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| 1 ONNX 能被指定结构框选node 如nn.mha 算子在netron中 自动按颜色进行选取 | |
| 2 |
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| /************************************************************** | |
| # * @Author: ljw | |
| # * @Date: 2026-04-19 10:14:11 | |
| # * @Last Modified by: ljw | |
| # * @Last Modified time: 2026-06-25 14:34:02 | |
| # **************************************************************/ | |
| #include <vector> | |
| #include <algorithm> |
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| #include <vector> | |
| #include <algorithm> | |
| #include <shared_mutex> | |
| #include <optional> | |
| #include <cmath> | |
| #include <mutex> | |
| #include <iostream> | |
| #include <iomanip> | |
| struct DataPoint { |
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| #include <stdio.h> | |
| #include <cmath> | |
| #include <iostream> | |
| /* | |
| def round_by_factor(number: int, factor: int) -> int: | |
| """Returns the closest integer to 'number' that is divisible by 'factor'.""" | |
| return round(number / factor) * factor | |
| factor=32 |
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| #include <iostream> | |
| #include <algorithm> | |
| #include <deque> | |
| #include <stdint.h> | |
| struct LocalPoseLite{ | |
| uint64_t measurement_time; | |
| LocalPoseLite(uint64_t t){ |
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| #include <iostream> | |
| #include <queue> | |
| int main() { | |
| struct DrInfo { | |
| int64_t timestamp; | |
| }; | |
| std::queue<DrInfo> dr_queue_; | |
| std::queue<DrInfo> dr_queue2_; |
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| #include <iostream> | |
| #include <experimental/filesystem> | |
| namespace fs = std::experimental::filesystem; | |
| void ensure_parent_exists(const std::string& filepath) { | |
| fs::path p(filepath); | |
| fs::path parent = p.parent_path(); | |
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| import numpy as np | |
| with open('chw888.bin', 'rb') as f: | |
| raw_data = f.read() | |
| array = np.frombuffer(raw_data, dtype=np.uint8) | |
| n=3 | |
| h=544 | |
| w=960 | |
| c=3 |
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| #include <iostream> | |
| #include <stdint.h> | |
| #include <bitset> | |
| uint32_t SetBit(uint32_t position) { | |
| uint32_t num = 0; | |
| num |= (1 << position); | |
| return num; | |
| } |
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| int tnbytes = h * w; | |
| // std::vector<cv::Mat> tchannels; | |
| // cv::split(img_bgr, tchannels); | |
| // std::cout << "宽度: " << tchannels[0].cols << std::endl; | |
| // std::cout << "高度: " << tchannels[0].rows << std::endl; | |
| // std::cout << "通道数: " << tchannels[0].channels() << std::endl; | |
| // std::cout << "数据类型: " << tchannels[0].type() << " ---- " << CV_8UC1 << std::endl; | |
| // std::cout << "深度: " << tchannels[0].depth() << std::endl; | |
| // std::cout << "尺寸: " << tchannels[0].size() << std::endl; | |
| // std::cout << "是否连续存储: " << (tchannels[0].isContinuous() ? "是" : "否") << std::endl; |
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