commit 7931375c8e6809162ce647b945b842379068badb Author: cyy_mac Date: Fri Aug 7 11:15:41 2026 +0800 Add YOLOv26n RDK X5 model and quantized artifacts diff --git a/README.md b/README.md new file mode 100644 index 0000000..48d9d14 --- /dev/null +++ b/README.md @@ -0,0 +1,116 @@ +# YOLOv26n RDK X5 模型与量化产物 + +这是基于 YOLOv26n 训练得到的检测模型，以及按 D-Robotics RDK X5 官方 +`rdk_x5` 模型仓库流程生成的 BPU 量化产物。 + +官方参考： + +- +- + +## 模型信息 + +| 项目 | 内容 | +| --- | --- | +| 浮点模型 | `best.onnx` | +| ONNX IR / opset | IR 6 / opset 11 | +| 输入 | `images`, `[1, 3, 640, 640]`, RGB | +| 类别数 | 4 | +| 类别名称 | `QR_code`, `line`, `end`, `roadblock` | +| 原始 ONNX 输出 | `output0`, `[1, 300, 6]` | +| BPU 输入 | NV12, 640x640 | +| BPU 输出 | 三尺度 `(cls, box)` 原始特征，共 6 个 NHWC 张量 | + +原始 `best.onnx` 包含 YOLOv26 的端到端后处理。为了减少 BPU 与 CPU 之间的 +切换，`x5_quantization/best_bpu.onnx` 只保留检测网络和原始检测头，移除了 +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 +sigmoid、置信度筛选、LTRB 解码和 NMS。 + +## 目录内容 + +```text +best.onnx # 原始浮点 ONNX +x5_quantization/ + best_bpu.onnx # 裁剪后的 BPU 友好 ONNX + best_bpu_int8.yaml # hb_mapper 配置 + mapper_output_bpu/ + best_bpu_bayese_640x640_nv12.bin # X5 可加载模型 + *_quant_info.json # 输出量化参数 + *_quantized_model.onnx # 量化检查模型 + calibration_data/ # 50 个 RGB/CHW/float32 校准输入 + prepare_calibration.py # 生成校准输入 + extract_yolo26_bpu.py # 裁剪 YOLOv26 后处理 + postprocess_yolo26.py # CPU 后处理 + quantize_x5.sh # Docker 一键量化 + checker.log / mapper.log # checker 和 makertbin 日志 +``` + +## 重新量化 + +需要 Docker Desktop 和已加载的镜像： + +```text +openexplorer/ai_toolchain_ubuntu_20_x5_cpu:v1.2.8 +``` + +在本目录的上一级执行： + +```bash +cd /Users/chenyouyuan/cyy_ws/smart_car_2026/model +./x5_quantization/quantize_x5.sh +``` + +脚本会从 `../dataset` 的 `images/train` 和 `images/vel` 中均匀抽取 50 张图片， +直接 resize 到 640x640，保存为 RGB、CHW、float32；`data_scale=1/255` 由 +`hb_mapper` 配置完成。量化目标为 `bayes-e`，默认 int8，编译优化等级为 O3， +并启用 `set_Softmax_input_int8,set_Softmax_output_int8`。 + +## BPU 输出与 CPU 后处理 + +模型输出顺序固定为： + +```text +cls_s8, box_s8, cls_s16, box_s16, cls_s32, box_s32 +``` + +形状分别为： + +```text +cls_s8 / box_s8 [1, 80, 80, 4] +cls_s16 / box_s16 [1, 40, 40, 4] +cls_s32 / box_s32 [1, 20, 20, 4] +``` + +可以直接复用 `x5_quantization/postprocess_yolo26.py`： + +```python +from x5_quantization.postprocess_yolo26 import postprocess + +boxes, scores, class_ids = postprocess( + [cls_s8, box_s8, cls_s16, box_s16, cls_s32, box_s32], + classes=4, + score_threshold=0.25, + iou_threshold=0.7, +) +``` + +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 +根据实际缩放比例和 padding 将坐标映射回原始相机分辨率。 + +## 量化结果 + +`hb_mapper checker` 和 `hb_mapper makertbin` 均已通过。编译器对 X5 的估计延迟 +为 `8.913 ms`，最终 `.bin` 大小约 `3.7 MB`。输出余弦相似度如下： + +| 输出 | Cosine Similarity | +| --- | ---: | +| `cls_s8` | 0.985422 | +| `box_s8` | 0.989597 | +| `cls_s16` | 0.989395 | +| `box_s16` | 0.993338 | +| `cls_s32` | 0.998478 | +| `box_s32` | 0.999024 | + +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 +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 +检测精度和端到端延迟。 diff --git a/best.onnx b/best.onnx new file mode 100644 index 0000000..4173434 Binary files /dev/null and b/best.onnx differ diff --git a/x5_quantization/README.md b/x5_quantization/README.md new file mode 100644 index 0000000..ff4dad3 --- /dev/null +++ b/x5_quantization/README.md @@ -0,0 +1,20 @@ +# RDK X5 YOLOv26n 量化 + +输入模型为 `../best.onnx`，固定输入 `images [1,3,640,640]`，opset 11。流程参考 +`D-Robotics/rdk_model_zoo` 的 `rdk_x5` 分支中 `ultralytics_yolo26` 示例： + +- `extract_yolo26_bpu.py` 移除 TopK、Gather 和最终检测结果组装，只输出三尺度 + `(cls, box)` 原始特征，输出布局为 NHWC。 +- 校准数据从 `../../dataset` 均匀抽取 50 张图片，直接 resize 到 640x640，保存 + RGB/CHW/float32；`data_scale=1/255` 由量化配置完成。 +- 板端输入为 NV12，量化默认 int8，并使用官方 Softmax int8 优化项。 + +执行 `./quantize_x5.sh` 会在 Docker 镜像 +`openexplorer/ai_toolchain_ubuntu_20_x5_cpu:v1.2.8` 中依次运行 `hb_mapper checker` +和 `hb_mapper makertbin`，产物为 +`mapper_output_bpu/best_bpu_bayese_640x640_nv12.bin`。部署端需要按三尺度输出完成 +sigmoid、LTRB 解码、阈值筛选和 NMS；可直接复用 `postprocess_yolo26.py`。 + +板端输入是 NV12，模型输出顺序为 `cls_s8, box_s8, cls_s16, box_s16, +cls_s32, box_s32`，输出张量布局是 NHWC。`.bin` 的 `model_info` 应以板端 +`hrt_model_exec` 实际显示的名称和量化参数为准。 diff --git a/x5_quantization/best_bpu.onnx b/x5_quantization/best_bpu.onnx new file mode 100644 index 0000000..36e563b Binary files /dev/null and b/x5_quantization/best_bpu.onnx differ diff --git a/x5_quantization/best_bpu_int8.yaml b/x5_quantization/best_bpu_int8.yaml new file mode 100644 index 0000000..8910e20 --- /dev/null +++ b/x5_quantization/best_bpu_int8.yaml @@ -0,0 +1,26 @@ +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: 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+images/train/c6a9a9fd-242d-420f-91bc-79419f83604a_aug2.jpg +images/train/cc7d55cb-6fb7-4ed8-a524-b022c671454e_aug1.jpg +images/train/d1b89258-c545-4d4a-bd32-60e6f5d7131a_aug1.jpg +images/train/d6601c84-b38a-46df-94c9-3e67ae4c0b7b_aug2.jpg +images/train/dbf7ba4e-24fc-45dd-b655-144bd4ccbe71_aug1.jpg +images/train/e0f3883b-2301-4b95-b975-9fd4a1cfa0be.png +images/train/e605a9e1-5ae1-4da4-8326-9050c21966c6_aug2.jpg +images/train/eb08a24f-7ead-4fae-9f4c-717cd54e4b8f_aug3.jpg +images/train/f040251a-9a78-4536-9439-3803759952e5.png +images/train/f5c6161c-9ea7-432a-9b44-82678c19ee0e_aug2.jpg +images/train/fb30aaaf-3009-4089-98b4-088e020ae1bb_aug2.jpg +images/vel/02f61ef1-3c40-446e-ac2d-fbc7e4ccf605_aug1.jpg +images/vel/0dc056fb-8373-4834-8630-bc0057a1d24c_aug1.jpg +images/vel/1cb927cc-6af4-4c87-a3fa-f5a6f1fc1ebd_aug2.jpg +images/vel/2bdc0ba0-bac7-41d2-80ce-f0301e3e2d5c.png +images/vel/3b347f91-60b4-4d1a-b187-50a9f106f072_aug2.jpg +images/vel/4a674364-26ba-43c8-9448-bcd2bdd68275_aug2.jpg +images/vel/4fc2dc2f-85db-4df0-a4a6-e18f15a856dd.png +images/vel/fb5adb2c-e598-4ae4-bbf1-8e46a10158c3_aug4.jpg diff --git a/x5_quantization/checker.log b/x5_quantization/checker.log new file mode 100644 index 0000000..4d28b5d --- /dev/null +++ b/x5_quantization/checker.log @@ -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 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id(1) HzSQuantizedConv -- 1.0 int8 +/model.19/m.0/m/m.1/cv1/act/Mul BPU id(1) HzLut -- 1.0 int8 +/model.19/m.0/m/m.1/cv2/conv/Conv BPU id(1) HzSQuantizedConv -- 1.0 int8 +/model.19/m.0/m/m.1/cv2/act/Mul BPU id(1) HzLut -- 1.0 int8 +/model.19/m.0/m/m.1/Add BPU id(1) HzSElementwiseAdd -- 1.0 int8 +/model.19/m.0/Concat BPU id(1) Concat -- 1.0 int8 +/model.19/m.0/cv3/conv/Conv BPU id(1) HzSQuantizedConv -- 1.0 int8 +/model.19/m.0/cv3/act/Mul BPU id(1) HzLut -- 1.0 int8 +/model.19/Concat BPU id(1) Concat -- 1.0 int8 +/model.19/cv2/conv/Conv BPU id(1) HzSQuantizedConv -- 1.0 int8 +/model.19/cv2/act/Mul BPU id(1) HzLut -- 1.0 int8 +/model.20/conv/Conv BPU id(1) HzSQuantizedConv -- 1.0 int8 +/model.23/one2one_cv2.1/one2one_cv2.1.0/conv/Conv BPU id(1) HzSQuantizedConv -- 1.0 int8 +...3.1/one2one_cv3.1.0/one2one_cv3.1.0.0/conv/Conv BPU id(1) HzSQuantizedConv -- 1.0 int8 +/model.20/act/Mul BPU id(1) HzLut -- 1.0 int8 +/model.23/one2one_cv2.1/one2one_cv2.1.0/act/Mul BPU id(1) HzLut -- 1.0 int8 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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.... diff --git a/x5_quantization/checker_output/Extracted from {main_graph}_subgraph_0.html b/x5_quantization/checker_output/Extracted from {main_graph}_subgraph_0.html new file mode 100644 index 0000000..5de7155 --- /dev/null +++ b/x5_quantization/checker_output/Extracted from {main_graph}_subgraph_0.html @@ -0,0 +1,983 @@ + + +Extracted from {main_graph}_subgraph_0 + +
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}, + "bpu_output_cls_s32": { + "type": "Transpose", + "inputs": [ + "/model.23/one2one_cv3.2/one2one_cv3.2.2/Conv_output_0" + ], + "outputs": [ + "cls_s32" + ], + "thresholds": [ + [] + ], + "cosine_similarity": "--" + }, + "bpu_output_box_s32": { + "type": "Transpose", + "inputs": [ + "/model.23/one2one_cv2.2/one2one_cv2.2.2/Conv_output_0" + ], + "outputs": [ + "box_s32" + ], + "thresholds": [ + [] + ], + "cosine_similarity": "--" + } +} \ No newline at end of file diff --git a/x5_quantization/checker_output/quantized_model.onnx b/x5_quantization/checker_output/quantized_model.onnx new file mode 100644 index 0000000..1f7b3f1 Binary files /dev/null and b/x5_quantization/checker_output/quantized_model.onnx differ diff --git a/x5_quantization/extract_yolo26_bpu.py b/x5_quantization/extract_yolo26_bpu.py new file mode 100644 index 0000000..24788e8 --- /dev/null +++ b/x5_quantization/extract_yolo26_bpu.py @@ -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() diff --git a/x5_quantization/mapper.log b/x5_quantization/mapper.log new file mode 100644 index 0000000..e1a4223 --- /dev/null +++ b/x5_quantization/mapper.log @@ -0,0 +1,1631 @@ +2026-08-07 10:39:54,809 file: tool_utils.py func: tool_utils line No: 77 log will be stored in /workspace/smart_car_2026/model/hb_mapper_makertbin.log +2026-08-07 10:39:54,810 file: hb_mapper.py func: hb_mapper line No: 132 Start hb_mapper.... +2026-08-07 10:39:54,810 file: hb_mapper.py func: hb_mapper line No: 133 hbdk version 3.49.15 +2026-08-07 10:39:54,811 file: hb_mapper.py func: hb_mapper line No: 134 horizon_nn version 1.1.0 +2026-08-07 10:39:54,811 file: hb_mapper.py func: hb_mapper line No: 135 hb_mapper version 1.24.3 +2026-08-07 10:39:54,811 file: hb_mapper_makertbin.py func: hb_mapper_makertbin line No: 530 Start Model Convert.... +2026-08-07 10:39:54,816 file: mapper_conf_parser.py func: mapper_conf_parser line No: 105 validating model_parameters... +2026-08-07 10:39:54,816 file: mapper_conf_parser.py func: mapper_conf_parser line No: 1347 Using abs path /workspace/smart_car_2026/model/x5_quantization/best_bpu.onnx +2026-08-07 10:39:54,816 file: mapper_conf_parser.py func: mapper_conf_parser line No: 260 Using onnx model file: /workspace/smart_car_2026/model/x5_quantization/best_bpu.onnx +2026-08-07 10:39:54,830 file: onnx_parser.py func: onnx_parser line No: 39 Model input names: ['images'] +2026-08-07 10:39:54,831 file: mapper_conf_parser.py func: mapper_conf_parser line No: 264 Model has 1 inputs according to model file +2026-08-07 10:39:54,831 file: mapper_conf_parser.py func: mapper_conf_parser line No: 1347 Using abs path /workspace/smart_car_2026/model/x5_quantization/mapper_output_bpu +2026-08-07 10:39:54,831 file: mapper_conf_parser.py func: mapper_conf_parser line No: 287 working_dir does not exist. Creating working_dir: /workspace/smart_car_2026/model/x5_quantization/mapper_output_bpu +2026-08-07 10:39:54,832 file: mapper_conf_parser.py func: mapper_conf_parser line No: 438 node_dict: {self.node_dict} +2026-08-07 10:39:54,832 file: mapper_conf_parser.py func: mapper_conf_parser line No: 119 validating model_parameters finished +2026-08-07 10:39:54,832 file: mapper_conf_parser.py func: mapper_conf_parser line No: 123 validating input_parameters... +2026-08-07 10:39:54,832 file: mapper_conf_parser.py func: mapper_conf_parser line No: 536 Model input shape not given in yaml_file, using shape from model file: [[1, 3, 640, 640]] +2026-08-07 10:39:54,832 file: mapper_conf_parser.py func: mapper_conf_parser line No: 639 nv12 input type rt received. +2026-08-07 10:39:54,833 file: mapper_conf_parser.py func: mapper_conf_parser line No: 135 validating input_parameters finished +2026-08-07 10:39:54,833 file: mapper_conf_parser.py func: mapper_conf_parser line No: 139 validating calibration_parameters... +2026-08-07 10:39:54,833 file: mapper_conf_parser.py func: mapper_conf_parser line No: 1347 Using abs path /workspace/smart_car_2026/model/x5_quantization/calibration_data +2026-08-07 10:39:54,833 file: mapper_conf_parser.py func: mapper_conf_parser line No: 1007 The calibration dir name suffix is not the same as the value float32 of the parameter cal_data_type, the parameter setting will prevail +2026-08-07 10:39:54,833 file: mapper_conf_parser.py func: mapper_conf_parser line No: 155 validating calibration_parameters finished +2026-08-07 10:39:54,833 file: mapper_conf_parser.py func: mapper_conf_parser line No: 159 validating custom_op... +2026-08-07 10:39:54,833 file: mapper_conf_parser.py func: mapper_conf_parser line No: 1076 custom_op does not exist, skipped +2026-08-07 10:39:54,834 file: mapper_conf_parser.py func: mapper_conf_parser line No: 165 validating custom_op finished +2026-08-07 10:39:54,834 file: mapper_conf_parser.py func: mapper_conf_parser line No: 168 validating compiler_parameters... +2026-08-07 10:39:54,834 file: mapper_conf_parser.py func: mapper_conf_parser line No: 1157 Input node images's input_source not set, it will be set to pyramid by default +2026-08-07 10:39:54,834 file: mapper_conf_parser.py func: mapper_conf_parser line No: 183 validating compiler_parameters finished +2026-08-07 10:39:54,834 file: mapper_conf_parser.py func: mapper_conf_parser line No: 187 validating deprecated parameters... +2026-08-07 10:39:54,834 file: mapper_conf_parser.py func: mapper_conf_parser line No: 193 validating deprecated parameters finished +2026-08-07 10:39:54,835 file: hb_mapper_makertbin.py func: hb_mapper_makertbin line No: 54 Dump config: +2026-08-07 10:39:54,835 file: hb_mapper_makertbin.py func: hb_mapper_makertbin line No: 55 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: + compile_mode: latency + debug: true + jobs: 8 + optimize_level: O3 +input_parameters: + input_layout_train: NCHW + input_name: images + input_type_rt: nv12 + input_type_train: rgb + norm_type: data_scale + scale_value: '0.003921568627451' +model_parameters: + layer_out_dump: false + march: bayes-e + onnx_model: ./best_bpu.onnx + output_model_file_prefix: best_bpu_bayese_640x640_nv12 + working_dir: mapper_output_bpu + +2026-08-07 10:39:54,837 file: hb_mapper_makertbin.py func: hb_mapper_makertbin line No: 60 input 'images' : original model shape: [1, 3, 640, 640] +2026-08-07 10:39:54,838 file: loader.py func: loader line No: 204 ******************************************* +2026-08-07 10:39:54,838 file: loader.py func: loader line No: 205 First calibration picture name: 00000.rgbchw +2026-08-07 10:39:54,839 file: loader.py func: loader line No: 207 First calibration picture md5: +2026-08-07 10:39:54,898 file: loader.py func: loader line No: 211 ******************************************* +2026-08-07 10:39:54,899 file: loader.py func: loader line No: 282 created RawImageDirLoader of shape:[1, 3, 640, 640] +2026-08-07 10:39:54,899 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00000.rgbchw +2026-08-07 10:39:54,970 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00001.rgbchw +2026-08-07 10:39:55,038 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00002.rgbchw +2026-08-07 10:39:55,106 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00003.rgbchw +2026-08-07 10:39:55,173 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00004.rgbchw +2026-08-07 10:39:55,240 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00005.rgbchw +2026-08-07 10:39:55,310 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00006.rgbchw +2026-08-07 10:39:55,378 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00007.rgbchw +2026-08-07 10:39:55,447 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00008.rgbchw +2026-08-07 10:39:55,515 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00009.rgbchw +2026-08-07 10:39:55,584 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00010.rgbchw +2026-08-07 10:39:55,653 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00011.rgbchw +2026-08-07 10:39:55,721 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00012.rgbchw +2026-08-07 10:39:55,789 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00013.rgbchw +2026-08-07 10:39:55,855 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00014.rgbchw +2026-08-07 10:39:55,923 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00015.rgbchw +2026-08-07 10:39:55,991 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00016.rgbchw +2026-08-07 10:39:56,060 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00017.rgbchw +2026-08-07 10:39:56,127 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00018.rgbchw +2026-08-07 10:39:56,194 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00019.rgbchw +2026-08-07 10:39:56,261 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00020.rgbchw +2026-08-07 10:39:56,328 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00021.rgbchw +2026-08-07 10:39:56,395 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00022.rgbchw +2026-08-07 10:39:56,463 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00023.rgbchw +2026-08-07 10:39:56,531 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00024.rgbchw +2026-08-07 10:39:56,600 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00025.rgbchw +2026-08-07 10:39:56,669 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00026.rgbchw +2026-08-07 10:39:56,741 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00027.rgbchw +2026-08-07 10:39:56,811 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00028.rgbchw +2026-08-07 10:39:56,884 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00029.rgbchw +2026-08-07 10:39:56,956 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00030.rgbchw +2026-08-07 10:39:57,027 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00031.rgbchw +2026-08-07 10:39:57,101 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00032.rgbchw +2026-08-07 10:39:57,175 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00033.rgbchw +2026-08-07 10:39:57,244 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00034.rgbchw +2026-08-07 10:39:57,314 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00035.rgbchw +2026-08-07 10:39:57,387 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00036.rgbchw +2026-08-07 10:39:57,474 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00037.rgbchw +2026-08-07 10:39:57,549 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00038.rgbchw +2026-08-07 10:39:57,621 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00039.rgbchw +2026-08-07 10:39:57,700 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00040.rgbchw +2026-08-07 10:39:57,772 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00041.rgbchw +2026-08-07 10:39:57,844 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00042.rgbchw +2026-08-07 10:39:57,917 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00043.rgbchw +2026-08-07 10:39:58,002 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00044.rgbchw +2026-08-07 10:39:58,076 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00045.rgbchw +2026-08-07 10:39:58,150 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00046.rgbchw +2026-08-07 10:39:58,228 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00047.rgbchw +2026-08-07 10:39:58,301 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00048.rgbchw +2026-08-07 10:39:58,372 file: loader.py func: loader line No: 287 Read raw file: /workspace/smart_car_2026/model/x5_quantization/calibration_data/00049.rgbchw +2026-08-07 10:39:58,446 file: tool_utils.py func: tool_utils line No: 368 num of calibration data: 50 +2026-08-07 10:39:58,446 file: tool_utils.py func: tool_utils line No: 369 calibration data shape: (1, 3, 640, 640) +2026-08-07 10:39:58,473 file: hb_mapper_makertbin.py func: hb_mapper_makertbin line No: 519 call build params: + {'march': 'bayes-e', 'save_model': True, 'name_prefix': 'best_bpu_bayese_640x640_nv12', 'input_dict': {'images': {'input_shape': [1, 3, 640, 640], 'expected_input_type': 'YUV444_128', 'original_input_type': 'RGB', 'original_input_layout': 'NCHW', 'scales': array([0.00392157], dtype=float32)}}, 'cali_dict': {'calibration_type': 'default', 'calibration_data': {'images': [array([[[[ -30., -30., -29., ..., -18., -18., -18.], + [ -29., -29., -28., ..., -17., -17., -18.], + [ -28., -28., -27., ..., -17., -17., -18.], + ..., + [ -12., -14., -14., ..., -114., -114., -114.], + [ -14., -15., -14., ..., -114., -114., -114.], + [ -15., -16., -15., ..., -115., -115., -115.]], + + [[ -10., -10., -10., ..., -4., -5., -5.], + [ -10., -10., -10., ..., -4., -5., -5.], + [ -10., -10., -10., ..., -5., -5., -5.], + ..., + [ -20., -20., -20., ..., -3., -3., -3.], + [ -21., -21., -20., ..., -3., -3., -3.], + [ -21., -21., -20., ..., -3., -3., -3.]], + + [[ 2., 2., 2., ..., -3., -4., -4.], + [ 2., 2., 2., ..., -3., -4., -4.], + [ -1., -1., -1., ..., -4., -4., -4.], + ..., + [ 8., 8., 8., ..., -3., -3., -3.], + [ 8., 8., 8., ..., -3., -3., -3.], + [ 8., 8., 8., ..., -3., -3., -3.]]]], dtype=float32), array([[[[ 7., -1., -9., ..., -128., -128., -128.], + [ 6., -1., -8., ..., -128., -128., -128.], + [ 5., 0., -5., ..., -128., -128., -128.], + ..., + [ -24., -23., -22., ..., -61., -62., -63.], + [ -24., -23., -22., ..., -71., -72., -73.], + [ -24., -23., -22., ..., -79., -80., -80.]], + + [[ -14., -14., -14., ..., -1., -1., -1.], + [ -14., -14., -14., ..., -1., -1., -1.], + [ -14., -14., -14., ..., -1., -1., -1.], + ..., + [ -2., -2., -2., ..., 1., 1., 1.], + [ -2., -2., -2., ..., 2., 2., 2.], + [ -2., -2., -2., ..., 2., 2., 2.]], + + [[ 4., 4., 4., ..., 0., 0., 0.], + [ 4., 4., 4., ..., 0., 0., 0.], + [ 4., 4., 4., ..., 0., 0., 0.], + ..., + [ -6., -6., -6., ..., -6., -6., -6.], + [ -6., -6., -6., ..., -6., -6., -6.], + [ -6., -6., -6., ..., -6., -6., -6.]]]], dtype=float32), array([[[[-115., -114., -114., ..., 10., 18., 14.], + [-112., -111., -111., ..., -2., 6., 6.], + [-108., -107., -106., ..., -7., -3., -2.], + ..., + [ -29., -29., -28., ..., -114., -114., -114.], + [ -28., -28., -28., ..., -114., -114., -114.], + [ -27., -28., -27., ..., -114., -114., -114.]], + + [[ -8., -8., -9., ..., -8., -6., -6.], + [ -8., -8., -9., ..., -8., -6., -6.], + [ -10., -10., -11., ..., -8., -7., -7.], + ..., + [ 3., 3., 3., ..., -8., -8., -8.], + [ 3., 3., 3., ..., -6., -6., -6.], + [ 3., 3., 3., ..., -6., -6., -6.]], + + [[ -8., -8., -8., ..., 0., -1., -1.], + [ -8., -8., -8., ..., 0., -1., -1.], + [ -7., -7., -8., ..., 0., -2., -2.], + ..., + [ -11., -11., -12., ..., -6., -6., -6.], + [ -11., -11., -12., ..., -6., -6., -6.], + [ -11., -11., -12., ..., -6., -6., -6.]]]], dtype=float32), array([[[[-113., -114., -114., ..., -29., -30., -31.], + [-113., -113., -114., ..., -29., -30., -31.], + [-113., -113., -114., ..., -29., -29., -30.], + ..., + [ -14., -14., -14., ..., -113., -113., -114.], + [ -13., -13., -14., ..., -114., -114., -115.], + [ -12., -13., -14., ..., -114., -115., -115.]], + + [[ -9., -9., -8., ..., -7., -7., -7.], + [ -9., -9., -8., ..., -7., -7., -7.], + [ -9., -9., -8., ..., -7., -7., -7.], + ..., + [ 1., 1., 2., ..., 5., 5., 5.], + [ 1., 1., 2., ..., 1., 1., 1.], + [ 1., 1., 2., ..., 1., 1., 1.]], + + [[ -6., -6., -6., ..., 0., 0., 0.], + [ -6., -6., -6., ..., 0., 0., 0.], + [ -6., -6., -6., ..., -1., -1., -1.], + ..., + [ -5., -5., -6., ..., -10., -10., -10.], + [ -5., -5., -6., ..., -6., -6., -6.], + [ -5., -5., -6., ..., -6., -6., -6.]]]], dtype=float32), array([[[[ -18., -18., -18., ..., -41., -41., -41.], + [ -18., -18., -18., ..., -40., -40., -40.], + [ -18., -18., -18., ..., -40., -40., -40.], + ..., + [ -42., -41., -39., ..., -120., -121., -121.], + [ -42., -41., -39., ..., -120., -121., -121.], + [ -42., -41., -39., ..., -120., -121., -121.]], + + [[ -14., -14., -14., ..., -20., -20., -20.], + [ -14., -14., -14., ..., -20., -20., -20.], + [ -14., -14., -14., ..., -20., -20., -20.], + ..., + [ -3., -3., -3., ..., -3., -3., -3.], + [ -3., -3., -3., ..., -4., -4., -4.], + [ -3., -3., -3., ..., -4., -4., -4.]], + + [[ 4., 4., 4., ..., 2., 2., 2.], + [ 4., 4., 4., ..., 2., 2., 2.], + [ 4., 4., 4., ..., 3., 3., 3.], + ..., + [ -5., -5., -5., ..., -6., -6., -6.], + [ -5., -5., -5., ..., -6., -6., -6.], + [ -5., -5., -5., ..., -6., -6., -6.]]]], dtype=float32), array([[[[-89., -81., -65., ..., -73., -74., -75.], + [-88., -80., -65., ..., -72., -73., -74.], + [-88., -80., -65., ..., -70., -71., -72.], + ..., + [-26., -23., -24., ..., -19., -19., -18.], + [-25., -24., -25., ..., -19., -19., -18.], + [-26., -26., -28., ..., -20., -20., -18.]], + + [[-15., -15., -15., ..., -14., -14., -14.], + [-15., -15., -15., ..., -14., -14., -14.], + [-15., -15., -15., ..., -14., -14., -14.], + ..., + [ 2., 2., 2., ..., 1., 1., 1.], + [ 2., 2., 2., ..., 1., 1., 1.], + [ 2., 2., 2., ..., 1., 1., 1.]], + + [[ -2., -2., -1., ..., -2., -2., -2.], + [ -2., -2., -1., ..., -2., -2., -2.], + [ -1., -1., -1., ..., -2., -2., -2.], + ..., + [ -9., -9., -10., ..., -8., -8., -8.], + [ -9., -9., -10., ..., -7., -8., -8.], + [ -9., -9., -10., ..., -7., -8., -8.]]]], dtype=float32), array([[[[-127., -127., -128., ..., -121., -124., -126.], + [-127., -127., -128., ..., -121., -124., -126.], + [-127., -127., -128., ..., -121., -124., -126.], + ..., + [-128., -128., -128., ..., -96., -101., -104.], + [-128., -128., -128., ..., -113., -118., -120.], + [-128., -128., -128., ..., -123., -126., -126.]], + + [[ -1., -1., 1., ..., -3., -3., -3.], + [ -1., -1., 1., ..., -3., -3., -3.], + [ -1., -1., -1., ..., -3., -3., -3.], + ..., + [ 0., 0., 0., ..., 2., 2., 2.], + [ 0., 0., 0., ..., 2., 2., 2.], + [ 0., 0., 0., ..., 2., 2., 2.]], + + [[ -1., -1., -1., ..., -3., -3., -3.], + [ -1., -1., -1., ..., -3., -3., -3.], + [ -1., -1., -1., ..., -3., -3., -3.], + ..., + [ 0., 0., 0., ..., -6., -6., -6.], + [ 0., 0., 0., ..., -6., -5., -5.], + [ 0., 0., 0., ..., -6., -5., -5.]]]], dtype=float32), array([[[[ 14., 14., 14., ..., -15., -16., -16.], + [ 15., 15., 15., ..., -15., -15., -15.], + [ 15., 15., 16., ..., -16., -16., -16.], + ..., + [ -29., -29., -29., ..., -114., -114., -114.], + [ -29., -29., -29., ..., -114., -114., -114.], + [ -28., -28., -28., ..., -115., -115., -115.]], + + [[ -11., -11., -11., ..., -7., -7., -7.], + [ -11., -11., -11., ..., -7., -7., -7.], + [ -11., -11., -11., ..., -7., -7., -7.], + ..., + [ -6., -6., -6., ..., -4., -4., -4.], + [ -6., -6., -6., ..., -4., -4., -4.], + [ -6., -6., -6., ..., -4., -4., -4.]], + + [[ 6., 6., 6., ..., 1., 1., 1.], + [ 6., 6., 6., ..., 1., 1., 1.], + [ 5., 5., 5., ..., 0., 0., 0.], + ..., + [ -6., -6., -6., ..., -4., -4., -4.], + [ -6., -6., -6., ..., -4., -4., -4.], + [ -6., -6., -6., ..., -4., -4., -4.]]]], dtype=float32), array([[[[-114., -114., -115., ..., -31., -24., -19.], + [-114., -114., -115., ..., -18., -15., -12.], + [-114., -114., -115., ..., -9., -9., -9.], + ..., + [ -9., -9., -7., ..., -46., -49., -51.], + [ -9., -9., -9., ..., -64., -67., -70.], + [ -9., -10., -10., ..., -77., -81., -84.]], + + [[ -3., -3., -3., ..., -14., -14., -14.], + [ -3., -3., -3., ..., -14., -14., -14.], + [ -3., -3., -3., ..., -15., -15., -15.], + ..., + [ 2., 2., 2., ..., 3., 3., 3.], + [ 2., 2., 2., ..., 6., 6., 6.], + [ 2., 2., 2., ..., 6., 6., 6.]], + + [[ -6., -6., -6., ..., 0., 0., 0.], + [ -6., -6., -6., ..., 0., 0., 0.], + [ -6., -6., -6., ..., 1., 1., 1.], + ..., + [ -6., -6., -6., ..., -8., -8., -8.], + [ -6., -6., -6., ..., -9., -9., -9.], + [ -6., -6., -6., ..., -9., -9., -9.]]]], dtype=float32), array([[[[ -3., -3., -3., ..., -89., -89., -90.], + [ -3., -2., -3., ..., -89., -89., -90.], + [ -3., -3., -3., ..., -89., -89., -90.], + ..., + [ -3., -3., -3., ..., -125., -125., -125.], + [ -3., -3., -3., ..., -126., -126., -126.], + [ -2., -2., -2., ..., -125., -125., -125.]], + + [[ -16., -16., -16., ..., -23., -23., -23.], + [ -16., -16., -16., ..., -23., -23., -23.], + [ -15., -15., -15., ..., -23., -23., -23.], + ..., + [ -3., -3., -3., ..., -1., -1., -1.], + [ -2., -2., -2., ..., -2., -2., -2.], + [ -2., -2., -2., ..., -2., -2., -2.]], + + [[ 4., 4., 4., ..., -5., -5., -5.], + [ 4., 4., 4., ..., -5., -5., 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1., 1., ..., -3., -3., -3.], + [ 1., 1., 1., ..., -3., -3., -3.], + [ 1., 1., 1., ..., -3., -3., -3.]], + + [[ -3., -3., -2., ..., 0., 0., 0.], + [ -3., -3., -2., ..., 0., 0., 0.], + [ -3., -3., -2., ..., -1., -1., -1.], + ..., + [ -10., -10., -10., ..., -4., -4., -4.], + [ -11., -11., -11., ..., -4., -4., -4.], + [ -11., -11., -11., ..., -4., -4., -4.]]]], dtype=float32), array([[[[-100., -99., -97., ..., -44., -45., -46.], + [ -99., -98., -97., ..., -44., -45., -46.], + [ -99., -98., -97., ..., -44., -45., -46.], + ..., + [ 7., 7., 7., ..., -97., -97., -98.], + [ 7., 7., 7., ..., -97., -98., -97.], + [ 7., 7., 7., ..., -96., -96., -96.]], + + [[ -7., -7., -7., ..., 2., 2., 2.], + [ -7., -7., -7., ..., 2., 2., 2.], + [ -7., -7., -7., ..., 3., 3., 3.], + ..., + [ -11., -11., -11., ..., -7., -7., -7.], + [ -11., -11., -11., ..., -6., -6., -6.], + [ -11., -11., -11., ..., -6., -6., -6.]], + + [[ -6., -6., -6., ..., -11., -11., -11.], + [ -6., -6., -6., ..., -11., -11., -11.], + [ -6., -6., -6., ..., -11., -11., -11.], + ..., + [ -3., -3., -3., ..., -4., -4., -4.], + [ -3., -3., -3., ..., -5., -5., -5.], + [ -3., -3., -3., ..., -5., -5., -5.]]]], dtype=float32), array([[[[ -76., -76., -75., ..., -84., -83., -83.], + [ -80., -80., -79., ..., -84., -83., -83.], + [ -85., -85., -85., ..., -84., -83., -83.], + ..., + [ -17., -17., -17., ..., -128., -128., -128.], + [ -17., -17., -17., ..., -128., -128., -128.], + [ -17., -17., -17., ..., -128., -128., -128.]], + + [[ -25., -25., -25., ..., -20., -20., -20.], + [ -25., -25., -25., ..., -20., -20., -20.], + [ -22., -22., -22., ..., -20., -20., -20.], + ..., + [ 1., 1., 1., ..., 2., 2., 2.], + [ 1., 1., 1., ..., 0., 0., 0.], + [ 1., 1., 1., ..., 0., 0., 0.]], + + [[ 4., 4., 4., ..., -3., -4., -4.], + [ 4., 4., 4., ..., -3., -4., -4.], + [ 3., 3., 3., ..., -3., -4., -4.], + ..., + [ -10., -10., -8., ..., -2., -1., -1.], + [ -10., -10., -8., ..., 0., 0., 0.], + [ -10., -10., -8., ..., 0., 0., 0.]]]], dtype=float32), array([[[[ 8., 8., 9., ..., -19., -19., -19.], + [ 9., 9., 9., ..., -18., -18., -18.], + [ 9., 9., 9., ..., -17., -17., -17.], + ..., + [ -29., -26., -24., ..., -115., -115., -115.], + [ -27., -25., -23., ..., -115., -115., -115.], + [ -26., -24., -22., ..., -115., -115., -115.]], + + [[ -12., -12., -14., ..., -8., -7., -7.], + [ -12., -12., -14., ..., -8., -7., -7.], + [ -13., -13., -14., ..., -8., -7., -7.], + ..., + [ -4., -4., -3., ..., -3., -3., -3.], + [ -3., -3., -3., ..., -3., -3., -3.], + [ -3., -3., -3., ..., -3., -3., -3.]], + + [[ 5., 5., 4., ..., 0., 0., 0.], + [ 5., 5., 4., ..., 0., 0., 0.], + [ 4., 4., 4., ..., -1., -1., -1.], + ..., + [ -9., -9., -7., ..., -4., -4., -4.], + [ -9., -9., -7., ..., -3., -3., -3.], + [ -9., -9., -7., ..., -3., -3., -3.]]]], dtype=float32), array([[[[-128., -128., -128., ..., -53., -53., -56.], + [-127., -127., -128., ..., -53., -53., -55.], + [-125., -125., -126., ..., -53., -52., -55.], + ..., + [ -25., -29., -32., ..., -128., -128., -128.], + [ -26., -29., -33., ..., -128., -128., -128.], + [ -25., -29., -33., ..., -128., -128., -128.]], + + [[ 2., 2., 2., ..., -7., -10., -10.], + [ 2., 2., 2., ..., -7., -10., -10.], + [ 2., 2., 2., ..., -7., -8., -8.], + ..., + [ -22., -22., -22., ..., 1., 1., 1.], + [ -23., -23., -23., ..., 0., 0., 0.], + [ -23., -23., -23., ..., 0., 0., 0.]], + + [[ -1., -1., -1., ..., -8., -8., -8.], + [ -1., -1., -1., ..., -8., -8., -8.], + [ -1., -1., -1., ..., -8., -8., -8.], + ..., + [ 4., 4., 4., ..., -1., -1., -1.], + [ 4., 4., 4., ..., 0., 0., 0.], + [ 4., 4., 4., ..., 0., 0., 0.]]]], dtype=float32)]}}, 'hbdk_dict': {'hbdk_pass_through_params': '--O3 --debug --core-num 1 --fast --jobs 8 ', 'input-source': {'images': 'pyramid', '_default_value': 'ddr'}}, 'node_dict': {}, 'check_mode': False, 'optimization': ['set_Softmax_input_int8,set_Softmax_output_int8']} +2026-08-07 10:39:58,490 file: model_builder.py func: model_builder line No: 35 Start to Horizon NN Model Convert. +2026-08-07 10:39:58,520 file: model_debugger.py func: model_debugger line No: 67 Loading horizon_nn debug methods:set() +2026-08-07 10:39:58,522 file: quantization_config.py func: quantization_config line No: 305 The activation calibration parameters: + calibration_type: ['max', 'kl'] + max_percentile: [0.99995, 1.0] + per_channel: [True, False] + asymmetric: [True, False] +The modelwise search parameters: + similarity: 0.995 + metric: cosine-similarity +The input of all Softmax nodes are set to : int8 +2026-08-07 10:39:58,523 file: input_dict_parser.py func: input_dict_parser line No: 240 input images is from pyramid. Its layout is set to NHWC +2026-08-07 10:39:58,524 file: model_builder.py func: model_builder line No: 197 The specified model compilation architecture: bayes-e. +2026-08-07 10:39:58,524 file: model_builder.py func: model_builder line No: 207 The specified model compilation optimization parameters: []. +2026-08-07 10:39:58,525 file: model_builder.py func: model_builder line No: 35 Start to prepare the onnx model. +2026-08-07 10:39:58,609 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 10:39:58,982 file: model_builder.py func: model_builder line No: 38 End to prepare the onnx model. +2026-08-07 10:39:59,024 file: model_builder.py func: model_builder line No: 265 Saving model to: best_bpu_bayese_640x640_nv12_original_float_model.onnx. +2026-08-07 10:39:59,025 file: model_builder.py func: model_builder line No: 35 Start to optimize the onnx model. +2026-08-07 10:39:59,210 file: constant_folding.py func: constant_folding line No: 66 Summary info for constant_folding: +2026-08-07 10:39:59,210 file: constant_folding.py func: constant_folding line No: 67 After constant_folding, the number of nodes has changed from 356 to 356. +2026-08-07 10:39:59,210 file: constant_folding.py func: constant_folding line No: 71 After constant_folding, the number of parameters has changed from 2375641 to 2375641. +2026-08-07 10:39:59,210 file: constant_folding.py func: constant_folding line No: 76 Detailed info for constant_folding: +2026-08-07 10:39:59,211 file: constant_folding.py func: constant_folding line No: 88 +2026-08-07 10:39:59,714 file: model_builder.py func: model_builder line No: 38 End to optimize the onnx model. +2026-08-07 10:39:59,751 file: model_builder.py func: model_builder line No: 265 Saving model to: best_bpu_bayese_640x640_nv12_optimized_float_model.onnx. +2026-08-07 10:39:59,752 file: model_builder.py func: model_builder line No: 35 Start to calibrate the model. +2026-08-07 10:40:00,033 file: calibration_data_set.py func: calibration_data_set line No: 111 input name: images, number_of_samples: 50 +2026-08-07 10:40:00,033 file: calibration_data_set.py func: calibration_data_set line No: 123 There are 50 samples in the data set. +2026-08-07 10:40:00,034 file: infer_thresholds.py func: infer_thresholds line No: 84 Run calibration model with modelwise search method. +2026-08-07 10:40:00,536 file: base.py func: base line No: 138 Calibration using batch 8 +2026-08-07 10:40:05,981 file: ort.py func: ort line No: 207 Reset batch_size=1 and execute forward again... +2026-08-07 10:46:16,933 file: base.py func: base line No: 138 Calibration using batch 8 +2026-08-07 10:46:18,673 file: ort.py func: ort line No: 207 Reset batch_size=1 and execute forward again... +2026-08-07 10:46:36,389 file: base.py func: base line No: 138 Calibration using batch 8 +2026-08-07 10:46:41,254 file: ort.py func: ort line No: 207 Reset batch_size=1 and execute forward again... +2026-08-07 10:53:54,824 file: modelwise_search.py func: modelwise_search line No: 75 Select max-percentile:percentile=0.99995 method. +2026-08-07 10:53:55,891 file: model_builder.py func: model_builder line No: 38 End to calibrate the model. +2026-08-07 10:53:56,028 file: model_builder.py func: model_builder line No: 265 Saving model to: best_bpu_bayese_640x640_nv12_calibrated_model.onnx. +2026-08-07 10:53:56,028 file: model_builder.py func: model_builder line No: 35 Start to quantize the model. +2026-08-07 10:53:58,869 file: constant_folding.py func: constant_folding line No: 66 Summary info for constant_folding: +2026-08-07 10:53:58,869 file: constant_folding.py func: constant_folding line No: 67 After constant_folding, the number of nodes has changed from 309 to 309. +2026-08-07 10:53:58,869 file: constant_folding.py func: constant_folding line No: 71 After constant_folding, the number of parameters has changed from 2407371 to 2407371. +2026-08-07 10:53:58,870 file: constant_folding.py func: constant_folding line No: 76 Detailed info for constant_folding: +2026-08-07 10:53:58,870 file: constant_folding.py func: constant_folding line No: 88 +2026-08-07 10:53:59,227 file: model_builder.py func: model_builder line No: 38 End to quantize the model. +2026-08-07 10:53:59,354 file: model_builder.py func: model_builder line No: 265 Saving model to: best_bpu_bayese_640x640_nv12_quantized_model.onnx. +2026-08-07 10:53:59,355 file: model_builder.py func: model_builder line No: 35 Start to compile the model with march bayes-e. +2026-08-07 10:54:00,099 file: hybrid_build.py func: hybrid_build line No: 111 Compile submodel: Extracted from {main_graph}_subgraph_0 +2026-08-07 10:54:00,148 file: hbdk_cc.py func: hbdk_cc line No: 126 hbdk-cc parameters:['--O3', '--debug', '--core-num', '1', '--fast', '--jobs', '8', '--input-layout', 'NHWC', '--output-layout', 'NHWC', '--input-source', 'pyramid'] +2026-08-07 10:54:00,149 file: hbdk_cc.py func: hbdk_cc line No: 127 hbdk-cc command used:hbdk-cc -f hbir -m /tmp/tmpn1xm3lyk/Extracted from {main_graph}_subgraph_0.hbir -o /tmp/tmpn1xm3lyk/Extracted from {main_graph}_subgraph_0.hbm --march bayes-e --progressbar --O3 --debug --core-num 1 --fast --jobs 8 --input-layout NHWC --output-layout NHWC --input-source pyramid +2026-08-07 10:59:35,665 file: tool_utils.py func: tool_utils line No: 326 consumed time 335.296 +2026-08-07 10:59:35,998 file: tool_utils.py func: tool_utils line No: 326 FPS=112.19, latency = 8913.1 us, DDR = 20676096 bytes (see Extracted from {main_graph}_subgraph_0.html) +2026-08-07 10:59:36,279 file: model_builder.py func: model_builder line No: 38 End to compile the model with march bayes-e. +2026-08-07 10:59:40,750 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 +-------------------------------------------------------------------------------------------------------------------------------------- +HZ_PREPROCESS_FOR_images BPU id(0) HzSQuantizedPreprocess 1.000036 127.0 int8 +/model.0/conv/Conv BPU id(0) HzSQuantizedConv 0.999420 1.01336 int8 +/model.0/act/Mul BPU id(0) HzLut 0.999356 41.2085 int8 +/model.1/conv/Conv BPU id(0) HzSQuantizedConv 0.994858 34.6575 int8 +/model.1/act/Mul BPU id(0) HzLut 0.994586 77.3055 int8 +/model.2/cv1/conv/Conv BPU id(0) HzSQuantizedConv 0.988316 61.1196 int8 +/model.2/cv1/act/Mul BPU id(0) HzLut 0.988277 58.76 int8 +/model.2/Split BPU id(0) Split 0.987462 41.5502 int8 +/model.2/m.0/cv1/conv/Conv BPU id(0) HzSQuantizedConv 0.997807 41.5502 int8 +/model.2/m.0/cv1/act/Mul BPU id(0) HzLut 0.997295 6.48102 int8 +/model.2/m.0/cv2/conv/Conv BPU id(0) HzSQuantizedConv 0.979294 4.49225 int8 +/model.2/m.0/cv2/act/Mul BPU id(0) HzLut 0.984540 38.6259 int8 +/model.2/m.0/Add BPU id(0) HzSElementwiseAdd 0.989001 41.5502 int8 +/model.2/Split_output_0_calibrated_Requantize BPU id(0) HzRequantize -- -- int8 +/model.2/Split_output_1_calibrated_Requantize BPU id(0) HzRequantize -- -- int8 +/model.2/Concat BPU id(0) Concat 0.988635 41.5502 int8 +/model.2/cv2/conv/Conv BPU id(0) HzSQuantizedConv 0.984512 42.3831 int8 +/model.2/cv2/act/Mul BPU id(0) HzLut 0.983102 46.6969 int8 +/model.3/conv/Conv BPU id(0) HzSQuantizedConv 0.990522 13.5453 int8 +/model.3/act/Mul BPU id(0) HzLut 0.994629 8.41636 int8 +/model.4/cv1/conv/Conv BPU id(0) HzSQuantizedConv 0.993375 7.23656 int8 +/model.4/cv1/act/Mul BPU id(0) HzLut 0.993696 6.07195 int8 +/model.4/Split BPU id(0) Split 0.992764 4.76361 int8 +/model.4/m.0/cv1/conv/Conv BPU id(0) HzSQuantizedConv 0.993655 4.76361 int8 +/model.4/m.0/cv1/act/Mul BPU id(0) HzLut 0.994053 4.97631 int8 +/model.4/m.0/cv2/conv/Conv BPU id(0) HzSQuantizedConv 0.994427 4.93203 int8 +/model.4/m.0/cv2/act/Mul BPU id(0) HzLut 0.994242 5.89425 int8 +/model.4/m.0/Add BPU id(0) HzSElementwiseAdd 0.996519 4.76361 int8 +/model.4/Split_output_0_calibrated_Requantize BPU id(0) HzRequantize -- -- int8 +/model.4/Split_output_1_calibrated_Requantize BPU id(0) HzRequantize -- -- int8 +/model.4/Concat BPU id(0) Concat 0.995726 4.76361 int8 +/model.4/cv2/conv/Conv BPU id(0) HzSQuantizedConv 0.986882 6.03048 int8 +/model.4/cv2/act/Mul BPU id(0) HzLut 0.984009 5.65269 int8 +/model.5/conv/Conv BPU id(0) HzSQuantizedConv 0.993324 3.11747 int8 +/model.5/act/Mul BPU id(0) HzLut 0.995369 5.72607 int8 +/model.6/cv1/conv/Conv BPU id(0) HzSQuantizedConv 0.989999 5.04224 int8 +/model.6/cv1/act/Mul BPU id(0) HzLut 0.991192 7.17241 int8 +/model.6/Split BPU id(0) Split 0.991260 4.80649 int8 +/model.6/m.0/cv1/conv/Conv BPU id(0) HzSQuantizedConv 0.993373 4.80649 int8 +/model.6/m.0/cv2/conv/Conv BPU id(0) HzSQuantizedConv 0.986195 4.80649 int8 +/model.6/m.0/cv1/act/Mul BPU id(0) HzLut 0.994111 3.73626 int8 +/model.6/m.0/cv2/act/Mul BPU id(0) HzLut 0.985150 9.58291 int8 +/model.6/m.0/m/m.0/cv1/conv/Conv BPU id(0) HzSQuantizedConv 0.991013 3.62476 int8 +/model.6/m.0/m/m.0/cv1/act/Mul BPU id(0) HzLut 0.986674 6.74554 int8 +/model.6/m.0/m/m.0/cv2/conv/Conv BPU id(0) HzSQuantizedConv 0.992821 5.26864 int8 +/model.6/m.0/m/m.0/cv2/act/Mul BPU id(0) HzLut 0.993137 5.39304 int8 +/model.6/m.0/m/m.0/Add BPU id(0) HzSElementwiseAdd 0.994573 3.62476 int8 +/model.6/m.0/m/m.1/cv1/conv/Conv BPU id(0) HzSQuantizedConv 0.993472 4.86168 int8 +/model.6/m.0/m/m.1/cv1/act/Mul BPU id(0) HzLut 0.992689 6.3859 int8 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BPU id(0) HzLut 0.932880 5.64418 int8 +...1/attn/Softmax_reducesum_FROM_QUANTIZED_SOFTMAX BPU id(0) HzSQuantizedReduceSum 0.963200 1.0 int8 +.../attn/Softmax_reciprocal_FROM_QUANTIZED_SOFTMAX BPU id(0) HzLut 0.976782 138.664 int8 +...0/m.0.1/attn/Softmax_mul_FROM_QUANTIZED_SOFTMAX BPU id(0) HzSElementwiseMul 0.973404 1.0 int8 +/model.22/m.0/m.0.1/attn/Transpose_1 BPU id(0) Transpose 0.973389 0.703209 int8 +/model.22/m.0/m.0.1/attn/MatMul_1 BPU id(0) HzSQuantizedMatmul 0.981709 8.32244 int8 +/model.22/m.0/m.0.1/attn/Reshape_1 BPU id(0) Reshape 0.981709 7.78857 int8 +/model.22/m.0/m.0.1/attn/pe/conv/Conv BPU id(0) HzSQuantizedConv 0.981477 8.32244 int8 +/model.22/m.0/m.0.1/attn/proj/conv/Conv BPU id(0) HzSQuantizedConv 0.981540 7.95935 int8 +/model.22/m.0/m.0.1/ffn/ffn.0/conv/Conv BPU id(0) HzSQuantizedConv 0.990591 9.51949 int8 +/model.22/m.0/m.0.1/ffn/ffn.0/act/Mul BPU id(0) HzLut 0.979219 14.447 int8 +/model.22/m.0/m.0.1/ffn/ffn.1/conv/Conv BPU id(0) HzSQuantizedConv 0.980551 7.85633 int8 +/model.22/Split_output_0_calibrated_Requantize BPU id(0) HzRequantize -- -- int8 +/model.22/Split_output_1_calibrated_Requantize BPU id(0) HzRequantize -- -- int8 +/model.22/Concat BPU id(0) Concat 0.981000 8.30991 int8 +/model.22/cv2/conv/Conv BPU id(0) HzSQuantizedConv 0.990501 9.72894 int8 +/model.22/cv2/act/Mul BPU id(0) HzLut 0.990327 15.4476 int8 +/model.23/one2one_cv2.2/one2one_cv2.2.0/conv/Conv BPU id(0) HzSQuantizedConv 0.997510 11.1421 int8 +...3.2/one2one_cv3.2.0/one2one_cv3.2.0.0/conv/Conv BPU id(0) HzSQuantizedConv 0.987130 11.1421 int8 +/model.23/one2one_cv2.2/one2one_cv2.2.0/act/Mul BPU id(0) HzLut 0.998104 7.45722 int8 +...cv3.2/one2one_cv3.2.0/one2one_cv3.2.0.0/act/Mul BPU id(0) HzLut 0.986272 13.8882 int8 +/model.23/one2one_cv2.2/one2one_cv2.2.1/conv/Conv BPU id(0) HzSQuantizedConv 0.994880 7.45292 int8 +...3.2/one2one_cv3.2.0/one2one_cv3.2.0.1/conv/Conv BPU id(0) HzSQuantizedConv 0.985228 12.588 int8 +/model.23/one2one_cv2.2/one2one_cv2.2.1/act/Mul BPU id(0) HzLut 0.994962 7.15209 int8 +...cv3.2/one2one_cv3.2.0/one2one_cv3.2.0.1/act/Mul BPU id(0) HzLut 0.980727 9.08317 int8 +/model.23/one2one_cv2.2/one2one_cv2.2.2/Conv BPU id(0) HzSQuantizedConv 0.999024 7.06212 int8 +...3.2/one2one_cv3.2.1/one2one_cv3.2.1.0/conv/Conv BPU id(0) HzSQuantizedConv 0.980994 7.83007 int8 +...cv3.2/one2one_cv3.2.1/one2one_cv3.2.1.0/act/Mul BPU id(0) HzLut 0.981529 23.5955 int8 +...3.2/one2one_cv3.2.1/one2one_cv3.2.1.1/conv/Conv BPU id(0) HzSQuantizedConv 0.979626 20.3248 int8 +...cv3.2/one2one_cv3.2.1/one2one_cv3.2.1.1/act/Mul BPU id(0) HzLut 0.978119 35.9431 int8 +/model.23/one2one_cv3.2/one2one_cv3.2.2/Conv BPU id(0) HzSQuantizedConv 0.998478 21.8894 int8 +2026-08-07 10:59:40,751 file: print_info_dict.py func: print_info_dict line No: 72 The quantized model output: +============================================================================= +Output Cosine Similarity L1 Distance L2 Distance Chebyshev Distance +----------------------------------------------------------------------------- +cls_s8 0.985422 2.081548 0.024582 73.135422 +box_s8 0.989597 0.201690 0.002376 4.414954 +cls_s16 0.989395 1.614797 0.035827 35.102242 +box_s16 0.993338 0.194142 0.004491 3.120226 +cls_s32 0.998478 0.769498 0.025959 5.004253 +box_s32 0.999024 0.123850 0.004851 0.863881 +2026-08-07 10:59:40,763 file: model_builder.py func: model_builder line No: 38 End to Horizon NN Model Convert. +2026-08-07 10:59:40,780 file: hb_mapper_makertbin.py func: hb_mapper_makertbin line No: 601 start convert to *.bin file.... +2026-08-07 10:59:41,033 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4326 ONNX model output num : 6 +2026-08-07 10:59:41,037 file: layout_util.py func: layout_util line No: 15 set_featuremap_layout start +2026-08-07 10:59:41,038 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4060 model_deps_info: {'hb_mapper_version': '1.24.3', 'hbdk_version': '3.49.15', 'hbdk_runtime_version': ' 3.15.55.0', 'horizon_nn_version': '1.1.0', 'onnx_model': '/workspace/smart_car_2026/model/x5_quantization/best_bpu.onnx', 'march': 'bayes-e', 'layer_out_dump': False, 'log_level': 'DEBUG', 'working_dir': '/workspace/smart_car_2026/model/x5_quantization/mapper_output_bpu', 'model_prefix': 'best_bpu_bayese_640x640_nv12', 'input_names': ['images'], 'input_type_rt': ['nv12'], 'input_space_and_range': ['regular'], 'input_type_train': ['rgb'], 'input_layout_rt': [''], 'input_layout_train': ['NCHW'], 'norm_type': ['data_scale'], 'scale_value': ['0.003921568627451,'], 'mean_value': [''], 'input_shape': ['1x3x640x640'], 'input_batch': [], 'cal_dir': ['/workspace/smart_car_2026/model/x5_quantization/calibration_data'], 'cal_data_type': ['float32'], 'preprocess_on': False, 'calibration_type': 'default', 'per_channel': 'False', 'optimization': ['set_Softmax_input_int8,set_Softmax_output_int8'], 'hbdk_params': {'hbdk_pass_through_params': '--O3 --debug --core-num 1 --fast --jobs 8 ', 'input-source': {'images': 'pyramid', '_default_value': 'ddr'}}, 'debug': True, 'compile_mode': 'latency'} +2026-08-07 10:59:41,040 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4183 ############# model deps info ############# +2026-08-07 10:59:41,041 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4184 hb_mapper version : 1.24.3 +2026-08-07 10:59:41,041 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4187 hbdk version : 3.49.15 +2026-08-07 10:59:41,042 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4189 hbdk runtime version: 3.15.55.0 +2026-08-07 10:59:41,042 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4192 horizon_nn version : 1.1.0 +2026-08-07 10:59:41,043 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4196 ############# model_parameters info ############# +2026-08-07 10:59:41,044 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4202 onnx_model : /workspace/smart_car_2026/model/x5_quantization/best_bpu.onnx +2026-08-07 10:59:41,044 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4203 BPU march : bayes-e +2026-08-07 10:59:41,044 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4204 layer_out_dump : False +2026-08-07 10:59:41,045 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4205 log_level : DEBUG +2026-08-07 10:59:41,045 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4206 working dir : /workspace/smart_car_2026/model/x5_quantization/mapper_output_bpu +2026-08-07 10:59:41,045 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4207 output_model_file_prefix: best_bpu_bayese_640x640_nv12 +2026-08-07 10:59:41,046 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4228 ############# input_parameters info ############# +2026-08-07 10:59:41,046 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4246 ------------------------------------------ +2026-08-07 10:59:41,046 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4248 ---------input info : images --------- +2026-08-07 10:59:41,047 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4249 input_name : images +2026-08-07 10:59:41,047 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4250 input_type_rt : nv12 +2026-08-07 10:59:41,047 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4252 input_space&range : regular +2026-08-07 10:59:41,048 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4254 input_layout_rt : None +2026-08-07 10:59:41,048 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4255 input_type_train : rgb +2026-08-07 10:59:41,048 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4256 input_layout_train : NCHW +2026-08-07 10:59:41,049 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4257 norm_type : data_scale +2026-08-07 10:59:41,049 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4258 input_shape : 1x3x640x640 +2026-08-07 10:59:41,049 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4266 scale_value : 0.003921568627451, +2026-08-07 10:59:41,050 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4268 cal_data_dir : /workspace/smart_car_2026/model/x5_quantization/calibration_data +2026-08-07 10:59:41,050 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4270 cal_data_type : float32 +2026-08-07 10:59:41,050 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4271 ---------input info : images end ------- +2026-08-07 10:59:41,051 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4272 ------------------------------------------ +2026-08-07 10:59:41,051 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4274 ############# calibration_parameters info ############# +2026-08-07 10:59:41,051 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4275 preprocess_on : False +2026-08-07 10:59:41,051 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4276 calibration_type: : default +2026-08-07 10:59:41,052 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4278 optimization : set_Softmax_input_int8,set_Softmax_output_int8; +2026-08-07 10:59:41,052 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4284 per_channel : False +2026-08-07 10:59:41,052 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4303 ############# compiler_parameters info ############# +2026-08-07 10:59:41,053 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4305 debug : True +2026-08-07 10:59:41,053 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4307 compile_mode : latency +2026-08-07 10:59:41,053 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4310 hbdk_pass_through_params: --O3 --debug --core-num 1 --fast --jobs 8 +2026-08-07 10:59:41,054 file: onnx2horizonrt.py func: onnx2horizonrt line No: 4310 input-source : {'images': 'pyramid', '_default_value': 'ddr'} +2026-08-07 10:59:41,062 file: hb_mapper_makertbin.py func: hb_mapper_makertbin line No: 783 Convert to runtime bin file successfully! +2026-08-07 10:59:41,063 file: hb_mapper_makertbin.py func: hb_mapper_makertbin line No: 784 End Model Convert diff --git a/x5_quantization/mapper_output_bpu/Extracted from {main_graph}_subgraph_0.html b/x5_quantization/mapper_output_bpu/Extracted from {main_graph}_subgraph_0.html new file mode 100644 index 0000000..08613f3 --- /dev/null +++ b/x5_quantization/mapper_output_bpu/Extracted from {main_graph}_subgraph_0.html @@ -0,0 +1,983 @@ + + +Extracted from {main_graph}_subgraph_0 + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/x5_quantization/mapper_output_bpu/Extracted from {main_graph}_subgraph_0.json b/x5_quantization/mapper_output_bpu/Extracted from {main_graph}_subgraph_0.json new file mode 100644 index 0000000..23c7bdb --- /dev/null +++ b/x5_quantization/mapper_output_bpu/Extracted from {main_graph}_subgraph_0.json @@ -0,0 +1,2984 @@ +{ + "summary": { + "BPU OPs per frame (effective)": 5320499200, + "BPU OPs per run (effective)": 5320499200, + "BPU PE number": 1, + "BPU core number": 1, + "BPU march": "B25E", + "DDR bytes per frame": 20676096, + "DDR bytes per run": 20676096, + "DDR bytes per second": 2319742922, + "DDR megabytes per frame": 19.718, + "DDR megabytes per run": 19.718, + "DDR megabytes per second": 2212.3, + "FPS": 112.19, + "HBDK version": "3.49.15", + "compiling options": "-f hbir -m /tmp/tmpn1xm3lyk/Extracted from {main_graph}_subgraph_0.hbir -o /tmp/tmpn1xm3lyk/Extracted from {main_graph}_subgraph_0.hbm --march bayes-e --progressbar --O3 --debug --core-num 1 --fast --jobs 8 --input-layout NHWC --output-layout NHWC --input-source pyramid", + "frame per run": 1, + "frame per second": 112.19, + "input features": [ + [ + "input name", + "input size" + ], + [ + "images", + "1x640x640x3" + ] + ], + "interval computing unit utilization": [ + 0.88, + 0.759, + 0.961, + 0.96, + 0.983, + 0.963, + 0.984, + 0.98, + 0.986, + 0.989, + 0.848, + 0.679, + 0.814, + 0.922, + 0.919, + 0.921, + 0.936, + 0.704, + 0.988, + 0.989, + 0.989, + 0.989, + 0.848, + 0.891, + 0.808, + 0.964, + 0.913, + 0.87, + 0.953, + 0.954, + 0.987, + 0.808, + 0.656, + 0.735, + 0.874, + 0.876, + 0.877, + 0.89, + 0.785, + 0.827, + 0.99, + 0.989, + 0.989, + 0.914, + 0.483 + ], + "interval computing units utilization": [ + 0.88, + 0.759, + 0.961, + 0.96, + 0.983, + 0.963, + 0.984, + 0.98, + 0.986, + 0.989, + 0.848, + 0.679, + 0.814, + 0.922, + 0.919, + 0.921, + 0.936, + 0.704, + 0.988, + 0.989, + 0.989, + 0.989, + 0.848, + 0.891, + 0.808, + 0.964, + 0.913, + 0.87, + 0.953, + 0.954, + 0.987, + 0.808, + 0.656, + 0.735, + 0.874, + 0.876, + 0.877, + 0.89, + 0.785, + 0.827, + 0.99, + 0.989, + 0.989, + 0.914, + 0.483 + ], + "interval loading bandwidth (megabytes/s)": [ + 3217, + 2607, + 1877, + 1030, + 553, + 1727, + 2476, + 1151, + 0, + 0, + 32, + 34, + 655, + 1442, + 1581, + 1585, + 1661, + 3629, + 2795, + 33, + 0, + 0, + 1730, + 2726, + 2503, + 1649, + 279, + 917, + 1215, + 436, + 0, + 7, + 7, + 650, + 1368, + 1437, + 1442, + 1331, + 3316, + 4345, + 1635, + 0, + 0, + 1150, + 1844 + ], + "interval number": 45, + "interval storing bandwidth (megabytes/s)": [ + 3320, + 1953, + 292, + 0, + 1494, + 2294, + 946, + 292, + 146, + 0, + 772, + 2593, + 2815, + 1663, + 1340, + 1342, + 1174, + 503, + 24, + 244, + 441, + 463, + 315, + 73, + 0, + 0, + 244, + 488, + 805, + 717, + 156, + 781, + 3177, + 3618, + 1888, + 1334, + 1360, + 1333, + 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--- /dev/null +++ b/x5_quantization/postprocess_yolo26.py @@ -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) diff --git a/x5_quantization/prepare_calibration.py b/x5_quantization/prepare_calibration.py new file mode 100644 index 0000000..c54cdc0 --- /dev/null +++ b/x5_quantization/prepare_calibration.py @@ -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() diff --git a/x5_quantization/quantize_x5.sh b/x5_quantization/quantize_x5.sh new file mode 100755 index 0000000..8d27081 --- /dev/null +++ b/x5_quantization/quantize_x5.sh @@ -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 + '