Add YOLOv26n RDK X5 model and quantized artifacts
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cyy_mac
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README.md
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README.md
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# YOLOv26n RDK X5 模型与量化产物
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这是基于 YOLOv26n 训练得到的检测模型，以及按 D-Robotics RDK X5 官方
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`rdk_x5` 模型仓库流程生成的 BPU 量化产物。
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官方参考：
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- <https://github.com/D-Robotics/rdk_model_zoo/tree/rdk_x5>
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- <https://developer.d-robotics.cc/rdk_doc/Algorithm_Application/model_zoo/model_zoo_intro>
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## 模型信息
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| 项目 | 内容 |
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| --- | --- |
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| 浮点模型 | `best.onnx` |
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| ONNX IR / opset | IR 6 / opset 11 |
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| 输入 | `images`, `[1, 3, 640, 640]`, RGB |
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| 类别数 | 4 |
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| 类别名称 | `QR_code`, `line`, `end`, `roadblock` |
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| 原始 ONNX 输出 | `output0`, `[1, 300, 6]` |
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| BPU 输入 | NV12, 640x640 |
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| BPU 输出 | 三尺度 `(cls, box)` 原始特征，共 6 个 NHWC 张量 |
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原始 `best.onnx` 包含 YOLOv26 的端到端后处理。为了减少 BPU 与 CPU 之间的
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切换，`x5_quantization/best_bpu.onnx` 只保留检测网络和原始检测头，移除了
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TopK、Gather、索引解码以及最终检测结果拼接。后处理在 CPU 上执行：分类
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sigmoid、置信度筛选、LTRB 解码和 NMS。
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## 目录内容
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```text
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best.onnx # 原始浮点 ONNX
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x5_quantization/
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best_bpu.onnx # 裁剪后的 BPU 友好 ONNX
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best_bpu_int8.yaml # hb_mapper 配置
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mapper_output_bpu/
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best_bpu_bayese_640x640_nv12.bin # X5 可加载模型
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*_quant_info.json # 输出量化参数
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*_quantized_model.onnx # 量化检查模型
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calibration_data/ # 50 个 RGB/CHW/float32 校准输入
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prepare_calibration.py # 生成校准输入
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extract_yolo26_bpu.py # 裁剪 YOLOv26 后处理
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postprocess_yolo26.py # CPU 后处理
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quantize_x5.sh # Docker 一键量化
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checker.log / mapper.log # checker 和 makertbin 日志
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```
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## 重新量化
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需要 Docker Desktop 和已加载的镜像：
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```text
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openexplorer/ai_toolchain_ubuntu_20_x5_cpu:v1.2.8
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```
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在本目录的上一级执行：
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```bash
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cd /Users/chenyouyuan/cyy_ws/smart_car_2026/model
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./x5_quantization/quantize_x5.sh
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```
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脚本会从 `../dataset` 的 `images/train` 和 `images/vel` 中均匀抽取 50 张图片，
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直接 resize 到 640x640，保存为 RGB、CHW、float32；`data_scale=1/255` 由
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`hb_mapper` 配置完成。量化目标为 `bayes-e`，默认 int8，编译优化等级为 O3，
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并启用 `set_Softmax_input_int8,set_Softmax_output_int8`。
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## BPU 输出与 CPU 后处理
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模型输出顺序固定为：
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```text
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cls_s8, box_s8, cls_s16, box_s16, cls_s32, box_s32
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```
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形状分别为：
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```text
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cls_s8 / box_s8 [1, 80, 80, 4]
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cls_s16 / box_s16 [1, 40, 40, 4]
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cls_s32 / box_s32 [1, 20, 20, 4]
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```
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可以直接复用 `x5_quantization/postprocess_yolo26.py`：
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```python
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from x5_quantization.postprocess_yolo26 import postprocess
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boxes, scores, class_ids = postprocess(
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[cls_s8, box_s8, cls_s16, box_s16, cls_s32, box_s32],
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classes=4,
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score_threshold=0.25,
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iou_threshold=0.7,
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)
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```
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返回的框坐标位于 640x640 模型坐标系。如果板端前处理使用 letterbox，需要
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根据实际缩放比例和 padding 将坐标映射回原始相机分辨率。
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## 量化结果
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`hb_mapper checker` 和 `hb_mapper makertbin` 均已通过。编译器对 X5 的估计延迟
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为 `8.913 ms`，最终 `.bin` 大小约 `3.7 MB`。输出余弦相似度如下：
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| 输出 | Cosine Similarity |
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| --- | ---: |
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| `cls_s8` | 0.985422 |
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| `box_s8` | 0.989597 |
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| `cls_s16` | 0.989395 |
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| `box_s16` | 0.993338 |
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| `cls_s32` | 0.998478 |
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| `box_s32` | 0.999024 |
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上述延迟是 Docker 中 OpenExplore 编译器的估计值，不是 X5 实板实测值。部署前
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应在板端用 `hrt_model_exec model_info` 检查模型元数据，再用真实相机输入验证
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检测精度和端到端延迟。
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x5_quantization/README.md
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# RDK X5 YOLOv26n 量化
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输入模型为 `../best.onnx`，固定输入 `images [1,3,640,640]`，opset 11。流程参考
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`D-Robotics/rdk_model_zoo` 的 `rdk_x5` 分支中 `ultralytics_yolo26` 示例：
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- `extract_yolo26_bpu.py` 移除 TopK、Gather 和最终检测结果组装，只输出三尺度
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`(cls, box)` 原始特征，输出布局为 NHWC。
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- 校准数据从 `../../dataset` 均匀抽取 50 张图片，直接 resize 到 640x640，保存
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RGB/CHW/float32；`data_scale=1/255` 由量化配置完成。
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- 板端输入为 NV12，量化默认 int8，并使用官方 Softmax int8 优化项。
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执行 `./quantize_x5.sh` 会在 Docker 镜像
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`openexplorer/ai_toolchain_ubuntu_20_x5_cpu:v1.2.8` 中依次运行 `hb_mapper checker`
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和 `hb_mapper makertbin`，产物为
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`mapper_output_bpu/best_bpu_bayese_640x640_nv12.bin`。部署端需要按三尺度输出完成
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sigmoid、LTRB 解码、阈值筛选和 NMS；可直接复用 `postprocess_yolo26.py`。
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板端输入是 NV12，模型输出顺序为 `cls_s8, box_s8, cls_s16, box_s16,
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cls_s32, box_s32`，输出张量布局是 NHWC。`.bin` 的 `model_info` 应以板端
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`hrt_model_exec` 实际显示的名称和量化参数为准。
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x5_quantization/best_bpu_int8.yaml
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model_parameters:
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onnx_model: "./best_bpu.onnx"
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march: "bayes-e"
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layer_out_dump: false
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working_dir: "mapper_output_bpu"
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output_model_file_prefix: "best_bpu_bayese_640x640_nv12"
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input_parameters:
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input_name: "images"
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input_type_rt: "nv12"
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input_type_train: "rgb"
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input_layout_train: "NCHW"
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norm_type: "data_scale"
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scale_value: 0.003921568627451
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calibration_parameters:
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cal_data_dir: "./calibration_data"
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cal_data_type: "float32"
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calibration_type: "default"
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optimization: "set_Softmax_input_int8,set_Softmax_output_int8"
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compiler_parameters:
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jobs: 8
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compile_mode: "latency"
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debug: true
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optimize_level: "O3"
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images/train/00246cf2-46a7-4a4e-8bc8-8e7f2317ad09.png
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images/train/5e5854dc-9716-4579-ab99-5f78383de59d_aug1.jpg
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|
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|
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images/train/7dd1d683-bbbb-4783-8700-94634f64a1fa_aug1.jpg
|
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|
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|
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images/train/8cf0b48c-52f0-4b02-88fe-fd26c0063565.png
|
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images/train/921171d2-9791-481a-a3b8-9c93fcb0f479_aug1.jpg
|
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images/train/964a3741-0a41-4a04-82f3-f74cc558a223_aug2.jpg
|
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images/train/9bd59151-88c0-4f4f-bcd8-a6c823248424_aug2.jpg
|
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|
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images/train/a56563df-3e99-45fb-9f29-5f3ec2062da4_aug2.jpg
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|
images/train/aaefdc2e-28cd-4769-96bd-4f7d43d58032.png
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images/train/b0473ba5-63d0-4ca1-a1b3-cd3a0d85cbce.png
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images/train/b62abb00-d665-4053-8639-97cf3243cf0d_aug1.jpg
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images/train/bb6936bc-cc3a-4bb1-9a2c-61ef054a8866_aug4.jpg
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images/train/c0c8f3c3-fa59-430a-819f-8da63d470d83.jpg
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images/train/c6a9a9fd-242d-420f-91bc-79419f83604a_aug2.jpg
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images/train/cc7d55cb-6fb7-4ed8-a524-b022c671454e_aug1.jpg
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images/train/d1b89258-c545-4d4a-bd32-60e6f5d7131a_aug1.jpg
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images/train/d6601c84-b38a-46df-94c9-3e67ae4c0b7b_aug2.jpg
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images/train/dbf7ba4e-24fc-45dd-b655-144bd4ccbe71_aug1.jpg
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images/train/e0f3883b-2301-4b95-b975-9fd4a1cfa0be.png
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images/train/e605a9e1-5ae1-4da4-8326-9050c21966c6_aug2.jpg
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images/train/eb08a24f-7ead-4fae-9f4c-717cd54e4b8f_aug3.jpg
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images/train/f040251a-9a78-4536-9439-3803759952e5.png
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images/train/f5c6161c-9ea7-432a-9b44-82678c19ee0e_aug2.jpg
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||||||
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images/train/fb30aaaf-3009-4089-98b4-088e020ae1bb_aug2.jpg
|
||||||
|
images/vel/02f61ef1-3c40-446e-ac2d-fbc7e4ccf605_aug1.jpg
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images/vel/0dc056fb-8373-4834-8630-bc0057a1d24c_aug1.jpg
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|
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|
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images/vel/3b347f91-60b4-4d1a-b187-50a9f106f072_aug2.jpg
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|
images/vel/4a674364-26ba-43c8-9448-bcd2bdd68275_aug2.jpg
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|
images/vel/4fc2dc2f-85db-4df0-a4a6-e18f15a856dd.png
|
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|
images/vel/fb5adb2c-e598-4ae4-bbf1-8e46a10158c3_aug4.jpg
|
||||||
343
x5_quantization/checker.log
Normal file
343
x5_quantization/checker.log
Normal file
@@ -0,0 +1,343 @@
|
|||||||
|
2026-08-07 10:39:43,366 file: tool_utils.py func: tool_utils line No: 77 log will be stored in /workspace/smart_car_2026/model/hb_mapper_checker.log
|
||||||
|
2026-08-07 10:39:43,367 file: hb_mapper.py func: hb_mapper line No: 72 Start hb_mapper....
|
||||||
|
2026-08-07 10:39:43,367 file: hb_mapper.py func: hb_mapper line No: 73 hbdk version 3.49.15
|
||||||
|
2026-08-07 10:39:43,368 file: hb_mapper.py func: hb_mapper line No: 74 horizon_nn version 1.1.0
|
||||||
|
2026-08-07 10:39:43,368 file: hb_mapper.py func: hb_mapper line No: 75 hb_mapper version 1.24.3
|
||||||
|
2026-08-07 10:39:43,386 file: onnx_parser.py func: onnx_parser line No: 39 Model input names: ['images']
|
||||||
|
2026-08-07 10:39:43,388 file: hb_mapper_checker.py func: hb_mapper_checker line No: 106 Model type: onnx
|
||||||
|
2026-08-07 10:39:43,388 file: hb_mapper_checker.py func: hb_mapper_checker line No: 107 march: bayes-e
|
||||||
|
2026-08-07 10:39:43,388 file: hb_mapper_checker.py func: hb_mapper_checker line No: 112 input names ['images']
|
||||||
|
2026-08-07 10:39:43,389 file: hb_mapper_checker.py func: hb_mapper_checker line No: 113 input shapes {'images': [1, 3, 640, 640]}
|
||||||
|
2026-08-07 10:39:43,396 file: onnx_parser.py func: onnx_parser line No: 39 Model input names: ['images']
|
||||||
|
2026-08-07 10:39:43,397 file: hb_mapper_checker.py func: hb_mapper_checker line No: 119 Begin model checking....
|
||||||
|
2026-08-07 10:39:43,409 file: model_builder.py func: model_builder line No: 35 Start to Horizon NN Model Convert.
|
||||||
|
2026-08-07 10:39:43,430 file: model_debugger.py func: model_debugger line No: 67 Loading horizon_nn debug methods:set()
|
||||||
|
2026-08-07 10:39:43,431 file: quantization_config.py func: quantization_config line No: 305 The activation calibration parameters:
|
||||||
|
calibration_type: fixed
|
||||||
|
2026-08-07 10:39:43,431 file: model_builder.py func: model_builder line No: 197 The specified model compilation architecture: bayes-e.
|
||||||
|
2026-08-07 10:39:43,431 file: model_builder.py func: model_builder line No: 207 The specified model compilation optimization parameters: [].
|
||||||
|
2026-08-07 10:39:43,432 file: model_builder.py func: model_builder line No: 35 Start to prepare the onnx model.
|
||||||
|
2026-08-07 10:39:43,468 file: prepare.py func: prepare line No: 106 Input ONNX Model Information:
|
||||||
|
ONNX IR version: 6
|
||||||
|
Opset version: ['ai.onnx v11', 'horizon v1']
|
||||||
|
Producer: onnx.utils.extract_model
|
||||||
|
Domain: None
|
||||||
|
Version: None
|
||||||
|
Graph input:
|
||||||
|
images: shape=[1, 3, 640, 640], dtype=FLOAT32
|
||||||
|
Graph output:
|
||||||
|
cls_s8: shape=[1, 80, 80, 4], dtype=FLOAT32
|
||||||
|
box_s8: shape=[1, 80, 80, 4], dtype=FLOAT32
|
||||||
|
cls_s16: shape=[1, 40, 40, 4], dtype=FLOAT32
|
||||||
|
box_s16: shape=[1, 40, 40, 4], dtype=FLOAT32
|
||||||
|
cls_s32: shape=[1, 20, 20, 4], dtype=FLOAT32
|
||||||
|
box_s32: shape=[1, 20, 20, 4], dtype=FLOAT32
|
||||||
|
2026-08-07 10:39:43,655 file: model_builder.py func: model_builder line No: 38 End to prepare the onnx model.
|
||||||
|
2026-08-07 10:39:43,689 file: model_builder.py func: model_builder line No: 265 Saving model to: ./.hb_check/original_float_model.onnx.
|
||||||
|
2026-08-07 10:39:43,689 file: model_builder.py func: model_builder line No: 35 Start to optimize the onnx model.
|
||||||
|
2026-08-07 10:39:43,863 file: constant_folding.py func: constant_folding line No: 66 Summary info for constant_folding:
|
||||||
|
2026-08-07 10:39:43,863 file: constant_folding.py func: constant_folding line No: 67 After constant_folding, the number of nodes has changed from 355 to 355.
|
||||||
|
2026-08-07 10:39:43,864 file: constant_folding.py func: constant_folding line No: 71 After constant_folding, the number of parameters has changed from 2375629 to 2375629.
|
||||||
|
2026-08-07 10:39:43,864 file: constant_folding.py func: constant_folding line No: 76 Detailed info for constant_folding:
|
||||||
|
2026-08-07 10:39:43,864 file: constant_folding.py func: constant_folding line No: 88
|
||||||
|
2026-08-07 10:39:44,358 file: model_builder.py func: model_builder line No: 38 End to optimize the onnx model.
|
||||||
|
2026-08-07 10:39:44,389 file: model_builder.py func: model_builder line No: 265 Saving model to: ./.hb_check/optimized_float_model.onnx.
|
||||||
|
2026-08-07 10:39:44,389 file: model_builder.py func: model_builder line No: 35 Start to calibrate the model.
|
||||||
|
2026-08-07 10:39:44,681 file: calibration_data_set.py func: calibration_data_set line No: 111 input name: images, number_of_samples: 1
|
||||||
|
2026-08-07 10:39:44,681 file: calibration_data_set.py func: calibration_data_set line No: 123 There are 1 samples in the data set.
|
||||||
|
2026-08-07 10:39:44,682 file: fixed_calibrater.py func: fixed_calibrater line No: 31 Run calibration model with fixed thresholds method.
|
||||||
|
2026-08-07 10:39:45,210 file: model_builder.py func: model_builder line No: 38 End to calibrate the model.
|
||||||
|
2026-08-07 10:39:45,332 file: model_builder.py func: model_builder line No: 265 Saving model to: ./.hb_check/calibrated_model.onnx.
|
||||||
|
2026-08-07 10:39:45,333 file: model_builder.py func: model_builder line No: 35 Start to quantize the model.
|
||||||
|
2026-08-07 10:39:47,542 file: constant_folding.py func: constant_folding line No: 66 Summary info for constant_folding:
|
||||||
|
2026-08-07 10:39:47,542 file: constant_folding.py func: constant_folding line No: 67 After constant_folding, the number of nodes has changed from 280 to 280.
|
||||||
|
2026-08-07 10:39:47,543 file: constant_folding.py func: constant_folding line No: 71 After constant_folding, the number of parameters has changed from 2406337 to 2406337.
|
||||||
|
2026-08-07 10:39:47,543 file: constant_folding.py func: constant_folding line No: 76 Detailed info for constant_folding:
|
||||||
|
2026-08-07 10:39:47,543 file: constant_folding.py func: constant_folding line No: 88
|
||||||
|
2026-08-07 10:39:47,634 file: model_builder.py func: model_builder line No: 38 End to quantize the model.
|
||||||
|
2026-08-07 10:39:47,729 file: model_builder.py func: model_builder line No: 265 Saving model to: ./.hb_check/quantized_model.onnx.
|
||||||
|
2026-08-07 10:39:47,729 file: model_builder.py func: model_builder line No: 35 Start to compile the model with march bayes-e.
|
||||||
|
2026-08-07 10:39:48,338 file: hybrid_build.py func: hybrid_build line No: 111 Compile submodel: Extracted from {main_graph}_subgraph_0
|
||||||
|
2026-08-07 10:39:48,363 file: hbdk_cc.py func: hbdk_cc line No: 126 hbdk-cc parameters:['--input-layout', 'NHWC', '--output-layout', 'NHWC']
|
||||||
|
2026-08-07 10:39:48,363 file: hbdk_cc.py func: hbdk_cc line No: 127 hbdk-cc command used:hbdk-cc -f hbir -m /tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_0.hbir -o /tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_0.hbm --march bayes-e --progressbar --input-layout NHWC --output-layout NHWC
|
||||||
|
2026-08-07 10:39:49,198 file: tool_utils.py func: tool_utils line No: 326 consumed time 0.65736
|
||||||
|
2026-08-07 10:39:49,411 file: tool_utils.py func: tool_utils line No: 326 FPS=52.45, latency = 19064.1 us, DDR = 122035200 bytes (see ./.hb_check/Extracted from {main_graph}_subgraph_0.html)
|
||||||
|
2026-08-07 10:39:49,414 file: hybrid_build.py func: hybrid_build line No: 111 Compile submodel: Extracted from {main_graph}_subgraph_1
|
||||||
|
2026-08-07 10:39:49,431 file: hbdk_cc.py func: hbdk_cc line No: 126 hbdk-cc parameters:['--input-layout', 'NHWC', '--output-layout', 'NHWC']
|
||||||
|
2026-08-07 10:39:49,431 file: hbdk_cc.py func: hbdk_cc line No: 127 hbdk-cc command used:hbdk-cc -f hbir -m /tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_1.hbir -o /tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_1.hbm --march bayes-e --progressbar --input-layout NHWC --output-layout NHWC
|
||||||
|
2026-08-07 10:39:50,353 file: tool_utils.py func: tool_utils line No: 326 consumed time 0.755009
|
||||||
|
2026-08-07 10:39:50,544 file: tool_utils.py func: tool_utils line No: 326 FPS=45.81, latency = 21827.8 us, DDR = 138583616 bytes (see ./.hb_check/Extracted from {main_graph}_subgraph_1.html)
|
||||||
|
2026-08-07 10:39:50,549 file: hybrid_build.py func: hybrid_build line No: 111 Compile submodel: Extracted from {main_graph}_subgraph_2
|
||||||
|
2026-08-07 10:39:50,556 file: hbdk_cc.py func: hbdk_cc line No: 126 hbdk-cc parameters:['--input-layout', 'NHWC', '--output-layout', 'NHWC']
|
||||||
|
2026-08-07 10:39:50,557 file: hbdk_cc.py func: hbdk_cc line No: 127 hbdk-cc command used:hbdk-cc -f hbir -m /tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_2.hbir -o /tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_2.hbm --march bayes-e --progressbar --input-layout NHWC --output-layout NHWC
|
||||||
|
2026-08-07 10:39:51,107 file: tool_utils.py func: tool_utils line No: 326 consumed time 0.387866
|
||||||
|
2026-08-07 10:39:51,284 file: tool_utils.py func: tool_utils line No: 326 FPS=142.7, latency = 7007.7 us, DDR = 44277504 bytes (see ./.hb_check/Extracted from {main_graph}_subgraph_2.html)
|
||||||
|
2026-08-07 10:39:51,550 file: model_builder.py func: model_builder line No: 38 End to compile the model with march bayes-e.
|
||||||
|
2026-08-07 10:39:51,564 file: print_info_dict.py func: print_info_dict line No: 72 The main quantized node information:
|
||||||
|
======================================================================================================================================
|
||||||
|
Node ON Subgraph Type Cosine Similarity Threshold DataType
|
||||||
|
--------------------------------------------------------------------------------------------------------------------------------------
|
||||||
|
/model.0/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.0/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.1/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.1/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.2/cv1/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.2/cv1/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.2/Split BPU id(0) Split -- 1.0 int8
|
||||||
|
/model.2/m.0/cv1/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.2/m.0/cv1/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.2/m.0/cv2/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.2/m.0/cv2/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.2/m.0/Add BPU id(0) HzSElementwiseAdd -- 1.0 int8
|
||||||
|
/model.2/Concat BPU id(0) Concat -- 1.0 int8
|
||||||
|
/model.2/cv2/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.2/cv2/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.3/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.3/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.4/cv1/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.4/cv1/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.4/Split BPU id(0) Split -- 1.0 int8
|
||||||
|
/model.4/m.0/cv1/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.4/m.0/cv1/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.4/m.0/cv2/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.4/m.0/cv2/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.4/m.0/Add BPU id(0) HzSElementwiseAdd -- 1.0 int8
|
||||||
|
/model.4/Concat BPU id(0) Concat -- 1.0 int8
|
||||||
|
/model.4/cv2/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.4/cv2/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.5/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.5/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.6/cv1/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.6/cv1/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.6/Split BPU id(0) Split -- 1.0 int8
|
||||||
|
/model.6/m.0/cv1/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.6/m.0/cv2/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.6/m.0/cv1/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.6/m.0/cv2/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.6/m.0/m/m.0/cv1/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.6/m.0/m/m.0/cv1/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.6/m.0/m/m.0/cv2/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.6/m.0/m/m.0/cv2/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.6/m.0/m/m.0/Add BPU id(0) HzSElementwiseAdd -- 1.0 int8
|
||||||
|
/model.6/m.0/m/m.1/cv1/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.6/m.0/m/m.1/cv1/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.6/m.0/m/m.1/cv2/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.6/m.0/m/m.1/cv2/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.6/m.0/m/m.1/Add BPU id(0) HzSElementwiseAdd -- 1.0 int8
|
||||||
|
/model.6/m.0/Concat BPU id(0) Concat -- 1.0 int8
|
||||||
|
/model.6/m.0/cv3/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.6/m.0/cv3/act/Mul BPU id(0) HzLut -- 1.0 int8
|
||||||
|
/model.6/Concat BPU id(0) Concat -- 1.0 int8
|
||||||
|
/model.6/cv2/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
|
||||||
|
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/model.10/m/m.0/attn/qkv/conv/Conv BPU id(0) HzSQuantizedConv -- 1.0 int8
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/model.10/m/m.0/attn/Reshape BPU id(0) Reshape -- 1.0 int8
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/model.10/m/m.0/attn/MatMul BPU id(0) HzSQuantizedMatmul -- 1.0 int8
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/model.10/m/m.0/attn/Softmax CPU -- Softmax -- -- float
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/model.10/m/m.0/attn/Transpose_1 BPU id(1) Transpose -- -- int8
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/model.10/m/m.0/attn/pe/conv/Conv BPU id(1) HzSQuantizedConv -- 1.0 int8
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/model.10/m/m.0/attn/proj/conv/Conv BPU id(1) HzSQuantizedConv -- 1.0 int8
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/model.10/m/m.0/ffn/ffn.0/act/Mul BPU id(1) HzLut -- 1.0 int8
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/model.10/m/m.0/ffn/ffn.1/conv/Conv BPU id(1) HzSQuantizedConv -- 1.0 int8
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/model.10/Concat BPU id(1) Concat -- 1.0 int8
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/model.10/cv2/conv/Conv BPU id(1) HzSQuantizedConv -- 1.0 int8
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/model.10/cv2/act/Mul BPU id(1) HzLut -- 1.0 int8
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/model.12/Concat BPU id(1) Concat -- 1.0 int8
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/model.20/act/Mul BPU id(1) HzLut -- 1.0 int8
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||||||
|
/model.22/m.0/m.0.1/attn/Transpose BPU id(1) Transpose -- 1.0 int8
|
||||||
|
/model.22/m.0/m.0.1/attn/MatMul BPU id(1) HzSQuantizedMatmul -- 1.0 int8
|
||||||
|
/model.22/m.0/m.0.1/attn/Softmax CPU -- Softmax -- -- float
|
||||||
|
/model.22/m.0/m.0.1/attn/Transpose_1 BPU id(2) Transpose -- -- int8
|
||||||
|
/model.22/m.0/m.0.1/attn/MatMul_1 BPU id(2) HzSQuantizedMatmul -- 1.0 int8
|
||||||
|
/model.22/m.0/m.0.1/attn/Reshape_1 BPU id(2) Reshape -- 1.0 int8
|
||||||
|
/model.22/m.0/m.0.1/attn/pe/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.22/m.0/m.0.1/attn/proj/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.22/m.0/m.0.1/ffn/ffn.0/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.22/m.0/m.0.1/ffn/ffn.0/act/Mul BPU id(2) HzLut -- 1.0 int8
|
||||||
|
/model.22/m.0/m.0.1/ffn/ffn.1/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.22/Concat BPU id(2) Concat -- 1.0 int8
|
||||||
|
/model.22/cv2/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.22/cv2/act/Mul BPU id(2) HzLut -- 1.0 int8
|
||||||
|
/model.23/one2one_cv2.2/one2one_cv2.2.0/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
...3.2/one2one_cv3.2.0/one2one_cv3.2.0.0/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.23/one2one_cv2.2/one2one_cv2.2.0/act/Mul BPU id(2) HzLut -- 1.0 int8
|
||||||
|
...cv3.2/one2one_cv3.2.0/one2one_cv3.2.0.0/act/Mul BPU id(2) HzLut -- 1.0 int8
|
||||||
|
/model.23/one2one_cv2.2/one2one_cv2.2.1/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
...3.2/one2one_cv3.2.0/one2one_cv3.2.0.1/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
/model.23/one2one_cv2.2/one2one_cv2.2.1/act/Mul BPU id(2) HzLut -- 1.0 int8
|
||||||
|
...cv3.2/one2one_cv3.2.0/one2one_cv3.2.0.1/act/Mul BPU id(2) HzLut -- 1.0 int8
|
||||||
|
/model.23/one2one_cv2.2/one2one_cv2.2.2/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
...3.2/one2one_cv3.2.1/one2one_cv3.2.1.0/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
...cv3.2/one2one_cv3.2.1/one2one_cv3.2.1.0/act/Mul BPU id(2) HzLut -- 1.0 int8
|
||||||
|
...3.2/one2one_cv3.2.1/one2one_cv3.2.1.1/conv/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
...cv3.2/one2one_cv3.2.1/one2one_cv3.2.1.1/act/Mul BPU id(2) HzLut -- 1.0 int8
|
||||||
|
/model.23/one2one_cv3.2/one2one_cv3.2.2/Conv BPU id(2) HzSQuantizedConv -- 1.0 int8
|
||||||
|
2026-08-07 10:39:51,565 file: print_info_dict.py func: print_info_dict line No: 72 The quantized model output:
|
||||||
|
============
|
||||||
|
Output
|
||||||
|
------------
|
||||||
|
2026-08-07 10:39:51,573 file: model_builder.py func: model_builder line No: 38 End to Horizon NN Model Convert.
|
||||||
|
2026-08-07 10:39:51,574 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4326 ONNX model output num : 6
|
||||||
|
2026-08-07 10:39:51,577 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4060 model_deps_info: {'hb_mapper_version': '1.24.3'}
|
||||||
|
2026-08-07 10:39:51,580 file: hb_mapper_checker.py func: hb_mapper_checker line No: 170 End model checking....
|
||||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1,213 @@
|
|||||||
|
{
|
||||||
|
"summary": {
|
||||||
|
"BPU OPs per frame (effective)": 2940160000,
|
||||||
|
"BPU OPs per run (effective)": 2940160000,
|
||||||
|
"BPU PE number": 1,
|
||||||
|
"BPU core number": 1,
|
||||||
|
"BPU march": "B25E",
|
||||||
|
"DDR bytes per frame": 122035200,
|
||||||
|
"DDR bytes per run": 122035200,
|
||||||
|
"DDR bytes per second": 6401297850,
|
||||||
|
"DDR megabytes per frame": 116.382,
|
||||||
|
"DDR megabytes per run": 116.382,
|
||||||
|
"DDR megabytes per second": 6104.8,
|
||||||
|
"FPS": 52.45,
|
||||||
|
"HBDK version": "3.49.15",
|
||||||
|
"compiling options": "-f hbir -m /tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_0.hbir -o /tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_0.hbm --march bayes-e --progressbar --input-layout NHWC --output-layout NHWC",
|
||||||
|
"frame per run": 1,
|
||||||
|
"frame per second": 52.45,
|
||||||
|
"input features": [
|
||||||
|
[
|
||||||
|
"input name",
|
||||||
|
"input size"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"images_calibrated_quantized",
|
||||||
|
"1x3x640x640"
|
||||||
|
]
|
||||||
|
],
|
||||||
|
"interval computing unit utilization": [
|
||||||
|
0.206,
|
||||||
|
0.136,
|
||||||
|
0.068,
|
||||||
|
0.095,
|
||||||
|
0.104,
|
||||||
|
0.052,
|
||||||
|
0.167,
|
||||||
|
0.104,
|
||||||
|
0.082,
|
||||||
|
0.094,
|
||||||
|
0.052,
|
||||||
|
0.116,
|
||||||
|
0.091,
|
||||||
|
0.078,
|
||||||
|
0.139,
|
||||||
|
0.247,
|
||||||
|
0.104,
|
||||||
|
0.142,
|
||||||
|
0.077,
|
||||||
|
0.194,
|
||||||
|
0.256,
|
||||||
|
0.115,
|
||||||
|
0.256,
|
||||||
|
0.164,
|
||||||
|
0.162,
|
||||||
|
0.161,
|
||||||
|
0.072,
|
||||||
|
0.12,
|
||||||
|
0.106,
|
||||||
|
0.147,
|
||||||
|
0.098,
|
||||||
|
0.086,
|
||||||
|
0.109,
|
||||||
|
0.27,
|
||||||
|
0.17,
|
||||||
|
0.084,
|
||||||
|
0.031,
|
||||||
|
0.084,
|
||||||
|
0.021
|
||||||
|
],
|
||||||
|
"interval computing units utilization": [
|
||||||
|
0.206,
|
||||||
|
0.136,
|
||||||
|
0.068,
|
||||||
|
0.095,
|
||||||
|
0.104,
|
||||||
|
0.052,
|
||||||
|
0.167,
|
||||||
|
0.104,
|
||||||
|
0.082,
|
||||||
|
0.094,
|
||||||
|
0.052,
|
||||||
|
0.116,
|
||||||
|
0.091,
|
||||||
|
0.078,
|
||||||
|
0.139,
|
||||||
|
0.247,
|
||||||
|
0.104,
|
||||||
|
0.142,
|
||||||
|
0.077,
|
||||||
|
0.194,
|
||||||
|
0.256,
|
||||||
|
0.115,
|
||||||
|
0.256,
|
||||||
|
0.164,
|
||||||
|
0.162,
|
||||||
|
0.161,
|
||||||
|
0.072,
|
||||||
|
0.12,
|
||||||
|
0.106,
|
||||||
|
0.147,
|
||||||
|
0.098,
|
||||||
|
0.086,
|
||||||
|
0.109,
|
||||||
|
0.27,
|
||||||
|
0.17,
|
||||||
|
0.084,
|
||||||
|
0.031,
|
||||||
|
0.084,
|
||||||
|
0.021
|
||||||
|
],
|
||||||
|
"interval loading bandwidth (megabytes/s)": [
|
||||||
|
1567,
|
||||||
|
2772,
|
||||||
|
3728,
|
||||||
|
3375,
|
||||||
|
3253,
|
||||||
|
3419,
|
||||||
|
3569,
|
||||||
|
3332,
|
||||||
|
3128,
|
||||||
|
3129,
|
||||||
|
3537,
|
||||||
|
3324,
|
||||||
|
3110,
|
||||||
|
3711,
|
||||||
|
3551,
|
||||||
|
2800,
|
||||||
|
2935,
|
||||||
|
3320,
|
||||||
|
3151,
|
||||||
|
3267,
|
||||||
|
2933,
|
||||||
|
2795,
|
||||||
|
3095,
|
||||||
|
3004,
|
||||||
|
3036,
|
||||||
|
3189,
|
||||||
|
3001,
|
||||||
|
3210,
|
||||||
|
3715,
|
||||||
|
2631,
|
||||||
|
1875,
|
||||||
|
2797,
|
||||||
|
3808,
|
||||||
|
4172,
|
||||||
|
3242,
|
||||||
|
2191,
|
||||||
|
2842,
|
||||||
|
3508,
|
||||||
|
1912
|
||||||
|
],
|
||||||
|
"interval number": 39,
|
||||||
|
"interval storing bandwidth (megabytes/s)": [
|
||||||
|
4079,
|
||||||
|
3124,
|
||||||
|
2647,
|
||||||
|
3125,
|
||||||
|
3125,
|
||||||
|
3125,
|
||||||
|
2729,
|
||||||
|
2767,
|
||||||
|
3276,
|
||||||
|
3279,
|
||||||
|
2977,
|
||||||
|
3140,
|
||||||
|
3215,
|
||||||
|
2768,
|
||||||
|
2770,
|
||||||
|
2887,
|
||||||
|
2803,
|
||||||
|
2794,
|
||||||
|
3141,
|
||||||
|
2869,
|
||||||
|
2425,
|
||||||
|
2636,
|
||||||
|
2421,
|
||||||
|
2226,
|
||||||
|
2437,
|
||||||
|
2483,
|
||||||
|
3134,
|
||||||
|
3174,
|
||||||
|
2502,
|
||||||
|
3435,
|
||||||
|
4276,
|
||||||
|
3652,
|
||||||
|
2602,
|
||||||
|
1582,
|
||||||
|
2150,
|
||||||
|
3870,
|
||||||
|
3841,
|
||||||
|
3115,
|
||||||
|
1647
|
||||||
|
],
|
||||||
|
"interval time (ms)": 0.5,
|
||||||
|
"latency (ms)": 19.06,
|
||||||
|
"latency (ms) by segments": [
|
||||||
|
19.064
|
||||||
|
],
|
||||||
|
"latency (us)": 19064.1,
|
||||||
|
"loaded bytes per frame": 63139840,
|
||||||
|
"loaded bytes per run": 63139840,
|
||||||
|
"model json CRC": "4bd1303b",
|
||||||
|
"model json file": "/tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_0.hbir",
|
||||||
|
"model name": "Extracted from {main_graph}_subgraph_0",
|
||||||
|
"model param CRC": "00000000",
|
||||||
|
"multicore sync time (ms)": 0.0,
|
||||||
|
"run per second": 52.45,
|
||||||
|
"runtime version": "3.15.55.0",
|
||||||
|
"stored bytes per frame": 58895360,
|
||||||
|
"stored bytes per run": 58895360,
|
||||||
|
"worst FPS": 52.45
|
||||||
|
}
|
||||||
|
}
|
||||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1,257 @@
|
|||||||
|
{
|
||||||
|
"summary": {
|
||||||
|
"BPU OPs per frame (effective)": 2136627200,
|
||||||
|
"BPU OPs per run (effective)": 2136627200,
|
||||||
|
"BPU PE number": 1,
|
||||||
|
"BPU core number": 1,
|
||||||
|
"BPU march": "B25E",
|
||||||
|
"DDR bytes per frame": 138583616,
|
||||||
|
"DDR bytes per run": 138583616,
|
||||||
|
"DDR bytes per second": 6348938021,
|
||||||
|
"DDR megabytes per frame": 132.164,
|
||||||
|
"DDR megabytes per run": 132.164,
|
||||||
|
"DDR megabytes per second": 6054.8,
|
||||||
|
"FPS": 45.81,
|
||||||
|
"HBDK version": "3.49.15",
|
||||||
|
"compiling options": "-f hbir -m /tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_1.hbir -o /tmp/tmpo3cnuwll/Extracted from {main_graph}_subgraph_1.hbm --march bayes-e --progressbar --input-layout NHWC --output-layout NHWC",
|
||||||
|
"frame per run": 1,
|
||||||
|
"frame per second": 45.81,
|
||||||
|
"input features": [
|
||||||
|
[
|
||||||
|
"input name",
|
||||||
|
"input size"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.10/m/m.0/attn/Transpose_1_output_0_calibrated_quantized",
|
||||||
|
"1x2x400x400"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.10/m/m.0/attn/Split_nhwc2nchw_transposed_output2",
|
||||||
|
"1x2x64x400"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.10/m/m.0/attn/pe/conv/Conv_nchw2nhwc_transposed_input0",
|
||||||
|
"1x20x20x128"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.10/Split_output_1_quantized",
|
||||||
|
"1x20x20x128"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.10/Split_output_0_quantized",
|
||||||
|
"1x20x20x128"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.6/cv2/act/Mul_output_0_quantized",
|
||||||
|
"1x40x40x128"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.4/cv2/act/Mul_output_0_quantized",
|
||||||
|
"1x80x80x128"
|
||||||
|
]
|
||||||
|
],
|
||||||
|
"interval computing unit utilization": [
|
||||||
|
0.101,
|
||||||
|
0.101,
|
||||||
|
0.199,
|
||||||
|
0.154,
|
||||||
|
0.112,
|
||||||
|
0.108,
|
||||||
|
0.101,
|
||||||
|
0.079,
|
||||||
|
0.106,
|
||||||
|
0.185,
|
||||||
|
0.096,
|
||||||
|
0.355,
|
||||||
|
0.093,
|
||||||
|
0.139,
|
||||||
|
0.152,
|
||||||
|
0.124,
|
||||||
|
0.185,
|
||||||
|
0.039,
|
||||||
|
0.128,
|
||||||
|
0.103,
|
||||||
|
0.117,
|
||||||
|
0.112,
|
||||||
|
0.085,
|
||||||
|
0.148,
|
||||||
|
0.134,
|
||||||
|
0.137,
|
||||||
|
0.16,
|
||||||
|
0.172,
|
||||||
|
0.132,
|
||||||
|
0.178,
|
||||||
|
0.172,
|
||||||
|
0.155,
|
||||||
|
0.041,
|
||||||
|
0.159,
|
||||||
|
0.132,
|
||||||
|
0.102,
|
||||||
|
0.108,
|
||||||
|
0.106,
|
||||||
|
0.092,
|
||||||
|
0.258,
|
||||||
|
0.211,
|
||||||
|
0.005,
|
||||||
|
0.068,
|
||||||
|
0.063
|
||||||
|
],
|
||||||
|
"interval computing units utilization": [
|
||||||
|
0.101,
|
||||||
|
0.101,
|
||||||
|
0.199,
|
||||||
|
0.154,
|
||||||
|
0.112,
|
||||||
|
0.108,
|
||||||
|
0.101,
|
||||||
|
0.079,
|
||||||
|
0.106,
|
||||||
|
0.185,
|
||||||
|
0.096,
|
||||||
|
0.355,
|
||||||
|
0.093,
|
||||||
|
0.139,
|
||||||
|
0.152,
|
||||||
|
0.124,
|
||||||
|
0.185,
|
||||||
|
0.039,
|
||||||
|
0.128,
|
||||||
|
0.103,
|
||||||
|
0.117,
|
||||||
|
0.112,
|
||||||
|
0.085,
|
||||||
|
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||||||
983
x5_quantization/checker_output/main_graph_subgraph_1.html
Normal file
983
x5_quantization/checker_output/main_graph_subgraph_1.html
Normal file
File diff suppressed because one or more lines are too long
273
x5_quantization/checker_output/main_graph_subgraph_1.json
Normal file
273
x5_quantization/checker_output/main_graph_subgraph_1.json
Normal file
@@ -0,0 +1,273 @@
|
|||||||
|
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|
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|
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|
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|
||||||
|
}
|
||||||
983
x5_quantization/checker_output/main_graph_subgraph_2.html
Normal file
983
x5_quantization/checker_output/main_graph_subgraph_2.html
Normal file
File diff suppressed because one or more lines are too long
191
x5_quantization/checker_output/main_graph_subgraph_2.json
Normal file
191
x5_quantization/checker_output/main_graph_subgraph_2.json
Normal file
@@ -0,0 +1,191 @@
|
|||||||
|
{
|
||||||
|
"summary": {
|
||||||
|
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|
||||||
|
"frame per run": 1,
|
||||||
|
"frame per second": 86.4,
|
||||||
|
"input features": [
|
||||||
|
[
|
||||||
|
"input name",
|
||||||
|
"input size"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.22/m.0/m.0.1/attn/Transpose_1_output_0_calibrated_quantized",
|
||||||
|
"1x2x400x400"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.22/m.0/m.0.1/attn/Split_nhwc2nchw_transposed_output2",
|
||||||
|
"1x2x64x400"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.22/m.0/m.0.1/attn/pe/conv/Conv_nchw2nhwc_transposed_input0",
|
||||||
|
"1x20x20x128"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.22/m.0/m.0.0/Add_output_0_quantized",
|
||||||
|
"1x20x20x128"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.22/Split_output_0_quantized",
|
||||||
|
"1x20x20x128"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.22/Split_output_1_quantized",
|
||||||
|
"1x20x20x128"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.23/Reshape_output_0_quantized",
|
||||||
|
"1x1x4x6400"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.23/Reshape_1_output_0_quantized",
|
||||||
|
"1x1x4x1600"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.23/Reshape_3_output_0_quantized",
|
||||||
|
"1x1x4x6400"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.23/Reshape_4_output_0_quantized",
|
||||||
|
"1x1x4x1600"
|
||||||
|
]
|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||||
|
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|
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|
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|
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|
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|
||||||
|
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|
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|
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|
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|
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|
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|
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|
||||||
|
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|
||||||
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||||
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|
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|
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|
||||||
|
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|
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|
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|
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|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
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|
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|
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|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||||
|
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|
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|
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|
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|
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|
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|
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|
||||||
|
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|
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|
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|
||||||
|
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|
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|
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|
||||||
|
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|
||||||
|
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|
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|
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|
||||||
|
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|
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|
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|
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|
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|
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|
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|
||||||
|
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|
||||||
|
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|
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|
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|
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|
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|
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|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
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|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
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|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
"interval time (ms)": 0.5,
|
||||||
|
"latency (ms)": 11.57,
|
||||||
|
"latency (ms) by segments": [
|
||||||
|
11.479,
|
||||||
|
0.0,
|
||||||
|
0.095
|
||||||
|
],
|
||||||
|
"latency (us)": 11573.9,
|
||||||
|
"loaded bytes per frame": 36598144,
|
||||||
|
"loaded bytes per run": 36598144,
|
||||||
|
"model json CRC": "7202325c",
|
||||||
|
"model json file": "/tmp/tmp0plq7oph/main_graph_subgraph_2.hbir",
|
||||||
|
"model name": "main_graph_subgraph_2",
|
||||||
|
"model param CRC": "00000000",
|
||||||
|
"multicore sync time (ms)": 0.0,
|
||||||
|
"run per second": 86.4,
|
||||||
|
"runtime version": "3.15.55.0",
|
||||||
|
"stored bytes per frame": 32928704,
|
||||||
|
"stored bytes per run": 32928704,
|
||||||
|
"worst FPS": 86.4
|
||||||
|
}
|
||||||
|
}
|
||||||
983
x5_quantization/checker_output/main_graph_subgraph_3.html
Normal file
983
x5_quantization/checker_output/main_graph_subgraph_3.html
Normal file
File diff suppressed because one or more lines are too long
86
x5_quantization/checker_output/main_graph_subgraph_3.json
Normal file
86
x5_quantization/checker_output/main_graph_subgraph_3.json
Normal file
@@ -0,0 +1,86 @@
|
|||||||
|
{
|
||||||
|
"summary": {
|
||||||
|
"BPU PE number": 1,
|
||||||
|
"BPU core number": 1,
|
||||||
|
"BPU march": "B25E",
|
||||||
|
"DDR bytes per frame": 1396800,
|
||||||
|
"DDR bytes per run": 1396800,
|
||||||
|
"DDR bytes per second": 5072300619,
|
||||||
|
"DDR megabytes per frame": 1.332,
|
||||||
|
"DDR megabytes per run": 1.332,
|
||||||
|
"DDR megabytes per second": 4837.3,
|
||||||
|
"FPS": 3631.37,
|
||||||
|
"HBDK version": "3.49.15",
|
||||||
|
"compiling options": "-f hbir -m /tmp/tmp0plq7oph/main_graph_subgraph_3.hbir -o /tmp/tmp0plq7oph/main_graph_subgraph_3.hbm --march bayes-e --progressbar --input-layout NHWC --output-layout NHWC",
|
||||||
|
"frame per run": 1,
|
||||||
|
"frame per second": 3631.37,
|
||||||
|
"input features": [
|
||||||
|
[
|
||||||
|
"input name",
|
||||||
|
"input size"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.23/Split_output_1_quantized",
|
||||||
|
"1x1x8400x4"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.23/Expand_output_0_/model.23/GatherElements_cast_input",
|
||||||
|
"1x1x300x4"
|
||||||
|
]
|
||||||
|
],
|
||||||
|
"interval computing unit utilization": [
|
||||||
|
0.403,
|
||||||
|
0.101,
|
||||||
|
0.194,
|
||||||
|
0.187,
|
||||||
|
0.317,
|
||||||
|
0.11
|
||||||
|
],
|
||||||
|
"interval computing units utilization": [
|
||||||
|
0.403,
|
||||||
|
0.101,
|
||||||
|
0.194,
|
||||||
|
0.187,
|
||||||
|
0.317,
|
||||||
|
0.11
|
||||||
|
],
|
||||||
|
"interval loading bandwidth (megabytes/s)": [
|
||||||
|
1831,
|
||||||
|
2380,
|
||||||
|
3024,
|
||||||
|
2792,
|
||||||
|
2317,
|
||||||
|
1639
|
||||||
|
],
|
||||||
|
"interval number": 6,
|
||||||
|
"interval storing bandwidth (megabytes/s)": [
|
||||||
|
1975,
|
||||||
|
2642,
|
||||||
|
2857,
|
||||||
|
2262,
|
||||||
|
2158,
|
||||||
|
1603
|
||||||
|
],
|
||||||
|
"interval time (ms)": 0.05,
|
||||||
|
"latency (ms)": 0.28,
|
||||||
|
"latency (ms) by segments": [
|
||||||
|
0.0,
|
||||||
|
0.157,
|
||||||
|
0.0,
|
||||||
|
0.118
|
||||||
|
],
|
||||||
|
"latency (us)": 275.4,
|
||||||
|
"loaded bytes per frame": 714368,
|
||||||
|
"loaded bytes per run": 714368,
|
||||||
|
"model json CRC": "d2eeed26",
|
||||||
|
"model json file": "/tmp/tmp0plq7oph/main_graph_subgraph_3.hbir",
|
||||||
|
"model name": "main_graph_subgraph_3",
|
||||||
|
"model param CRC": "00000000",
|
||||||
|
"multicore sync time (ms)": 0.0,
|
||||||
|
"run per second": 3631.37,
|
||||||
|
"runtime version": "3.15.55.0",
|
||||||
|
"stored bytes per frame": 682432,
|
||||||
|
"stored bytes per run": 682432,
|
||||||
|
"worst FPS": 3631.37
|
||||||
|
}
|
||||||
|
}
|
||||||
983
x5_quantization/checker_output/main_graph_subgraph_4.html
Normal file
983
x5_quantization/checker_output/main_graph_subgraph_4.html
Normal file
File diff suppressed because one or more lines are too long
100
x5_quantization/checker_output/main_graph_subgraph_4.json
Normal file
100
x5_quantization/checker_output/main_graph_subgraph_4.json
Normal file
@@ -0,0 +1,100 @@
|
|||||||
|
{
|
||||||
|
"summary": {
|
||||||
|
"BPU PE number": 1,
|
||||||
|
"BPU core number": 1,
|
||||||
|
"BPU march": "B25E",
|
||||||
|
"DDR bytes per frame": 120960,
|
||||||
|
"DDR bytes per run": 120960,
|
||||||
|
"DDR bytes per second": 3114475513,
|
||||||
|
"DDR megabytes per frame": 0.115,
|
||||||
|
"DDR megabytes per run": 0.115,
|
||||||
|
"DDR megabytes per second": 2970.2,
|
||||||
|
"FPS": 25747.98,
|
||||||
|
"HBDK version": "3.49.15",
|
||||||
|
"compiling options": "-f hbir -m /tmp/tmp0plq7oph/main_graph_subgraph_4.hbir -o /tmp/tmp0plq7oph/main_graph_subgraph_4.hbm --march bayes-e --progressbar --input-layout NHWC --output-layout NHWC",
|
||||||
|
"frame per run": 1,
|
||||||
|
"frame per second": 25747.98,
|
||||||
|
"input features": [
|
||||||
|
[
|
||||||
|
"input name",
|
||||||
|
"input size"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.23/Split_output_0_quantized",
|
||||||
|
"1x1x8400x4"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.23/Expand_1_output_0_/model.23/GatherElements_2_cast_input",
|
||||||
|
"1x1x300x4"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.23/Unsqueeze_2_output_0_calibrated_Requantize_requantized_output",
|
||||||
|
"1x1x300x1"
|
||||||
|
],
|
||||||
|
[
|
||||||
|
"/model.23/Cast_2_output_0_calibrated_quantized",
|
||||||
|
"1x1x300x1"
|
||||||
|
]
|
||||||
|
],
|
||||||
|
"interval computing unit utilization": [
|
||||||
|
0.103,
|
||||||
|
0.072,
|
||||||
|
0.154,
|
||||||
|
0.262,
|
||||||
|
0.074,
|
||||||
|
0.09,
|
||||||
|
0.088,
|
||||||
|
0.38
|
||||||
|
],
|
||||||
|
"interval computing units utilization": [
|
||||||
|
0.103,
|
||||||
|
0.072,
|
||||||
|
0.154,
|
||||||
|
0.262,
|
||||||
|
0.074,
|
||||||
|
0.09,
|
||||||
|
0.088,
|
||||||
|
0.38
|
||||||
|
],
|
||||||
|
"interval loading bandwidth (megabytes/s)": [
|
||||||
|
1159,
|
||||||
|
1988,
|
||||||
|
4125,
|
||||||
|
3204,
|
||||||
|
1013,
|
||||||
|
952,
|
||||||
|
1382,
|
||||||
|
1293
|
||||||
|
],
|
||||||
|
"interval number": 8,
|
||||||
|
"interval storing bandwidth (megabytes/s)": [
|
||||||
|
1049,
|
||||||
|
1049,
|
||||||
|
524,
|
||||||
|
463,
|
||||||
|
1220,
|
||||||
|
1066,
|
||||||
|
1366,
|
||||||
|
1515
|
||||||
|
],
|
||||||
|
"interval time (ms)": 0.005,
|
||||||
|
"latency (ms)": 0.04,
|
||||||
|
"latency (ms) by segments": [
|
||||||
|
0.0,
|
||||||
|
0.039
|
||||||
|
],
|
||||||
|
"latency (us)": 38.8,
|
||||||
|
"loaded bytes per frame": 78016,
|
||||||
|
"loaded bytes per run": 78016,
|
||||||
|
"model json CRC": "6234711c",
|
||||||
|
"model json file": "/tmp/tmp0plq7oph/main_graph_subgraph_4.hbir",
|
||||||
|
"model name": "main_graph_subgraph_4",
|
||||||
|
"model param CRC": "00000000",
|
||||||
|
"multicore sync time (ms)": 0.0,
|
||||||
|
"run per second": 25747.98,
|
||||||
|
"runtime version": "3.15.55.0",
|
||||||
|
"stored bytes per frame": 42944,
|
||||||
|
"stored bytes per run": 42944,
|
||||||
|
"worst FPS": 25747.98
|
||||||
|
}
|
||||||
|
}
|
||||||
BIN
x5_quantization/checker_output/optimized_float_model.onnx
Normal file
BIN
x5_quantization/checker_output/optimized_float_model.onnx
Normal file
Binary file not shown.
BIN
x5_quantization/checker_output/original_float_model.onnx
Normal file
BIN
x5_quantization/checker_output/original_float_model.onnx
Normal file
Binary file not shown.
4235
x5_quantization/checker_output/quant_info.json
Normal file
4235
x5_quantization/checker_output/quant_info.json
Normal file
File diff suppressed because it is too large
Load Diff
BIN
x5_quantization/checker_output/quantized_model.onnx
Normal file
BIN
x5_quantization/checker_output/quantized_model.onnx
Normal file
Binary file not shown.
83
x5_quantization/extract_yolo26_bpu.py
Normal file
83
x5_quantization/extract_yolo26_bpu.py
Normal file
@@ -0,0 +1,83 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Extract YOLO26 raw detection heads from a standard Ultralytics ONNX export."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import re
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
import onnx
|
||||||
|
from onnx import TensorProto, helper, shape_inference
|
||||||
|
|
||||||
|
|
||||||
|
TERMINAL_HEAD = re.compile(
|
||||||
|
r"one2one_cv([23])\.(\d+)/one2one_cv\1\.\2\.2/Conv$"
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> None:
|
||||||
|
parser = argparse.ArgumentParser()
|
||||||
|
parser.add_argument("--input", type=Path, required=True)
|
||||||
|
parser.add_argument("--output", type=Path, required=True)
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
model = shape_inference.infer_shapes(onnx.load(args.input))
|
||||||
|
shapes = {
|
||||||
|
value.name: [dim.dim_value for dim in value.type.tensor_type.shape.dim]
|
||||||
|
for value in list(model.graph.value_info) + list(model.graph.output)
|
||||||
|
}
|
||||||
|
heads: dict[tuple[int, int], str] = {}
|
||||||
|
for node in model.graph.node:
|
||||||
|
match = TERMINAL_HEAD.search(node.name)
|
||||||
|
if match and node.op_type == "Conv":
|
||||||
|
branch, scale = int(match.group(1)), int(match.group(2))
|
||||||
|
heads[(branch, scale)] = node.output[0]
|
||||||
|
|
||||||
|
expected = {(branch, scale) for branch in (2, 3) for scale in range(3)}
|
||||||
|
if set(heads) != expected:
|
||||||
|
missing = sorted(expected - set(heads))
|
||||||
|
raise SystemExit(f"could not locate all YOLO26 one-to-one heads; missing {missing}")
|
||||||
|
|
||||||
|
del model.graph.output[:]
|
||||||
|
output_names = []
|
||||||
|
for scale, stride in enumerate((8, 16, 32)):
|
||||||
|
for branch, kind in ((3, "cls"), (2, "box")):
|
||||||
|
source = heads[(branch, scale)]
|
||||||
|
source_shape = shapes[source]
|
||||||
|
if len(source_shape) != 4:
|
||||||
|
raise SystemExit(f"unexpected head shape for {source}: {source_shape}")
|
||||||
|
output_name = f"{kind}_s{stride}"
|
||||||
|
model.graph.node.append(
|
||||||
|
helper.make_node(
|
||||||
|
"Transpose",
|
||||||
|
[source],
|
||||||
|
[output_name],
|
||||||
|
name=f"bpu_output_{kind}_s{stride}",
|
||||||
|
perm=[0, 2, 3, 1],
|
||||||
|
)
|
||||||
|
)
|
||||||
|
model.graph.output.append(
|
||||||
|
helper.make_tensor_value_info(
|
||||||
|
output_name,
|
||||||
|
TensorProto.FLOAT,
|
||||||
|
[source_shape[0], source_shape[2], source_shape[3], source_shape[1]],
|
||||||
|
)
|
||||||
|
)
|
||||||
|
output_names.append(output_name)
|
||||||
|
|
||||||
|
args.output.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
temporary = args.output.with_suffix(".unpruned.onnx")
|
||||||
|
onnx.save(model, temporary)
|
||||||
|
onnx.utils.extract_model(str(temporary), str(args.output), [model.graph.input[0].name], output_names)
|
||||||
|
temporary.unlink()
|
||||||
|
extracted = onnx.load(args.output)
|
||||||
|
onnx.checker.check_model(extracted)
|
||||||
|
print(f"wrote {args.output} with outputs:")
|
||||||
|
for output in extracted.graph.output:
|
||||||
|
dims = [dim.dim_value for dim in output.type.tensor_type.shape.dim]
|
||||||
|
print(f" {output.name}: {dims}")
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
1631
x5_quantization/mapper.log
Normal file
1631
x5_quantization/mapper.log
Normal file
File diff suppressed because it is too large
Load Diff
File diff suppressed because one or more lines are too long
File diff suppressed because it is too large
Load Diff
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
File diff suppressed because it is too large
Load Diff
Binary file not shown.
78
x5_quantization/postprocess_yolo26.py
Normal file
78
x5_quantization/postprocess_yolo26.py
Normal file
@@ -0,0 +1,78 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""CPU post-processing for the six raw outputs of best_bpu.onnx."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import numpy as np
|
||||||
|
|
||||||
|
|
||||||
|
def _nms(boxes: np.ndarray, scores: np.ndarray, iou_threshold: float) -> np.ndarray:
|
||||||
|
order = scores.argsort()[::-1]
|
||||||
|
kept: list[int] = []
|
||||||
|
while order.size:
|
||||||
|
current = int(order[0])
|
||||||
|
kept.append(current)
|
||||||
|
if order.size == 1:
|
||||||
|
break
|
||||||
|
rest = order[1:]
|
||||||
|
xx1 = np.maximum(boxes[current, 0], boxes[rest, 0])
|
||||||
|
yy1 = np.maximum(boxes[current, 1], boxes[rest, 1])
|
||||||
|
xx2 = np.minimum(boxes[current, 2], boxes[rest, 2])
|
||||||
|
yy2 = np.minimum(boxes[current, 3], boxes[rest, 3])
|
||||||
|
inter = np.maximum(0.0, xx2 - xx1) * np.maximum(0.0, yy2 - yy1)
|
||||||
|
area = (boxes[:, 2] - boxes[:, 0]) * (boxes[:, 3] - boxes[:, 1])
|
||||||
|
union = area[current] + area[rest] - inter
|
||||||
|
order = rest[(inter / np.maximum(union, 1e-9)) <= iou_threshold]
|
||||||
|
return np.asarray(kept, dtype=np.int64)
|
||||||
|
|
||||||
|
|
||||||
|
def postprocess(
|
||||||
|
outputs: list[np.ndarray] | tuple[np.ndarray, ...],
|
||||||
|
classes: int = 4,
|
||||||
|
score_threshold: float = 0.25,
|
||||||
|
iou_threshold: float = 0.7,
|
||||||
|
) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
|
||||||
|
"""Decode `(cls_s8, box_s8, cls_s16, box_s16, cls_s32, box_s32)` outputs.
|
||||||
|
|
||||||
|
Returns `(boxes_xyxy, scores, class_ids)` in the 640x640 model coordinate
|
||||||
|
system. Scale boxes back to the camera image after this function when using
|
||||||
|
letterbox preprocessing.
|
||||||
|
"""
|
||||||
|
if len(outputs) != 6:
|
||||||
|
raise ValueError(f"expected six outputs, got {len(outputs)}")
|
||||||
|
conf_raw = -np.log(1.0 / score_threshold - 1.0)
|
||||||
|
detections: list[np.ndarray] = []
|
||||||
|
for index, stride in enumerate((8, 16, 32)):
|
||||||
|
cls = np.asarray(outputs[index * 2]).reshape(-1, classes).astype(np.float32)
|
||||||
|
box = np.asarray(outputs[index * 2 + 1]).reshape(-1, 4).astype(np.float32)
|
||||||
|
max_logits = cls.max(axis=1)
|
||||||
|
valid = np.flatnonzero(max_logits >= conf_raw)
|
||||||
|
if valid.size == 0:
|
||||||
|
continue
|
||||||
|
height = width = 640 // stride
|
||||||
|
grid_y, grid_x = np.indices((height, width))
|
||||||
|
grid = np.stack((grid_x, grid_y), axis=-1).reshape(-1, 2).astype(np.float32) + 0.5
|
||||||
|
anchor = grid[valid]
|
||||||
|
distances = box[valid]
|
||||||
|
xyxy = np.column_stack(
|
||||||
|
((anchor[:, 0] - distances[:, 0]) * stride,
|
||||||
|
(anchor[:, 1] - distances[:, 1]) * stride,
|
||||||
|
(anchor[:, 0] + distances[:, 2]) * stride,
|
||||||
|
(anchor[:, 1] + distances[:, 3]) * stride)
|
||||||
|
)
|
||||||
|
scores = 1.0 / (1.0 + np.exp(-max_logits[valid]))
|
||||||
|
ids = cls[valid].argmax(axis=1).astype(np.float32)
|
||||||
|
detections.append(np.column_stack((xyxy, scores, ids)))
|
||||||
|
|
||||||
|
if not detections:
|
||||||
|
return np.empty((0, 4), np.float32), np.empty((0,), np.float32), np.empty((0,), np.int32)
|
||||||
|
dets = np.concatenate(detections, axis=0)
|
||||||
|
kept: list[np.ndarray] = []
|
||||||
|
for class_id in np.unique(dets[:, 5]).astype(np.int32):
|
||||||
|
class_dets = dets[dets[:, 5] == class_id]
|
||||||
|
indices = _nms(class_dets[:, :4], class_dets[:, 4], iou_threshold)
|
||||||
|
kept.append(class_dets[indices])
|
||||||
|
if not kept:
|
||||||
|
return np.empty((0, 4), np.float32), np.empty((0,), np.float32), np.empty((0,), np.int32)
|
||||||
|
result = np.concatenate(kept, axis=0)
|
||||||
|
return result[:, :4], result[:, 4], result[:, 5].astype(np.int32)
|
||||||
58
x5_quantization/prepare_calibration.py
Normal file
58
x5_quantization/prepare_calibration.py
Normal file
@@ -0,0 +1,58 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Create Horizon hb_mapper calibration feature maps from the YOLO dataset."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
import numpy as np
|
||||||
|
from PIL import Image
|
||||||
|
|
||||||
|
|
||||||
|
IMAGE_EXTS = {".jpg", ".jpeg", ".png", ".bmp", ".webp"}
|
||||||
|
|
||||||
|
|
||||||
|
def resize_rgb(image: Image.Image, size: int) -> np.ndarray:
|
||||||
|
image = image.convert("RGB")
|
||||||
|
resized = image.resize((size, size), Image.Resampling.BILINEAR)
|
||||||
|
array = np.asarray(resized, dtype=np.float32)
|
||||||
|
return np.transpose(array, (2, 0, 1))[None, ...]
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> None:
|
||||||
|
parser = argparse.ArgumentParser()
|
||||||
|
parser.add_argument("--dataset", type=Path, required=True)
|
||||||
|
parser.add_argument("--output", type=Path, required=True)
|
||||||
|
parser.add_argument("--samples", type=int, default=128)
|
||||||
|
parser.add_argument("--size", type=int, default=640)
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
roots = [args.dataset / "images" / "train", args.dataset / "images" / "vel"]
|
||||||
|
images = sorted(
|
||||||
|
p for root in roots if root.is_dir() for p in root.iterdir() if p.suffix.lower() in IMAGE_EXTS
|
||||||
|
)
|
||||||
|
if not images:
|
||||||
|
raise SystemExit(f"no images found below {args.dataset}")
|
||||||
|
count = min(args.samples, len(images))
|
||||||
|
# Evenly spread samples over the sorted set so calibration is not dominated by one split.
|
||||||
|
indices = np.linspace(0, len(images) - 1, count, dtype=np.int64)
|
||||||
|
selected = [images[int(i)] for i in indices]
|
||||||
|
|
||||||
|
args.output.mkdir(parents=True, exist_ok=True)
|
||||||
|
for old in args.output.iterdir():
|
||||||
|
if old.is_file() and old.suffix in {".bin", ".rgbchw", ".txt"}:
|
||||||
|
old.unlink()
|
||||||
|
manifest = []
|
||||||
|
for index, path in enumerate(selected):
|
||||||
|
data = resize_rgb(Image.open(path), args.size)
|
||||||
|
data.tofile(args.output / f"{index:05d}.rgbchw")
|
||||||
|
manifest.append(str(path.relative_to(args.dataset)))
|
||||||
|
(args.output.parent / "calibration_manifest.txt").write_text(
|
||||||
|
"\n".join(manifest) + "\n", encoding="utf-8"
|
||||||
|
)
|
||||||
|
print(f"wrote {count} samples ({args.size}x{args.size}) to {args.output}")
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
58
x5_quantization/quantize_x5.sh
Executable file
58
x5_quantization/quantize_x5.sh
Executable file
@@ -0,0 +1,58 @@
|
|||||||
|
#!/usr/bin/env bash
|
||||||
|
set -euo pipefail
|
||||||
|
|
||||||
|
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
|
||||||
|
MODEL_DIR="$(cd "${SCRIPT_DIR}/.." && pwd)"
|
||||||
|
REPO_DIR="$(cd "${MODEL_DIR}/.." && pwd)"
|
||||||
|
IMAGE="openexplorer/ai_toolchain_ubuntu_20_x5_cpu:v1.2.8"
|
||||||
|
|
||||||
|
docker run --rm --platform linux/amd64 \
|
||||||
|
-v "${REPO_DIR}:/workspace/smart_car_2026" \
|
||||||
|
"${IMAGE}" bash -lc '
|
||||||
|
set -euo pipefail
|
||||||
|
cd /workspace/smart_car_2026/model/x5_quantization
|
||||||
|
python3 extract_yolo26_bpu.py \
|
||||||
|
--input ../best.onnx \
|
||||||
|
--output best_bpu.onnx
|
||||||
|
python3 prepare_calibration.py \
|
||||||
|
--dataset /workspace/smart_car_2026/dataset \
|
||||||
|
--output calibration_data \
|
||||||
|
--samples 50
|
||||||
|
cat > best_bpu_int8.yaml <<"YAML"
|
||||||
|
model_parameters:
|
||||||
|
onnx_model: "./best_bpu.onnx"
|
||||||
|
march: "bayes-e"
|
||||||
|
layer_out_dump: false
|
||||||
|
working_dir: "mapper_output_bpu"
|
||||||
|
output_model_file_prefix: "best_bpu_bayese_640x640_nv12"
|
||||||
|
|
||||||
|
input_parameters:
|
||||||
|
input_name: "images"
|
||||||
|
input_type_rt: "nv12"
|
||||||
|
input_type_train: "rgb"
|
||||||
|
input_layout_train: "NCHW"
|
||||||
|
norm_type: "data_scale"
|
||||||
|
scale_value: 0.003921568627451
|
||||||
|
|
||||||
|
calibration_parameters:
|
||||||
|
cal_data_dir: "./calibration_data"
|
||||||
|
cal_data_type: "float32"
|
||||||
|
calibration_type: "default"
|
||||||
|
optimization: "set_Softmax_input_int8,set_Softmax_output_int8"
|
||||||
|
|
||||||
|
compiler_parameters:
|
||||||
|
jobs: 8
|
||||||
|
compile_mode: "latency"
|
||||||
|
debug: true
|
||||||
|
optimize_level: "O3"
|
||||||
|
YAML
|
||||||
|
hb_mapper checker \
|
||||||
|
--model best_bpu.onnx \
|
||||||
|
--model-type onnx \
|
||||||
|
--march bayes-e \
|
||||||
|
--input-shape images 1x3x640x640
|
||||||
|
hb_mapper makertbin \
|
||||||
|
--config best_bpu_int8.yaml \
|
||||||
|
--model-type onnx
|
||||||
|
ls -lh mapper_output_bpu/best_bpu_bayese_640x640_nv12.bin
|
||||||
|
'
|
||||||
Reference in New Issue
Block a user