mirror of
https://github.com/RapidAI/RapidOCR.git
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Cursor AgentandDaniel
3622c4598e
Expose the PP-OCRv6 engine through a stable C ABI and installable shared and static libraries, plus a ctypes Python package that follows the RapidOCR call shape. Keep AVX-512 out of the AVX2 object file and speed up GEMM accumulate and the AArch64 GEMM tile. Co-authored-by: Daniel <znsoft@163.com>
86 lines
3.1 KiB
C++
86 lines
3.1 KiB
C++
#include "kernels.hpp"
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#include "ppocr/ppocr.hpp"
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#include <chrono>
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#include <cstdlib>
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#include <iostream>
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#include <string>
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#include <vector>
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namespace {
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template <class Fn>
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double TimeMs(Fn&& fn, int warmup, int runs) {
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for (int i = 0; i < warmup; ++i) fn();
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const auto begin = std::chrono::steady_clock::now();
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for (int i = 0; i < runs; ++i) fn();
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return std::chrono::duration<double, std::milli>(
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std::chrono::steady_clock::now() - begin)
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.count() /
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runs;
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}
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} // namespace
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int main(int argc, char** argv) {
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const auto cpu = ppocr::QueryCpuInfo();
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std::cout << "{\n"
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<< " \"active_isa\": \"" << cpu.active_isa << "\",\n"
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<< " \"avx2\": " << (cpu.avx2 ? "true" : "false") << ",\n"
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<< " \"avx512\": " << (cpu.avx512 ? "true" : "false") << ",\n"
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<< " \"neon\": " << (cpu.neon ? "true" : "false") << ",\n"
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<< " \"threads\": " << cpu.threads << ",\n";
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using ppocr::detail::kernels::Gemm;
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using ppocr::detail::kernels::GemmAccumulate;
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using ppocr::detail::kernels::WriteIdentityRgbToNchw;
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constexpr int rows = 32;
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constexpr int cols = 256;
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constexpr int depth = 256;
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std::vector<float> a(static_cast<std::size_t>(rows) * depth);
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std::vector<float> b(static_cast<std::size_t>(depth) * cols);
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std::vector<float> bias(cols, 0.1F);
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std::vector<float> c(static_cast<std::size_t>(rows) * cols, 0.F);
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for (std::size_t i = 0; i < a.size(); ++i) a[i] = float(int(i % 13) - 6) * 0.05F;
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for (std::size_t i = 0; i < b.size(); ++i) b[i] = float(int(i % 11) - 5) * 0.04F;
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const double gemm_ms = TimeMs([&] {
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Gemm(c.data(), a.data(), b.data(), bias.data(), rows, cols, depth);
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}, 2, 8);
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const double acc_ms = TimeMs([&] {
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GemmAccumulate(c.data(), a.data(), b.data(), rows, cols, depth);
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}, 2, 8);
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constexpr int width = 960;
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constexpr int height = 544;
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const float scale[3] = {1.F / (255.F * .229F), 1.F / (255.F * .224F), 1.F / (255.F * .225F)};
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const float shift[3] = {-.485F / .229F, -.456F / .224F, -.406F / .225F};
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std::vector<std::uint8_t> rgb(static_cast<std::size_t>(width) * height * 3, 128);
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std::vector<float> nchw(static_cast<std::size_t>(3) * height * width);
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const double rgb_ms = TimeMs([&] {
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WriteIdentityRgbToNchw(nchw.data(), rgb.data(), width, height, width, 0, 0,
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scale, shift, width);
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}, 1, 4);
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std::cout << " \"gemm_ms\": " << gemm_ms << ",\n"
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<< " \"gemm_accumulate_ms\": " << acc_ms << ",\n"
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<< " \"identity_rgb_ms\": " << rgb_ms;
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if (argc == 6) {
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try {
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ppocr::Options options;
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options.backend = ppocr::Backend::cpu_only;
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const auto image = ppocr::LoadPPM(argv[4]);
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ppocr::OCR ocr(argv[1], argv[2], argv[3], options);
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const int runs = std::stoi(argv[5]);
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const double ocr_ms = TimeMs([&] { (void)ocr.Recognize(image); }, 1, runs);
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const auto boxes = ocr.Recognize(image).size();
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std::cout << ",\n \"ocr_ms\": " << ocr_ms << ",\n \"boxes\": " << boxes;
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} catch (const std::exception& ex) {
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std::cerr << "error: " << ex.what() << '\n';
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return 1;
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}
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}
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std::cout << "\n}\n";
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return 0;
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}
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