mckero
f4f6ec7db5
用户要求内置完整版模型, 不要量化版。 assets/deepcw/model.onnx: 4,354,478 bytes (int8) -> 15,139,839 bytes (fp32) sha256 ef120799457bca042d4690944f0faf93268eb4654e7f50f28784ad63bdc1fe02, 与上游 commit 8e264d2 发布的原始文件逐字节一致, 零修改。 实测验证(直接对仓库内的 asset 跑推理, 35 个场景): - 信噪比: 干净 ~ -6 dB 全部逐字符正确; -9 dB 起显著劣化 - 速度: 12-45 WPM, 8 档中 7 档零错误 (40 WPM 推理仅 167ms) - 音调: 450-1150 Hz 全窗口 6/6 零错误 - 频率漂移: +20/+60/+150/-300 Hz 全部 4/4 零错误 (卫星多普勒无忧) - QSB 衰落: 6/12 dB 无损, 20 dB 深衰落 CER 23.5% - QRM 同频干扰: 4/4 失败(会把干扰台内容一起解出), 全频段模型固有特性, 实用时依赖电台窄带 CW 滤波器缓解 - fp32 vs int8 准确率打平(5 档中 4 档完全一致); 服务器 x86 上 fp32 推理 耗时约为 int8 的一半(int8 动态量化的反量化开销在无 int8 加速指令的 CPU 上反而更慢)。手机 ARM 侧表现待装机确认。 NOTICE.md / DEEPCW.md / README.md 同步更新: 移除 int8 量化派生的记录与复现 步骤, 改为声明未修改照搬上游。 代价: APK 体积约 59MB -> 70MB, 运行内存峰值上升。此前真机闪退的根因是 R8 缺 -keep ai.onnxruntime.** 规则(已修), 与模型大小无关。
68 lines
2.9 KiB
Markdown
68 lines
2.9 KiB
Markdown
# Third-Party Notices — CW Decode Module
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## DeepCW neural CW decoding model
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The CW (Morse code) decoder in this module performs inference with a neural
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network model obtained from the DeepCW project.
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| **Component** | `src/main/assets/deepcw/model.onnx` and `model.onnx.json` |
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| **Upstream project** | DeepCW / deepcw-engine |
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| **Source repository** | https://github.com/e04/deepcw-engine |
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| **Author / copyright** | e04 |
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| **License** | GNU Affero General Public License v3.0 only (AGPL-3.0-only) |
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| **License text** | [`DeepCW-AGPL-3.0.txt`](DeepCW-AGPL-3.0.txt) |
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| **Obtained at commit** | `8e264d243bbd4467bd19f3f28292219405b47e0e` |
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| **File size** | 15,139,839 bytes |
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| **SHA-256** | `ef120799457bca042d4690944f0faf93268eb4654e7f50f28784ad63bdc1fe02` |
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| **Modifications** | None. The full fp32 model is vendored byte-for-byte as published upstream. |
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Related upstream repositories by the same author (not vendored here):
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- https://github.com/e04/web-deep-cw-decoder — reference web application
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- https://github.com/e04/HamNoise — neural noise reduction (not used)
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### License compatibility
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Look4Sat is licensed under the GNU General Public License v3.0 or later
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(GPL-3.0-or-later). The DeepCW model is licensed under AGPL-3.0-only.
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Section 13 of the GPL version 3 expressly permits combining GPL-3.0 covered
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work with AGPL-3.0 covered work; the resulting combination may be conveyed,
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with the AGPL's additional network-interaction requirement applying to the
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AGPL-covered portion. Accordingly:
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- The Look4Sat source code remains under GPL-3.0-or-later.
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- The DeepCW model remains under AGPL-3.0-only.
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- Distributions of the combined application are accompanied by complete
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corresponding source, satisfying both licenses.
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### AGPL section 13 (network interaction)
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Inference runs entirely on the local device via ONNX Runtime. The application
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does not offer the model's functionality to users interacting with it remotely
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over a network, so the additional network-source-offer requirement of AGPL-3.0
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section 13 is not triggered by this usage. The complete corresponding source
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for both the application and the vendored model remains publicly available at
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the repository hosting this file.
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### Reproducing the vendored files
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```bash
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SHA=8e264d243bbd4467bd19f3f28292219405b47e0e
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curl -sLO https://raw.githubusercontent.com/e04/deepcw-engine/$SHA/model.onnx
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curl -sLO https://raw.githubusercontent.com/e04/deepcw-engine/$SHA/model.onnx.json
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curl -sL -o DeepCW-AGPL-3.0.txt \
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https://raw.githubusercontent.com/e04/deepcw-engine/$SHA/LICENSE
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sha256sum model.onnx
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# expected: ef120799457bca042d4690944f0faf93268eb4654e7f50f28784ad63bdc1fe02
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# copy model.onnx and model.onnx.json into assets/deepcw/ unchanged
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```
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## ONNX Runtime
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Inference engine: `com.microsoft.onnxruntime:onnxruntime-android`, licensed
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under the MIT License. Consumed as a published Maven artifact; not vendored in
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this repository.
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