Add --val-render

opensplat.cpp

@@ -17,6 +17,7 @@ int main(int argc, char *argv[]){
         ("s,save-every", "Save output scene every these many steps (set to -1 to disable)", cxxopts::value<int>()->default_value("-1"))
         ("val", "Withhold a camera shot for validating the scene loss")
         ("val-image", "Filename of the image to withhold for validating scene loss", cxxopts::value<std::string>()->default_value("random"))
+        ("val-render", "Path of the directory where to render validation images", cxxopts::value<std::string>()->default_value(""))
         ("cpu", "Force CPU execution")
 
         ("n,num-iters", "Number of iterations to run", cxxopts::value<int>()->default_value("30000"))
@@ -57,8 +58,10 @@ int main(int argc, char *argv[]){
     const std::string projectRoot = result["input"].as<std::string>();
     const std::string outputScene = result["output"].as<std::string>();
     const int saveEvery = result["save-every"].as<int>(); 
-    const bool validate = result.count("val") > 0;
+    const bool validate = result.count("val") > 0 || result.count("val-render") > 0;
     const std::string valImage = result["val-image"].as<std::string>();
+    const std::string valRender = result["val-render"].as<std::string>();
+    if (!valRender.empty() && !fs::exists(valRender)) fs::create_directories(valRender);
 
     const float downScaleFactor = (std::max)(result["downscale-factor"].as<float>(), 1.0f);
     const int numIters = result["num-iters"].as<int>();
@@ -79,6 +82,7 @@ int main(int argc, char *argv[]){
     torch::Device device = torch::kCPU;
     int displayStep = 1;
 
+
     if (torch::cuda::is_available() && result.count("cpu") == 0) {
         std::cout << "Using CUDA" << std::endl;
         device = torch::kCUDA;
@@ -132,6 +136,13 @@ int main(int argc, char *argv[]){
                 fs::path p(outputScene);
                 model.savePlySplat((p.replace_filename(fs::path(p.stem().string() + "_" + std::to_string(step) + p.extension().string())).string()));
             }
+
+            if (!valRender.empty() && step % displayStep == 0){
+                torch::Tensor rgb = model.forward(*valCam, step);
+                cv::Mat image = tensorToImage(rgb.detach().cpu());
+                cv::cvtColor(image, image, cv::COLOR_RGB2BGR);
+                cv::imwrite((fs::path(valRender) / (std::to_string(step) + ".png")).string(), image);
+            }
         }
 
         model.savePlySplat(outputScene);