render_patch.txt

commit 92bea692acc2554689e6797fd65f953643534571
Author: Matthieu Gendrin <matthieu.gendrin@orange.com>
Date:   Tue Feb 6 16:21:08 2024 +0100

    render results

diff --git a/render.py b/render.py
new file mode 100644
index 0000000..4b9bb54
--- /dev/null
+++ b/render.py
@@ -0,0 +1,66 @@
+#
+# Copyright (C) 2023, Inria
+# GRAPHDECO research group, https://team.inria.fr/graphdeco
+# All rights reserved.
+#
+# This software is free for non-commercial, research and evaluation use 
+# under the terms of the LICENSE.md file.
+#
+# For inquiries contact  george.drettakis@inria.fr
+#
+
+import torch
+from scene import Scene
+import os
+from tqdm import tqdm
+from os import makedirs
+from gaussian_renderer import render
+import torchvision
+from utils.general_utils import safe_state
+from argparse import ArgumentParser
+from arguments import ModelParams, PipelineParams, get_combined_args
+from gaussian_renderer import GaussianModel
+
+def render_set(model_path, name, iteration, views, gaussians, pipeline, background):
+    render_path = os.path.join(model_path, name, "ours_{}".format(iteration), "renders")
+    gts_path = os.path.join(model_path, name, "ours_{}".format(iteration), "gt")
+
+    makedirs(render_path, exist_ok=True)
+    makedirs(gts_path, exist_ok=True)
+
+    for idx, view in enumerate(tqdm(views, desc="Rendering progress")):
+        rendering = render(view[1].cuda(), gaussians, pipeline, background)["render"]
+        gt = view[0][0:3, :, :]
+        torchvision.utils.save_image(rendering, os.path.join(render_path, '{0:05d}'.format(idx) + ".png"))
+        torchvision.utils.save_image(gt, os.path.join(gts_path, '{0:05d}'.format(idx) + ".png"))
+
+def render_sets(dataset : ModelParams, iteration : int, pipeline : PipelineParams, skip_train : bool, skip_test : bool):
+    with torch.no_grad():
+        gaussians = GaussianModel(dataset.sh_degree, gaussian_dim=4, rot_4d=True)
+        scene = Scene(dataset, gaussians, shuffle=False)
+
+        bg_color = [1,1,1] if dataset.white_background else [0, 0, 0]
+        background = torch.tensor(bg_color, dtype=torch.float32, device="cuda")
+
+        if not skip_train:
+             render_set(dataset.model_path, "train", scene.loaded_iter, scene.getTrainCameras(), gaussians, pipeline, background)
+
+        if not skip_test:
+             render_set(dataset.model_path, "test", scene.loaded_iter, scene.getTestCameras(), gaussians, pipeline, background)
+
+if __name__ == "__main__":
+    # Set up command line argument parser
+    parser = ArgumentParser(description="Testing script parameters")
+    model = ModelParams(parser, sentinel=True)
+    pipeline = PipelineParams(parser)
+    parser.add_argument("--iteration", default=-1, type=int)
+    parser.add_argument("--skip_train", action="store_true")
+    parser.add_argument("--skip_test", action="store_true")
+    parser.add_argument("--quiet", action="store_true")
+    args = get_combined_args(parser)
+    print("Rendering " + args.model_path)
+
+    # Initialize system state (RNG)
+    safe_state(args.quiet)
+
+    render_sets(model.extract(args), args.iteration, pipeline.extract(args), args.skip_train, args.skip_test)
\ No newline at end of file
diff --git a/scene/__init__.py b/scene/__init__.py
index ccb10a5..e0ac824 100644
--- a/scene/__init__.py
+++ b/scene/__init__.py
@@ -78,7 +78,7 @@ class Scene:
             self.test_cameras[resolution_scale] = cameraList_from_camInfos(scene_info.test_cameras, resolution_scale, args)
             
         if args.loaded_pth:
-            self.gaussians.create_from_pth(args.loaded_pth, self.cameras_extent)
+            self.gaussians.restore(model_args=torch.load(args.loaded_pth)[0], training_args=None)
         else:
             if self.loaded_iter:
                 self.gaussians.load_ply(os.path.join(self.model_path,