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examples/blazepose_landmark/cpp/src/main.cpp

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+/*
+ * Copyright (C) 2024–2025 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 = 256;
+const int MODEL_INPUT_HEIGHT = 256;
+const float SCORE_THRESHOLD = 0.5f;
+
+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;
+    }
+    // Load detections
+    // n * 13 detections
+    // image_path -> txt_path
+    std::vector<std::vector<float>> detections;
+
+    std::string txt_path = image_path.substr(0, image_path.find_last_of('.'));
+    txt_path += ".txt";
+    std::ifstream ifs(txt_path);
+    for (std::string line; std::getline(ifs, line);)
+    {
+        std::istringstream iss(line);
+        std::vector<float> det;
+        float val;
+        while (iss >> val)
+            det.push_back(val);
+        if (!det.empty())
+            detections.push_back(det);
+    }
+
+    // 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, affine] = preprocess(img, detections, std::make_tuple(MODEL_INPUT_HEIGHT, MODEL_INPUT_WIDTH));
+
+    // Quantize to int16 (model expects quantized input)
+    cv::Mat quantized_img = quantize_input(preprocessed, 0.000030518509447574615f);
+
+    // 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
+    std::vector<BlazePoseLandmark> landmarks = postprocess(outdata, affine);
+    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 << "Landmarks: " << landmarks.size() << std::endl;
+
+    // 6. Draw and Save
+    cv::Mat result_img = draw_landmarks(img, landmarks, SCORE_THRESHOLD);
+    cv::imwrite(DEFAULT_OUTPUT_PATH, result_img);
+    std::cout << "Result saved to " << DEFAULT_OUTPUT_PATH << std::endl;
+
+    // 7. Cleanup
+    uninit_network(context);
+
+    return 0;
+}