docs: Update README and compilation guides for clarity and consistency, including path corrections and improved formatting. Add copyright notices to source files and adjust file permissions for several scripts and directories.

This commit is contained in:
dian.yuan 2026-02-28 11:06:26 +08:00
parent f960c5030d
commit bd891a96dd
136 changed files with 14413 additions and 9399 deletions

0
examples/blazepose_detect/cpp/.gitkeep Normal file → Executable file
View file

View file

@ -0,0 +1,77 @@
#!/bin/bash
set -e
#
# Copyright (C) 20242025 Amlogic, Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
usage() {
echo "Usage: $0 [-a <target_abi>]"
echo " -a <target_abi> : Target ABI (default: arm64-v8a)"
echo " -h : Show this help message"
exit 1
}
# Default values
TARGET_ABI=arm64-v8a
# Parse arguments
while getopts 'a:h' opt; do
case "$opt" in
a)
TARGET_ABI=$OPTARG
;;
h)
usage
;;
*)
usage
;;
esac
done
if [ -z "${ANDROID_NDK_PATH}" ]; then
if [ -n "${ANDROID_NDK}" ]; then
ANDROID_NDK_PATH=${ANDROID_NDK}
elif [ -n "${ANDROID_NDK_HOME}" ]; then
ANDROID_NDK_PATH=${ANDROID_NDK_HOME}
else
echo "Error: ANDROID_NDK_PATH is not set."
echo "Please set ANDROID_NDK_PATH to your Android NDK directory."
exit 1
fi
fi
ROOT_PWD=$(cd "$(dirname $0)" && pwd)
BUILD_DIR=${ROOT_PWD}/build/android
echo "Building for Android..."
echo "NDK_PATH: ${ANDROID_NDK_PATH}"
echo "TARGET_ABI: ${TARGET_ABI}"
echo "BUILD_DIR: ${BUILD_DIR}"
mkdir -p ${BUILD_DIR}
cd ${BUILD_DIR}
cmake ../../src \
-DCMAKE_TOOLCHAIN_FILE=${ANDROID_NDK_PATH}/build/cmake/android.toolchain.cmake \
-DANDROID_ABI=${TARGET_ABI} \
-DANDROID_PLATFORM=android-24 \
-DCMAKE_BUILD_TYPE=Release \
-DOpenCV_DIR=${ROOT_PWD}/../../../dependency/opencv/opencv-android-sdk-build/sdk/native/jni/abi-${TARGET_ABI}
make -j4
echo "Build complete. Executable in ${BUILD_DIR}/blazepose_detect_demo"

View file

@ -0,0 +1,168 @@
#!/bin/bash
set -e
#
# Copyright (C) 20242025 Amlogic, Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
usage() {
echo "Usage: $0 [-m <mode>] [-a <target_arch>] [-b <arch_bits>] [-s <yocto_sdk_root>] [-t <toolchain_file>]"
echo " -m <mode> : Build mode: 'linux' or 'yocto' (default: linux)"
echo " -a <target> : Target arch for linux mode (default: aarch64)"
echo " -b <arch_bits> : Arch bits for yocto mode: 32 or 64 (default: 64)"
echo " -s <sdk_root> : Yocto SDK root path (overrides YOCTO_SDK_ROOT env var)"
echo " -t <toolchain> : CMake toolchain file (overrides TOOLCHAIN_FILE env var)"
echo " -h : Show this help message"
exit 1
}
# Default values
BUILD_MODE=linux
TARGET_ARCH=aarch64
ARCH_BITS=64
CLI_SDK_ROOT=""
CLI_TOOLCHAIN_FILE=""
# Parse arguments
while getopts 'm:a:b:s:t:h' opt; do
case "$opt" in
m)
BUILD_MODE=$OPTARG
;;
a)
TARGET_ARCH=$OPTARG
;;
b)
ARCH_BITS=$OPTARG
;;
s)
CLI_SDK_ROOT=$OPTARG
;;
t)
CLI_TOOLCHAIN_FILE=$OPTARG
;;
h)
usage
;;
*)
usage
;;
esac
done
ROOT_PWD=$(cd "$(dirname $0)" && pwd)
# ===========================================================================
# Yocto build
# ===========================================================================
if [[ "${BUILD_MODE}" == "yocto" ]]; then
if [[ "${ARCH_BITS}" != "32" && "${ARCH_BITS}" != "64" ]]; then
echo "Unsupported ARCH_BITS \"${ARCH_BITS}\". Must be 32 or 64." >&2
exit 1
fi
# Configurable via environment variables (CLI args > env vars > defaults)
CMAKE_BIN="${CMAKE_BIN:-cmake}"
YOCTO_SDK_ROOT="${CLI_SDK_ROOT:-${YOCTO_SDK_ROOT:-/data/yuandian/tools/poky/4.0.20}}"
TOOLCHAIN_FILE="${CLI_TOOLCHAIN_FILE:-${TOOLCHAIN_FILE:-${ROOT_PWD}/../../cmake/yocto-toolchain.cmake}}"
# Export variables for CMake
export YOCTO_SDK_ROOT
export ARCH_BITS
BUILD_DIR="${ROOT_PWD}/build/yocto/${ARCH_BITS}"
echo "==> Building Yocto ${ARCH_BITS}-bit"
echo " toolchain : ${TOOLCHAIN_FILE}"
echo " SDK root : ${YOCTO_SDK_ROOT}"
echo " BUILD_DIR : ${BUILD_DIR}"
mkdir -p "${BUILD_DIR}"
rm -rf "${BUILD_DIR}"
# Select OpenCV based on target architecture
if [[ "${ARCH_BITS}" == "32" ]]; then
OPENCV_DIR="${ROOT_PWD}/../../../dependency/opencv/opencv-linux-armhf/share/OpenCV"
else
OPENCV_DIR="${ROOT_PWD}/../../../dependency/opencv/opencv-linux-aarch64/share/OpenCV"
fi
"${CMAKE_BIN}" \
-S "${ROOT_PWD}/src" \
-B "${BUILD_DIR}" \
-DCMAKE_TOOLCHAIN_FILE="${TOOLCHAIN_FILE}" \
-DYOCTO_SDK_ROOT="${YOCTO_SDK_ROOT}" \
-DARCH_BITS="${ARCH_BITS}" \
-DCMAKE_BUILD_TYPE=Release \
-DOpenCV_DIR="${OPENCV_DIR}"
"${CMAKE_BIN}" --build "${BUILD_DIR}" --config Release
# Strip (best-effort)
HOST_SYSROOT="${YOCTO_SDK_ROOT}/sysroots/x86_64-pokysdk-linux"
if [[ "${ARCH_BITS}" == "32" ]]; then
CROSS_TRIPLE="arm-poky-linux-gnueabi"
else
CROSS_TRIPLE="aarch64-poky-linux"
fi
STRIP_TOOL="${HOST_SYSROOT}/usr/bin/${CROSS_TRIPLE}/${CROSS_TRIPLE}-strip"
if [[ -x "${STRIP_TOOL}" ]]; then
"${STRIP_TOOL}" --strip-unneeded "${BUILD_DIR}/blazepose_detect_demo"
else
echo "warning: strip tool not found; keeping debug info." >&2
fi
echo "Build complete. Executable in ${BUILD_DIR}/blazepose_detect_demo"
exit 0
fi
# ===========================================================================
# Standard Linux cross-compile build
# ===========================================================================
# Default to aarch64-linux-gnu if GCC_COMPILER is not set
GCC_COMPILER=${GCC_COMPILER:-aarch64-linux-gnu}
# Set compilers
export CC=${GCC_COMPILER}-gcc
export CXX=${GCC_COMPILER}-g++
# Validate compiler
if ! command -v ${CC} &> /dev/null; then
echo "Error: Compiler ${CC} not found."
echo "Please set GCC_COMPILER environment variable to your cross-compiler path prefix."
echo "Example: export GCC_COMPILER=/path/to/toolchain/bin/aarch64-linux-gnu"
exit 1
fi
BUILD_DIR=${ROOT_PWD}/build/linux
echo "Building for Linux..."
echo "COMPILER: ${CC}"
echo "TARGET_ARCH: ${TARGET_ARCH}"
echo "BUILD_DIR: ${BUILD_DIR}"
mkdir -p ${BUILD_DIR}
cd ${BUILD_DIR}
cmake ../../src \
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=${TARGET_ARCH} \
-DCMAKE_BUILD_TYPE=Release
make -j4
echo "Build complete. Executable in ${BUILD_DIR}/blazepose_detect_demo"

View file

@ -0,0 +1,36 @@
cmake_minimum_required(VERSION 3.10...3.27)
project(blazepose_detect_demo)
set(CMAKE_CXX_STANDARD 17)
list(APPEND CMAKE_MODULE_PATH "${CMAKE_SOURCE_DIR}/../../../../cmake")
find_package(AMLNN REQUIRED)
include_directories(${AMLNN_INCLUDE_DIR})
link_directories(${AMLNN_LIBRARY_DIR})
include_directories(${CMAKE_SOURCE_DIR}/../../../../common)
# Set 3rdparty path
set(3RDPARTY_DIR "${CMAKE_SOURCE_DIR}/../../../../dependency")
if(CMAKE_SYSTEM_NAME STREQUAL "Android")
# Android needs log
link_libraries(log)
endif()
# Find OpenCV
message(STATUS "OpenCV_DIR: ${OpenCV_DIR}")
find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})
add_executable(blazepose_detect_demo
main.cpp
postprocess.cpp
postprocess.h
${CMAKE_SOURCE_DIR}/../../../../common/model_loader.cpp
)
target_link_libraries(blazepose_detect_demo
${OpenCV_LIBS}
${AMLNN_LIBRARY}
)

File diff suppressed because it is too large Load diff

View file

@ -0,0 +1,151 @@
/*
* Copyright (C) 20242025 Amlogic, Inc. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <iostream>
#include <string>
#include <vector>
#include <chrono>
#include <tuple>
#include <iomanip>
#include <fstream>
#include <opencv2/opencv.hpp>
#include "postprocess.h"
#include "model_loader.h"
const std::string DEFAULT_OUTPUT_PATH = "./result.jpg";
const int MODEL_INPUT_WIDTH = 224;
const int MODEL_INPUT_HEIGHT = 224;
const float SCORE_THRESHOLD = 0.5f;
const float NMS_THRESHOLD = 0.3f;
int main(int argc, char **argv)
{
std::string model_path;
std::string image_path;
if (argc != 3)
{
printf("%s <model_path> <image_path>\n", argv[0]);
return -1;
}
if (argc > 1)
model_path = argv[1];
if (argc > 2)
image_path = argv[2];
std::cout << "Blazepose Detect Demo" << std::endl;
std::cout << "Model: " << model_path << std::endl;
std::cout << "Image: " << image_path << std::endl;
std::cout << "Output: " << DEFAULT_OUTPUT_PATH << std::endl;
// 1. Load Image
cv::Mat img = cv::imread(image_path);
if (img.empty())
{
std::cerr << "Failed to load image from " << image_path << std::endl;
return -1;
}
// 2. Initialize Network
void *context = init_network(model_path.c_str());
if (!context)
{
std::cerr << "Failed to initialize network." << std::endl;
return -1;
}
// 3. Preprocess
auto start_time = std::chrono::high_resolution_clock::now();
auto [preprocessed, scale, pad] = preprocess(img, std::make_tuple(MODEL_INPUT_HEIGHT, MODEL_INPUT_WIDTH));
std::cout << "scale" << scale << std::endl;
std::cout << "pad: ("
<< std::get<0>(pad) << ", "
<< std::get<1>(pad) << ")"
<< std::endl;
// Quantize to int8 (model expects quantized input)
cv::Mat quantized_img = quantize_input(preprocessed, 0.007843137718737125, -1);
// 4. Set input and run inference
nn_input inData;
memset(&inData, 0, sizeof(nn_input));
inData.input_type = BINARY_RAW_DATA;
inData.input = quantized_img.data;
inData.input_index = 0;
inData.size = quantized_img.total() * quantized_img.elemSize();
if (aml_module_input_set(context, &inData) != 0)
{
std::cerr << "Failed to set input." << std::endl;
uninit_network(context);
return -1;
}
aml_output_config_t outconfig;
memset(&outconfig, 0, sizeof(aml_output_config_t));
outconfig.typeSize = sizeof(aml_output_config_t);
outconfig.format = AML_OUTDATA_FLOAT32;
nn_output *outdata = (nn_output *)aml_module_output_get(context, outconfig);
if (!outdata)
{
std::cerr << "Failed to run network." << std::endl;
uninit_network(context);
return -1;
}
// 5. Postprocess
float *ori_boxes = (float *)outdata->out[0].buf; // 2254 * 12
float *raw_scores = (float *)outdata->out[1].buf; // 2254 * 1
std::vector<BlazePoseDetection> detections = postprocess(
ori_boxes,
raw_scores,
std::make_tuple(preprocessed, scale, pad),
SCORE_THRESHOLD,
NMS_THRESHOLD);
auto end_time = std::chrono::high_resolution_clock::now();
std::chrono::duration<double, std::milli> inference_time = end_time - start_time;
std::cout << "Inference time: " << inference_time.count() << " ms" << std::endl;
std::cout << "Detections: " << detections.size() << std::endl;
// 6. Draw and Save
cv::Mat result_img = draw_detections(img, detections);
cv::imwrite(DEFAULT_OUTPUT_PATH, result_img);
std::cout << "Result saved to " << DEFAULT_OUTPUT_PATH << std::endl;
// image_path -> txt_path
std::string txt_path = image_path.substr(0, image_path.find_last_of('.'));
txt_path += ".txt";
std::ofstream ofs(txt_path);
if (ofs.is_open())
{
for (const auto &det : detections)
{
for (int i = 0; i < NUM_COORDS + 1; ++i)
ofs << det.coords[i] << (i < NUM_COORDS ? " " : "\n");
}
}
std::cout << "Detections saved to " << txt_path << std::endl;
// 7. Cleanup
uninit_network(context);
return 0;
}

View file

@ -0,0 +1,306 @@
/*
* Copyright (C) 20242025 Amlogic, Inc. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "postprocess.h"
#include <iostream>
#include <cmath>
#include <algorithm>
#include <unordered_map>
#define LOGI(...) \
do \
{ \
printf(__VA_ARGS__); \
printf("\n"); \
} while (0)
#define LOGE(...) \
do \
{ \
fprintf(stderr, __VA_ARGS__); \
fprintf(stderr, "\n"); \
} while (0)
// SHOW class names (1 classes)
const char *SHOW_CLASSES[1] = {"pose"};
inline float sigmoid(float x)
{
return 1.0f / (1.0f + std::exp(-x));
}
void decode_boxes(const float *ori_boxes, std::vector<std::vector<float>> &boxes)
{
const float x_scale = 224.0f;
const float y_scale = 224.0f;
const float h_scale = 224.0f;
const float w_scale = 224.0f;
boxes.resize(NUM_ANCHORS, std::vector<float>(NUM_COORDS, 0.0f));
for (int i = 0; i < NUM_ANCHORS; ++i)
{
float x_center = ori_boxes[i * NUM_COORDS + 0] / x_scale * anchors[i * 4 + 2] + anchors[i * 4 + 0];
float y_center = ori_boxes[i * NUM_COORDS + 1] / y_scale * anchors[i * 4 + 3] + anchors[i * 4 + 1];
float w = ori_boxes[i * NUM_COORDS + 2] / w_scale * anchors[i * 4 + 2];
float h = ori_boxes[i * NUM_COORDS + 3] / h_scale * anchors[i * 4 + 3];
boxes[i][0] = y_center - h / 2.0f;
boxes[i][1] = x_center - w / 2.0f;
boxes[i][2] = y_center + h / 2.0f;
boxes[i][3] = x_center + w / 2.0f;
for (int k = 0; k < 4; ++k)
{
int offset = 4 + k * 2;
float keypoint_x = ori_boxes[i * NUM_COORDS + offset] / x_scale * anchors[i * 4 + 2] + anchors[i * 4 + 0];
float keypoint_y = ori_boxes[i * NUM_COORDS + offset + 1] / y_scale * anchors[i * 4 + 3] + anchors[i * 4 + 1];
boxes[i][offset] = keypoint_x;
boxes[i][offset + 1] = keypoint_y;
}
}
}
void convert_output_to_detections(const float *ori_boxes, const float *ori_scores, std::vector<BlazePoseDetection> &detections, float min_score_thresh = 0.3f)
{
std::vector<std::vector<float>> decoded_boxes;
decode_boxes(ori_boxes, decoded_boxes);
detections.clear();
for (int i = 0; i < NUM_ANCHORS; ++i)
{
float s = sigmoid(std::min(std::max(ori_scores[i], -100.0f), 100.0f));
if (s < min_score_thresh)
continue;
BlazePoseDetection det;
for (int j = 0; j < NUM_COORDS; ++j)
det.coords[j] = decoded_boxes[i][j];
det.coords[NUM_COORDS] = s;
detections.push_back(det);
}
}
static inline float iou(const float *a, const float *b)
{
float xA = std::max(a[1], b[1]);
float yA = std::max(a[0], b[0]);
float xB = std::min(a[3], b[3]);
float yB = std::min(a[2], b[2]);
float interW = std::max(0.0f, xB - xA);
float interH = std::max(0.0f, yB - yA);
float inter = interW * interH;
float areaA = (a[3] - a[1]) * (a[2] - a[0]);
float areaB = (b[3] - b[1]) * (b[2] - b[0]);
float unionAB = areaA + areaB - inter;
if (unionAB <= 0.0f)
return 0.0f;
return inter / unionAB;
}
void weighted_nms(
std::vector<BlazePoseDetection> &detections, std::vector<BlazePoseDetection> &output, float iou_threshold = 0.3f)
{
output.clear();
if (detections.empty())
return;
std::sort(detections.begin(), detections.end(),
[](const BlazePoseDetection &a, const BlazePoseDetection &b)
{
return a.coords[NUM_COORDS] > b.coords[NUM_COORDS];
});
std::vector<bool> removed(detections.size(), false);
for (size_t i = 0; i < detections.size(); ++i)
{
if (removed[i])
continue;
std::vector<size_t> overlap_indices;
overlap_indices.push_back(i);
for (size_t j = i + 1; j < detections.size(); ++j)
{
if (removed[j])
continue;
if (iou(detections[i].coords, detections[j].coords) > iou_threshold)
overlap_indices.push_back(j);
}
float total_score = 0.0f;
std::vector<float> weighted(NUM_COORDS, 0.0f);
for (size_t idx : overlap_indices)
{
float score = detections[idx].coords[NUM_COORDS];
total_score += score;
for (int k = 0; k < NUM_COORDS; ++k)
weighted[k] += detections[idx].coords[k] * score;
removed[idx] = true;
}
BlazePoseDetection wdet;
for (int k = 0; k < NUM_COORDS; ++k)
wdet.coords[k] = weighted[k] / total_score;
wdet.coords[NUM_COORDS] = total_score / overlap_indices.size();
output.push_back(wdet);
}
}
std::tuple<cv::Mat, float, std::tuple<int, int>> preprocess(cv::Mat img, std::tuple<int, int> new_shape)
{
cv::Mat img_rgb;
if (img.empty())
{
LOGE("Preprocess received empty image");
return {};
}
// Convert to RGB
if (img.channels() == 4)
cv::cvtColor(img, img_rgb, cv::COLOR_RGBA2RGB);
else if (img.channels() == 3)
cv::cvtColor(img, img_rgb, cv::COLOR_BGR2RGB);
else
img_rgb = img.clone();
int orig_h = img.rows;
int orig_w = img.cols;
float scale = std::min(static_cast<float>(std::get<0>(new_shape)) / orig_h,
static_cast<float>(std::get<1>(new_shape)) / orig_w);
int new_h = static_cast<int>(round(orig_h * scale));
int new_w = static_cast<int>(round(orig_w * scale));
cv::Mat img_resized;
cv::resize(img_rgb, img_resized, cv::Size(new_w, new_h), 0, 0, cv::INTER_LINEAR);
int pad_h = std::get<0>(new_shape) - new_h;
int pad_w = std::get<1>(new_shape) - new_w;
int pad_left = static_cast<int>(round(pad_w / 2.0 - 0.1));
int pad_right = static_cast<int>(round(pad_w / 2.0 + 0.1));
int pad_top = static_cast<int>(round(pad_h / 2.0 - 0.1));
int pad_bottom = static_cast<int>(round(pad_h / 2.0 + 0.1));
cv::Mat img_padded;
cv::copyMakeBorder(img_resized, img_padded, pad_top, pad_bottom, pad_left, pad_right, cv::BORDER_CONSTANT, cv::Scalar(0, 0, 0));
cv::Mat img_float;
img_padded.convertTo(img_float, CV_32F, 1.0 / 127.5, -1.0);
scale = 1.0f / scale;
int pad_orig_h = static_cast<int>(pad_top * scale);
int pad_orig_w = static_cast<int>(pad_left * scale);
return std::make_tuple(img_float, scale, std::make_tuple(pad_orig_h, pad_orig_w));
}
cv::Mat quantize_input(const cv::Mat &float_img, float scale, int8_t zero_point)
{
if (float_img.empty() || float_img.type() != CV_32FC3)
{
LOGE("quantize_input: Invalid input image (must be CV_32FC3)");
return cv::Mat();
}
cv::Mat quantized_img(float_img.rows, float_img.cols, CV_8SC3);
const float *src_ptr = (const float *)float_img.data;
int8_t *dst_ptr = (int8_t *)quantized_img.data;
int total_elements = float_img.total() * float_img.channels();
for (int i = 0; i < total_elements; ++i)
{
dst_ptr[i] = static_cast<int8_t>(std::round(src_ptr[i] / scale + zero_point));
}
return quantized_img;
}
void denorm_detections(std::vector<float> &detection, float scale, const float pad[2])
{
detection[0] = detection[0] * scale * 224.0f - pad[0];
detection[1] = detection[1] * scale * 224.0f - pad[1];
detection[2] = detection[2] * scale * 224.0f - pad[0];
detection[3] = detection[3] * scale * 224.0f - pad[1];
for (size_t k = 4; k + 1 < detection.size(); k += 2)
{
detection[k] = detection[k] * scale * 224.0f - pad[1];
detection[k + 1] = detection[k + 1] * scale * 224.0f - pad[0];
}
}
std::vector<BlazePoseDetection> postprocess(float *ori_boxes, float *ori_scores,
std::tuple<cv::Mat, float, std::tuple<int, int>> input_tuple,
float conf_threshold, float iou_threshold)
{
float scale = std::get<1>(input_tuple);
int pad_left = std::get<0>(std::get<2>(input_tuple));
int pad_top = std::get<1>(std::get<2>(input_tuple));
float pad[2] = {static_cast<float>(pad_left), static_cast<float>(pad_top)};
std::vector<BlazePoseDetection> detections;
convert_output_to_detections(ori_boxes, ori_scores, detections, conf_threshold);
std::vector<BlazePoseDetection> filtered;
weighted_nms(detections, filtered, iou_threshold);
int pose_num = filtered.size();
for (size_t b = 0; b < pose_num; ++b)
{
std::vector<float> coords(filtered[b].coords, filtered[b].coords + NUM_COORDS + 1);
// mapping to original size
denorm_detections(coords, scale, pad);
for (size_t i = 0; i < NUM_COORDS + 1; ++i)
filtered[b].coords[i] = coords[i];
}
return filtered;
}
cv::Mat draw_detections(cv::Mat image, const std::vector<BlazePoseDetection> &detections)
{
cv::Mat drawn_image = image.clone();
int class_id = 0;
for (const auto &det : detections)
{
// Generate color based on class_id using HSV
float hue = fmod(class_id * 137.508f, 360.0f);
cv::Mat hsv(1, 1, CV_8UC3, cv::Scalar(hue / 2.0f, 204, 230));
cv::Mat rgb;
cv::cvtColor(hsv, rgb, cv::COLOR_HSV2BGR);
cv::Scalar color(rgb.at<cv::Vec3b>(0, 0)[0], rgb.at<cv::Vec3b>(0, 0)[1], rgb.at<cv::Vec3b>(0, 0)[2]);
// Draw bounding box
int x1 = static_cast<int>(det.coords[1]);
int y1 = static_cast<int>(det.coords[0]);
int x2 = static_cast<int>(det.coords[3]);
int y2 = static_cast<int>(det.coords[2]);
cv::rectangle(drawn_image, cv::Point(x1, y1), cv::Point(x2, y2), color, 2);
// Draw label
std::string label = std::string(SHOW_CLASSES[class_id]) + ": " + cv::format("%.2f", det.coords[12]);
int baseline = 0;
cv::Size text_size = cv::getTextSize(label, cv::FONT_HERSHEY_SIMPLEX, 0.6, 1, &baseline);
int label_x = x1;
int label_y = y1 - 5;
if (label_y < text_size.height)
label_y = x1 + text_size.height + 5;
// Draw label background
cv::rectangle(drawn_image,
cv::Point(label_x, label_y - text_size.height - baseline),
cv::Point(label_x + text_size.width, label_y + baseline),
color, cv::FILLED);
// Determine text color based on background brightness
int brightness = (color[0] + color[1] + color[2]) / 3;
cv::Scalar text_color = brightness < 128 ? cv::Scalar(255, 255, 255) : cv::Scalar(0, 0, 0);
cv::putText(drawn_image, label,
cv::Point(label_x, label_y),
cv::FONT_HERSHEY_SIMPLEX, 0.6, text_color, 1, cv::LINE_AA);
}
return drawn_image;
}

View file

@ -0,0 +1,52 @@
/*
* Copyright (C) 20242025 Amlogic, Inc. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef _AMLNN_BLAZEPOSE_DETECT_POSTPROCESS_H_
#define _AMLNN_BLAZEPOSE_DETECT_POSTPROCESS_H_
#include <opencv2/opencv.hpp>
#include <vector>
#include <tuple>
#include <string>
#include "anchors.h"
#define NUM_COORDS 12
// BlazePoseDetection result structure
struct BlazePoseDetection
{
float coords[NUM_COORDS + 1]; // 12 coords + 1 score
};
// COCO class names (80 classes)
extern const char *COCO_CLASSES[80];
// Preprocess image with letterbox resizing
std::tuple<cv::Mat, float, std::tuple<int, int>> preprocess(cv::Mat img, std::tuple<int, int> new_shape);
// Quantize float32 image to int8 for model input
cv::Mat quantize_input(const cv::Mat &float_img, float scale = 0.007843137718737125, int8_t zero_point = -1);
// Postprocess blazepose_detect outputs with DFL decoding
std::vector<BlazePoseDetection> postprocess(float *raw_boxes, float *raw_scores,
std::tuple<cv::Mat, float, std::tuple<int, int>> input_tuple,
float conf_threshold, float iou_threshold);
// Draw detections on image
cv::Mat draw_detections(cv::Mat image, const std::vector<BlazePoseDetection> &detections);
#endif // _AMLNN_BLAZEPOSE_DETECT_POSTPROCESS_H_