add ocr cpp pferx to logi
@@ -42,17 +42,17 @@ template <typename ConfigT> int PPredictor::_init(ConfigT &config) {
// CL_PRECISION_FP32: 1, force fp32
// CL_PRECISION_FP16: 2, force fp16
config.set_opencl_precision(paddle::lite_api::CL_PRECISION_FP32);
- LOGI("device: running on gpu.");
+ LOGI("ocr cpp device: running on gpu.");
}
} else {
- LOGI("device: running on cpu.");
+ LOGI("ocr cpp device: running on cpu.");
// you can give backup cpu nb model instead
// config.set_model_from_file(cpu_nb_model_dir);
}
config.set_threads(_thread_num);
config.set_power_mode(_mode);
_predictor = paddle::lite_api::CreatePaddlePredictor(config);
- LOGI("paddle instance created");
+ LOGI("ocr cpp paddle instance created");
return RETURN_OK;
}
@@ -73,18 +73,18 @@ std::vector<PredictorInput> PPredictor::get_inputs(int num) {
PredictorInput PPredictor::get_first_input() { return get_input(0); }
std::vector<PredictorOutput> PPredictor::infer() {
- LOGI("infer Run start %d", _net_flag);
+ LOGI("ocr cpp infer Run start %d", _net_flag);
std::vector<PredictorOutput> results;
if (!_is_input_get) {
return results;
}
_predictor->Run();
- LOGI("infer Run end");
+ LOGI("ocr cpp infer Run end");
for (int i = 0; i < _predictor->GetOutputNames().size(); i++) {
std::unique_ptr<const paddle::lite_api::Tensor> output_tensor =
_predictor->GetOutput(i);
- LOGI("output tensor[%d] size %ld", i, product(output_tensor->shape()));
+ LOGI("ocr cpp output tensor[%d] size %ld", i, product(output_tensor->shape()));
PredictorOutput result{std::move(output_tensor), i, _net_flag};
results.emplace_back(std::move(result));
}
