mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-07 01:22:59 +08:00
cc4bbf2163
* add java examples * fix detail * fix pre-config --------- Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
59 lines
2.2 KiB
C++
59 lines
2.2 KiB
C++
#include "infer_demo.h"
|
|
|
|
#include "fastdeploy/vision.h"
|
|
|
|
std::string ConvertTo(JNIEnv *env, jstring jstr) {
|
|
if (!jstr) {
|
|
return "";
|
|
}
|
|
const jclass jstring_clazz = env->GetObjectClass(jstr);
|
|
const jmethodID getBytesID =
|
|
env->GetMethodID(jstring_clazz, "getBytes", "(Ljava/lang/String;)[B");
|
|
const jbyteArray jstring_bytes = reinterpret_cast<jbyteArray>(
|
|
env->CallObjectMethod(jstr, getBytesID, env->NewStringUTF("UTF-8")));
|
|
|
|
size_t length = static_cast<size_t>(env->GetArrayLength(jstring_bytes));
|
|
jbyte *jstring_bytes_ptr = env->GetByteArrayElements(jstring_bytes, NULL);
|
|
|
|
std::string res =
|
|
std::string(reinterpret_cast<char *>(jstring_bytes_ptr), length);
|
|
env->ReleaseByteArrayElements(jstring_bytes, jstring_bytes_ptr, JNI_ABORT);
|
|
|
|
env->DeleteLocalRef(jstring_bytes);
|
|
env->DeleteLocalRef(jstring_clazz);
|
|
return res;
|
|
}
|
|
|
|
JNIEXPORT void JNICALL Java_InferDemo_infer(JNIEnv *env, jobject thiz,
|
|
jstring modelPath,
|
|
jstring imagePath) {
|
|
std::string model_path = ConvertTo(env, modelPath);
|
|
if (model_path[model_path.length() - 1] != '/') {
|
|
model_path += "/";
|
|
}
|
|
std::string model_file = model_path + "model.pdmodel";
|
|
std::string params_file = model_path + "model.pdiparams";
|
|
std::string infer_cfg_file = model_path + "infer_cfg.yml";
|
|
|
|
// Configuration information for model inference
|
|
fastdeploy::RuntimeOption option;
|
|
auto model = fastdeploy::vision::detection::PPYOLOE(model_file, params_file,
|
|
infer_cfg_file, option);
|
|
|
|
assert(model.Initialized()); // Check whether the model is successfully
|
|
// initialized
|
|
|
|
std::string image_path = ConvertTo(env, imagePath);
|
|
cv::Mat im = cv::imread(image_path);
|
|
fastdeploy::vision::DetectionResult result;
|
|
|
|
assert(model.Predict(&im,
|
|
&result)); // Check whether the prediction is successful
|
|
|
|
std::cout << result.Str() << std::endl;
|
|
|
|
cv::Mat vis_im = fastdeploy::vision::Visualize::VisDetection(im, result, 0.5);
|
|
// sava the visual results
|
|
cv::imwrite("vis_result.jpg", vis_im);
|
|
std::cout << "Visualized result save in vis_result.jpg" << std::endl;
|
|
} |