1#include "blace_ai.h"
 2#include <opencv2/opencv.hpp>
 3
 4// include the models you want to use
 5#include "ben2_v1_default_v1_ALL_export_version_v26.h"
 6
 7using namespace blace;
 8int main() {
 9  ::workload_management::BlaceWorld blace;
10
11  // load image into op
12  auto exe_path = util::getPathToExe();
13  std::filesystem::path photo_path = exe_path / "person.jpg";
14  auto world_tensor_orig =
15      CONSTRUCT_OP(ops::FromImageFileOp(photo_path.string()));
16
17  // interpolate to size consumable by model
18  auto interpolated = CONSTRUCT_OP(ops::Interpolate2DOp(
19      world_tensor_orig, 512, 896, ml_core::BICUBIC, false, true));
20
21  // construct model inference arguments
22  ml_core::InferenceArgsCollection infer_args;
23  infer_args.inference_args.backends = {
24      ml_core::TORCHSCRIPT_CUDA_FP16, ml_core::TORCHSCRIPT_MPS_FP16,
25      ml_core::TORCHSCRIPT_CUDA_FP32, ml_core::TORCHSCRIPT_MPS_FP32,
26      ml_core::ONNX_DML_FP32,         ml_core::TORCHSCRIPT_CPU_FP32};
27
28  // construct inference operation
29  auto infer_op = ben2_v1_default_v1_ALL_export_version_v26_run(
30      interpolated, 0, infer_args, util::getPathToExe().string());
31
32  // normalize matte to zero-one range
33  auto normalized_matte =
34      CONSTRUCT_OP(ops::MapToRangeOp(infer_op, ml_core::ZERO_TO_ONE));
35
36  // construct evaluator and evaluate to cv::Mat
37  computation_graph::GraphEvaluator evaluator(normalized_matte);
38  auto [return_code, cv_result] = evaluator.evaluateToCVMat();
39
40  // multiply for plotting
41  cv_result *= 255.;
42
43  // save to disk and return
44  auto out_file = exe_path / "matte.png";
45  cv::imwrite(out_file.string(), cv_result);
46
47  return 0;
48}