` 含同步时间、相机标定及 UAV 标注。
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+ - `metadata.json`、`config.json`、`state_schema.json`,以及源样本提供的 `actions.json`、`scene_metadata.json`。
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+ - `read_sample.py` 和转换校验记录。仅需 NumPy,无需 HDF5 插件。
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+
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+ ```python
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+ from read_sample import load_rss
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+ rss_dbm = load_rss("extracted_sample", frames=slice(0, 5))
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+ # float32 dBm;无效位置 NaN。解码必须先转有符号整数,避免 uint16 下溢。
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+ ```
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+
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+ 30 帧时间通常为 0–29 s,具体以 `timestamps_s.npy` 为准;高度逐样本采样,以 `heights_m.npy` 为准。先解压后可 mmap 读取存储数组;读取完整解码 RSS 约需 720 MiB 内存,训练时可按帧/片段加载。
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+
36
+ 所有发布样本为训练集;当前不提供独立测试集。同一物理场景的不同格式、版本或重试不能算独立场景,分组请使用 `physical_episode_group`。历史辅助样本的光学 UAV 不意味着原 RF 中有 UAV 实体;主训练与历史辅助清单分别为 `dynamic_rf_train.jsonl` 和 `legacy_aux_train.jsonl`。
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+
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+ 地图主要为真实建筑轮廓挤出几何,部分高度为估计;视觉为合成渲染,不是真实照片。材料参数包含合成分组与动态变化,不是逐栋实测材料。固定预算单次 RT 样本不做统计置信度验证,具体读取 `qa_protocol`、`confidence_evaluated` 和逐样本 metadata。转换校验只验证存储往返、状态及视觉同步,不声称重新验证 RT 的物理误差。
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+
40
+
41
+ 本仓库是完整 uint16 NumPy 训练包的第二发布仓库,源仓库为 [PATIENTHZ/low-altitude-rf-worldmodel](https://huggingface.co/datasets/PATIENTHZ/low-altitude-rf-worldmodel). 两个仓库相同 record_id 的训练包保持相同 SHA256;不要跨仓库重复计数。 本仓库不包含源仓库旧版 float32 存储版本;服务器原始 RF 归档继续保留。
compact_uint16/README.md ADDED
@@ -0,0 +1,41 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language:
3
+ - zh
4
+ - en
5
+ task_categories:
6
+ - other
7
+ tags:
8
+ - radio-propagation
9
+ - world-model
10
+ - sionna
11
+ - multimodal
12
+ pretty_name: Low-altitude RF world-model training episodes
13
+ ---
14
+
15
+ # Low-altitude RF world-model training data
16
+
17
+ 推荐下载 **compact_uint16** 完整 NumPy 训练包。当前清单含 **1 条**(动态 UAV RF 实体 1 条,历史辅助 0 条)。统计范围:`committed_on_huggingface`,正在增量上传,尚不是全量完成声明。
18
+
19
+ 完整下载清单:[`compact_uint16/manifests/train.jsonl`](https://huggingface.co/datasets/DaftJun/RFWM/resolve/main/compact_uint16/manifests/train.jsonl)。每行含仓库内路径、字节数、SHA256、城市、物理场景组、版本及训练用途。每个 `.tar.gz` 是可独立读取的完整样本,包含:
20
+
21
+ - `rss_dbm_uint16.npy`:RSS,逻辑形状 `[30,24,512,512]`,轴为时间、高度、y、x;NumPy Fortran 存储布局用于压缩。
22
+ - `quantization.json`:0.01 dB 步长,偏移 32768,无效码 0。解码结果单位仍为 **dBm**。相对现有 centi-dBm 训练数据可精确还原,无额外量化损失,不截断有效值。
23
+ - `states.npz`、`array_schema.json`、`heights_m.npy`、`timestamps_s.npy`:保留原训练文件的状态、动作、链路、材料、掩码、属性和字段映射;以实际样本字段为准。
24
+ - `visual/bs/`、`visual/topdown/`、`visual/elevated/`:每路 30 张 PNG,共 90 张;`visual/synchronization.json` 含同步时间、相机标定及 UAV 标注。
25
+ - `metadata.json`、`config.json`、`state_schema.json`,以及源样本提供的 `actions.json`、`scene_metadata.json`。
26
+ - `read_sample.py` 和转换校验记录。仅需 NumPy,无需 HDF5 插件。
27
+
28
+ ```python
29
+ from read_sample import load_rss
30
+ rss_dbm = load_rss("extracted_sample", frames=slice(0, 5))
31
+ # float32 dBm;无效位置 NaN。解码必须先转有符号整数,避免 uint16 下溢。
32
+ ```
33
+
34
+ 30 帧时间通常为 0–29 s,具体以 `timestamps_s.npy` 为准;高度逐样本采样,以 `heights_m.npy` 为准。先解压后可 mmap 读取存储数组;读取完整解码 RSS 约需 720 MiB 内存,训练时可按帧/片段加载。
35
+
36
+ 所有发布样本为训练集;当前不提供独立测试集。同一物理场景的不同格式、版本或重试不能算独立场景,分组请使用 `physical_episode_group`。历史辅助样本的光学 UAV 不意味着原 RF 中有 UAV 实体;主训练与历史辅助清单分别为 `dynamic_rf_train.jsonl` 和 `legacy_aux_train.jsonl`。
37
+
38
+ 地图主要为真实建筑轮廓挤出几何,部分高度为估计;视觉为合成渲染,不是真实照片。材料参数包含合成分组与动态变化,不是逐栋实测材料。固定预算单次 RT 样本不做统计置信度验证,具体读取 `qa_protocol`、`confidence_evaluated` 和逐样本 metadata。转换校验只验证存储往返、状态及视觉同步,不声称重新验证 RT 的物理误差。
39
+
40
+
41
+ 本仓库是完整 uint16 NumPy 训练包的第二发布仓库,源仓库为 [PATIENTHZ/low-altitude-rf-worldmodel](https://huggingface.co/datasets/PATIENTHZ/low-altitude-rf-worldmodel). 两个仓库相同 record_id 的训练包保持相同 SHA256;不要跨仓库重复计数。 本仓库不包含源仓库旧版 float32 存储版本;服务器原始 RF 归档继续保留。
compact_uint16/data/dynamic_rf/data_v6/boston/boston_real_bos_i_3_000_bs_uav_actions_v2_episode_001.tar.gz ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:cfa5a033d92f36396bade848e7b29d3b414ff6024f0fe21829e13b58bcf34497
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+ size 173901181
compact_uint16/dataset_summary.json ADDED
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+ {
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+ "updated_shanghai": "2026-11-01T00:52:29.318915+08:00",
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+ "scope": "committed_on_huggingface",
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+ "repository": "DaftJun/RFWM",
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+ "complete_samples": 1,
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+ "dynamic_rf_samples": 1,
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+ "legacy_auxiliary_samples": 0,
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+ "counts_by_city": {
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+ "boston": 1
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+ },
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+ "unique_physical_groups": 1,
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+ "total_tar_bytes": 173901181,
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+ "split": "train",
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+ "rf_encoding": "uint16 centi-dBm; decode to float32 dBm with step 0.01 and offset 32768; invalid code 0",
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+ "edition": "uint16",
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+ "manifest": "compact_uint16/manifests/train.jsonl",
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+ "required_visual_views": [
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+ "bs",
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+ "topdown",
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+ "elevated"
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+ ],
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+ "contains_original_rf_archives": false,
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+ "contains_telephoto": false,
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+ "statistical_confidence_policy": "Read per-sample qa_protocol; fixed-budget samples do not evaluate confidence."
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+ }
compact_uint16/format.json ADDED
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+ {"edition": "uint16", "rss_dtype": "uint16", "physical_unit": "dBm", "step_db": 0.01, "integer_offset": 32768, "invalid_code": 0, "additional_error_relative_to_existing_training_db": 0, "archive": "tar.gz", "rss_axes": ["time", "height", "y", "x"], "array_storage_order": "F"}
compact_uint16/manifests/dynamic_rf_train.jsonl ADDED
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+ {"record_id": "data_v6/boston_real_bos_i_3_000_bs_uav_actions_v2_episode_001", "sample_id": "boston_real_bos_i_3_000_bs_uav_actions_v2_episode_001", "scene_id": "boston_real_bos_i_3_000", "source_version": "data_v6", "city": "boston", "split": "train", "source_split": "train", "physical_episode_group": "9fa4b62da5b3ca5510eebfb0de5169cb7c58dcc9c8b8ec57c9a789f95878a748", "dynamic_rf_uav_body": true, "recommended_training_use": "dynamic_rf_multimodal_world_model", "qa_protocol": "fixed_budget_single_v1", "confidence_evaluated": false, "control_schedule": "two_switches_diverse_v2", "path": "compact_uint16/data/dynamic_rf/data_v6/boston/boston_real_bos_i_3_000_bs_uav_actions_v2_episode_001.tar.gz", "sha256": "cfa5a033d92f36396bade848e7b29d3b414ff6024f0fe21829e13b58bcf34497", "bytes": 173901181, "rf_shape": [30, 24, 512, 512], "rf_dataset": null, "rf_dtype": "uint16", "rf_unit": "dBm", "invalid_value": 0, "visual_views": ["bs", "topdown", "elevated"], "rgb_image_count": 90, "packaged_shanghai": "2026-10-31T19:21:20.804891+08:00", "export_seconds": 51.388, "rf_file": "rss_dbm_uint16.npy", "rf_encoding": "uint16_centi_dbm_v1", "rf_compression": {"codec": "gzip", "level": 4, "array_order": "F"}, "decoded_invalid": "NaN", "step_db": 0.01, "integer_offset": 32768, "additional_quantization_error_db": 0.0, "clipped_voxels": 0, "source_float32_path": "data/dynamic_rf/data_v6/boston/boston_real_bos_i_3_000_bs_uav_actions_v2_episode_001.tar", "source_float32_sha256": "352a05b706efe3e0c7c8c5a816bc66cb40a3c1b8408fe3cc801344ff6d997c11", "source_float32_bytes": 414504960, "source_float32_packaged_shanghai": "2026-10-31T15:04:27.515160+08:00", "conversion_validation": {"rss_shape": [30, 24, 512, 512], "rss_dtype": "uint16", "rss_array_order": "F", "rss_all_values_exact": true, "state_arrays_exact": 43, "rgb_images": 90, "rgb_timestamps_exact": true, "numpy_directory_bytes": 432615645, "source_tar_bytes": 414504960, "conversion_and_verification_seconds": 32.306}}
compact_uint16/manifests/legacy_aux_train.jsonl ADDED
File without changes
compact_uint16/manifests/train.jsonl ADDED
@@ -0,0 +1 @@
 
 
1
+ {"record_id": "data_v6/boston_real_bos_i_3_000_bs_uav_actions_v2_episode_001", "sample_id": "boston_real_bos_i_3_000_bs_uav_actions_v2_episode_001", "scene_id": "boston_real_bos_i_3_000", "source_version": "data_v6", "city": "boston", "split": "train", "source_split": "train", "physical_episode_group": "9fa4b62da5b3ca5510eebfb0de5169cb7c58dcc9c8b8ec57c9a789f95878a748", "dynamic_rf_uav_body": true, "recommended_training_use": "dynamic_rf_multimodal_world_model", "qa_protocol": "fixed_budget_single_v1", "confidence_evaluated": false, "control_schedule": "two_switches_diverse_v2", "path": "compact_uint16/data/dynamic_rf/data_v6/boston/boston_real_bos_i_3_000_bs_uav_actions_v2_episode_001.tar.gz", "sha256": "cfa5a033d92f36396bade848e7b29d3b414ff6024f0fe21829e13b58bcf34497", "bytes": 173901181, "rf_shape": [30, 24, 512, 512], "rf_dataset": null, "rf_dtype": "uint16", "rf_unit": "dBm", "invalid_value": 0, "visual_views": ["bs", "topdown", "elevated"], "rgb_image_count": 90, "packaged_shanghai": "2026-10-31T19:21:20.804891+08:00", "export_seconds": 51.388, "rf_file": "rss_dbm_uint16.npy", "rf_encoding": "uint16_centi_dbm_v1", "rf_compression": {"codec": "gzip", "level": 4, "array_order": "F"}, "decoded_invalid": "NaN", "step_db": 0.01, "integer_offset": 32768, "additional_quantization_error_db": 0.0, "clipped_voxels": 0, "source_float32_path": "data/dynamic_rf/data_v6/boston/boston_real_bos_i_3_000_bs_uav_actions_v2_episode_001.tar", "source_float32_sha256": "352a05b706efe3e0c7c8c5a816bc66cb40a3c1b8408fe3cc801344ff6d997c11", "source_float32_bytes": 414504960, "source_float32_packaged_shanghai": "2026-10-31T15:04:27.515160+08:00", "conversion_validation": {"rss_shape": [30, 24, 512, 512], "rss_dtype": "uint16", "rss_array_order": "F", "rss_all_values_exact": true, "state_arrays_exact": 43, "rgb_images": 90, "rgb_timestamps_exact": true, "numpy_directory_bytes": 432615645, "source_tar_bytes": 414504960, "conversion_and_verification_seconds": 32.306}}