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0000000000000000000000000000000000000000..d22a8652a72412e22288c227fdbc2d086dd7c867 --- /dev/null +++ b/mipnerf360/kitchen/test/ours_30000/vis/depth_00033.tiff @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d3216b7c0f1a8c06267eb8b0a1d39366f6ff9f9de4c860fe25bed8c0e28d39f9 +size 6475182 diff --git a/mipnerf360/kitchen/test/ours_30000/vis/depth_00034.tiff b/mipnerf360/kitchen/test/ours_30000/vis/depth_00034.tiff new file mode 100644 index 0000000000000000000000000000000000000000..10c6ce3946240bb2ecbd4734f0af1520c9905890 --- /dev/null +++ b/mipnerf360/kitchen/test/ours_30000/vis/depth_00034.tiff @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:62662588b8850f35e288af434ce6385153ba1bc9bcc2b1488bc1669a574db6bc +size 6475182 diff --git a/mipnerf360/kitchen/train/ours_30000/fuse.ply b/mipnerf360/kitchen/train/ours_30000/fuse.ply new file mode 100644 index 0000000000000000000000000000000000000000..21067d99740fd6be56092a471b8ca9788d2d4653 --- /dev/null +++ b/mipnerf360/kitchen/train/ours_30000/fuse.ply @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:623b8ca1f76dd573b9d9acdf48a817345ae4df7f8fc1740d95fb3f99d274542d +size 112380034 diff --git a/mipnerf360/kitchen/train/ours_30000/fuse_post.ply b/mipnerf360/kitchen/train/ours_30000/fuse_post.ply new file mode 100644 index 0000000000000000000000000000000000000000..9a86c75c23a85ad5e303227c90a009745fad8184 --- /dev/null +++ b/mipnerf360/kitchen/train/ours_30000/fuse_post.ply @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6066c13c6cdf175f7ffb6ad34a5589eb180076d9f4f25d18ce511abd88e48476 +size 103164705 diff --git a/mipnerf360/logs/bicycle.log b/mipnerf360/logs/bicycle.log new file mode 100644 index 0000000000000000000000000000000000000000..c539c8fe781d73f172d82283380c1419dd13548d --- /dev/null +++ b/mipnerf360/logs/bicycle.log @@ -0,0 +1,65 @@ +Optimizing output/mipnerf360/bicycle +Output folder: output/mipnerf360/bicycle [12/11 10:09:22] + Reading camera 1/194 Reading camera 2/194 Reading camera 3/194 Reading camera 4/194 Reading camera 5/194 Reading camera 6/194 Reading camera 7/194 Reading camera 8/194 Reading camera 9/194 Reading camera 10/194 Reading camera 11/194 Reading camera 12/194 Reading camera 13/194 Reading camera 14/194 Reading camera 15/194 Reading camera 16/194 Reading camera 17/194 Reading camera 18/194 Reading camera 19/194 Reading camera 20/194 Reading camera 21/194 Reading camera 22/194 Reading camera 23/194 Reading camera 24/194 Reading camera 25/194 Reading camera 26/194 Reading camera 27/194 Reading camera 28/194 Reading camera 29/194 Reading camera 30/194 Reading camera 31/194 Reading camera 32/194 Reading camera 33/194 Reading camera 34/194 Reading camera 35/194 Reading camera 36/194 Reading camera 37/194 Reading camera 38/194 Reading camera 39/194 Reading camera 40/194 Reading camera 41/194 Reading camera 42/194 Reading camera 43/194 Reading camera 44/194 Reading camera 45/194 Reading camera 46/194 Reading camera 47/194 Reading camera 48/194 Reading camera 49/194 Reading camera 50/194 Reading camera 51/194 Reading camera 52/194 Reading camera 53/194 Reading camera 54/194 Reading camera 55/194 Reading camera 56/194 Reading camera 57/194 Reading camera 58/194 Reading camera 59/194 Reading camera 60/194 Reading camera 61/194 Reading camera 62/194 Reading camera 63/194 Reading camera 64/194 Reading camera 65/194 Reading camera 66/194 Reading camera 67/194 Reading camera 68/194 Reading camera 69/194 Reading camera 70/194 Reading camera 71/194 Reading camera 72/194 Reading camera 73/194 Reading camera 74/194 Reading camera 75/194 Reading camera 76/194 Reading camera 77/194 Reading camera 78/194 Reading camera 79/194 Reading camera 80/194 Reading camera 81/194 Reading camera 82/194 Reading camera 83/194 Reading camera 84/194 Reading camera 85/194 Reading camera 86/194 Reading camera 87/194 Reading camera 88/194 Reading camera 89/194 Reading camera 90/194 Reading camera 91/194 Reading camera 92/194 Reading camera 93/194 Reading camera 94/194 Reading camera 95/194 Reading camera 96/194 Reading camera 97/194 Reading camera 98/194 Reading camera 99/194 Reading camera 100/194 Reading camera 101/194 Reading camera 102/194 Reading camera 103/194 Reading camera 104/194 Reading camera 105/194 Reading camera 106/194 Reading camera 107/194 Reading camera 108/194 Reading camera 109/194 Reading camera 110/194 Reading camera 111/194 Reading camera 112/194 Reading camera 113/194 Reading camera 114/194 Reading camera 115/194 Reading camera 116/194 Reading camera 117/194 Reading camera 118/194 Reading camera 119/194 Reading camera 120/194 Reading camera 121/194 Reading camera 122/194 Reading camera 123/194 Reading camera 124/194 Reading camera 125/194 Reading camera 126/194 Reading camera 127/194 Reading camera 128/194 Reading camera 129/194 Reading camera 130/194 Reading camera 131/194 Reading camera 132/194 Reading camera 133/194 Reading camera 134/194 Reading camera 135/194 Reading camera 136/194 Reading camera 137/194 Reading camera 138/194 Reading camera 139/194 Reading camera 140/194 Reading camera 141/194 Reading camera 142/194 Reading camera 143/194 Reading camera 144/194 Reading camera 145/194 Reading camera 146/194 Reading camera 147/194 Reading camera 148/194 Reading camera 149/194 Reading camera 150/194 Reading camera 151/194 Reading camera 152/194 Reading camera 153/194 Reading camera 154/194 Reading camera 155/194 Reading camera 156/194 Reading camera 157/194 Reading camera 158/194 Reading camera 159/194 Reading camera 160/194 Reading camera 161/194 Reading camera 162/194 Reading camera 163/194 Reading camera 164/194 Reading camera 165/194 Reading camera 166/194 Reading camera 167/194 Reading camera 168/194 Reading camera 169/194 Reading camera 170/194 Reading camera 171/194 Reading camera 172/194 Reading camera 173/194 Reading camera 174/194 Reading camera 175/194 Reading camera 176/194 Reading camera 177/194 Reading camera 178/194 Reading camera 179/194 Reading camera 180/194 Reading camera 181/194 Reading camera 182/194 Reading camera 183/194 Reading camera 184/194 Reading camera 185/194 Reading camera 186/194 Reading camera 187/194 Reading camera 188/194 Reading camera 189/194 Reading camera 190/194 Reading camera 191/194 Reading camera 192/194 Reading camera 193/194 Reading camera 194/194 [12/11 10:09:24] +Loading Training Cameras [12/11 10:09:24] +Loading Test Cameras [12/11 10:09:27] +Number of points at initialisation : 54275 [12/11 10:09:28] + Training progress: 0%| | 0/30000 [00:00 + training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 119, in training + training_report(tb_writer, iteration, Ll1, loss, l1_loss, iter_start.elapsed_time(iter_end), testing_iterations, scene, render, (pipe, background)) + File "/home/work/workspace/cuda124/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context + return func(*args, **kwargs) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 219, in training_report + depth = colormap(depth.cpu().numpy()[0], cmap='turbo') + File "/home/work/workspace/gs-baselines/2DGS/utils/general_utils.py", line 177, in colormap + data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8) +AttributeError: 'FigureCanvasAgg' object has no attribute 'tostring_rgb'. Did you mean: 'tostring_argb'? + Training progress: 17%|█▋ | 5000/30000 [01:12<06:04, 68.66it/s, Loss=0.01040, distort=0.00000, normal=0.00000, Points=86457] +Looking for config file in output/nerf_synthetic/chair/cfg_args +Config file found: output/nerf_synthetic/chair/cfg_args +Rendering output/nerf_synthetic/chair +Traceback (most recent call last): + File "/home/work/workspace/gs-baselines/2DGS/render.py", line 51, in + scene = Scene(dataset, gaussians, load_iteration=iteration, shuffle=False) + File "/home/work/workspace/gs-baselines/2DGS/scene/__init__.py", line 35, in __init__ + self.loaded_iter = searchForMaxIteration(os.path.join(self.model_path, "point_cloud")) + File "/home/work/workspace/gs-baselines/2DGS/utils/system_utils.py", line 27, in searchForMaxIteration + saved_iters = [int(fname.split("_")[-1]) for fname in os.listdir(folder)] +FileNotFoundError: [Errno 2] No such file or directory: 'output/nerf_synthetic/chair/point_cloud' +Scene: output/nerf_synthetic/chair +Unable to compute metrics for model output/nerf_synthetic/chair +Optimizing output/nerf_synthetic/chair +Output folder: output/nerf_synthetic/chair [12/11 13:28:10] +Found transforms_train.json file, assuming Blender data set! [12/11 13:28:10] +Reading Training Transforms [12/11 13:28:10] +Reading Test Transforms [12/11 13:28:16] +Loading Training Cameras [12/11 13:28:30] +Loading Test Cameras [12/11 13:28:31] +Number of points at initialisation : 10000 [12/11 13:28:32] + Training progress: 0%| | 0/30000 [00:00 + training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 119, in training + training_report(tb_writer, iteration, Ll1, loss, l1_loss, iter_start.elapsed_time(iter_end), testing_iterations, scene, render, (pipe, background)) + File "/home/work/workspace/cuda124/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context + return func(*args, **kwargs) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 219, in training_report + depth = colormap(depth.cpu().numpy()[0], cmap='turbo') + File "/home/work/workspace/gs-baselines/2DGS/utils/general_utils.py", line 177, in colormap + data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8) +AttributeError: 'FigureCanvasAgg' object has no attribute 'tostring_rgb'. Did you mean: 'tostring_argb'? + Training progress: 17%|█▋ | 5000/30000 [01:14<06:12, 67.05it/s, Loss=0.01932, distort=0.00000, normal=0.00000, Points=109217] +Looking for config file in output/nerf_synthetic/drums/cfg_args +Config file found: output/nerf_synthetic/drums/cfg_args +Rendering output/nerf_synthetic/drums +Traceback (most recent call last): + File "/home/work/workspace/gs-baselines/2DGS/render.py", line 51, in + scene = Scene(dataset, gaussians, load_iteration=iteration, shuffle=False) + File "/home/work/workspace/gs-baselines/2DGS/scene/__init__.py", line 35, in __init__ + self.loaded_iter = searchForMaxIteration(os.path.join(self.model_path, "point_cloud")) + File "/home/work/workspace/gs-baselines/2DGS/utils/system_utils.py", line 27, in searchForMaxIteration + saved_iters = [int(fname.split("_")[-1]) for fname in os.listdir(folder)] +FileNotFoundError: [Errno 2] No such file or directory: 'output/nerf_synthetic/drums/point_cloud' +Scene: output/nerf_synthetic/drums +Unable to compute metrics for model output/nerf_synthetic/drums +Optimizing output/nerf_synthetic/drums +Output folder: output/nerf_synthetic/drums [12/11 13:28:08] +Found transforms_train.json file, assuming Blender data set! [12/11 13:28:08] +Reading Training Transforms [12/11 13:28:08] +Reading Test Transforms [12/11 13:28:16] +Loading Training Cameras [12/11 13:28:29] +Loading Test Cameras [12/11 13:28:30] +Number of points at initialisation : 10000 [12/11 13:28:32] + Training progress: 0%| | 0/30000 [00:00 + training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 119, in training + training_report(tb_writer, iteration, Ll1, loss, l1_loss, iter_start.elapsed_time(iter_end), testing_iterations, scene, render, (pipe, background)) + File "/home/work/workspace/cuda124/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context + return func(*args, **kwargs) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 219, in training_report + depth = colormap(depth.cpu().numpy()[0], cmap='turbo') + File "/home/work/workspace/gs-baselines/2DGS/utils/general_utils.py", line 177, in colormap + data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8) +AttributeError: 'FigureCanvasAgg' object has no attribute 'tostring_rgb'. Did you mean: 'tostring_argb'? + Training progress: 17%|█▋ | 5000/30000 [01:05<05:26, 76.56it/s, Loss=0.00734, distort=0.00000, normal=0.00000, Points=53503] +Looking for config file in output/nerf_synthetic/ficus/cfg_args +Config file found: output/nerf_synthetic/ficus/cfg_args +Rendering output/nerf_synthetic/ficus +Traceback (most recent call last): + File "/home/work/workspace/gs-baselines/2DGS/render.py", line 51, in + scene = Scene(dataset, gaussians, load_iteration=iteration, shuffle=False) + File "/home/work/workspace/gs-baselines/2DGS/scene/__init__.py", line 35, in __init__ + self.loaded_iter = searchForMaxIteration(os.path.join(self.model_path, "point_cloud")) + File "/home/work/workspace/gs-baselines/2DGS/utils/system_utils.py", line 27, in searchForMaxIteration + saved_iters = [int(fname.split("_")[-1]) for fname in os.listdir(folder)] +FileNotFoundError: [Errno 2] No such file or directory: 'output/nerf_synthetic/ficus/point_cloud' +Scene: output/nerf_synthetic/ficus +Unable to compute metrics for model output/nerf_synthetic/ficus +Optimizing output/nerf_synthetic/ficus +Output folder: output/nerf_synthetic/ficus [12/11 13:28:10] +Found transforms_train.json file, assuming Blender data set! [12/11 13:28:10] +Reading Training Transforms [12/11 13:28:10] +Reading Test Transforms [12/11 13:28:16] +Loading Training Cameras [12/11 13:28:29] +Loading Test Cameras [12/11 13:28:30] +Number of points at initialisation : 10000 [12/11 13:28:31] + Training progress: 0%| | 0/30000 [00:00 + training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 119, in training + training_report(tb_writer, iteration, Ll1, loss, l1_loss, iter_start.elapsed_time(iter_end), testing_iterations, scene, render, (pipe, background)) + File "/home/work/workspace/cuda124/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context + return func(*args, **kwargs) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 219, in training_report + depth = colormap(depth.cpu().numpy()[0], cmap='turbo') + File "/home/work/workspace/gs-baselines/2DGS/utils/general_utils.py", line 177, in colormap + data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8) +AttributeError: 'FigureCanvasAgg' object has no attribute 'tostring_rgb'. Did you mean: 'tostring_argb'? + Training progress: 17%|█▋ | 5000/30000 [01:25<07:09, 58.27it/s, Loss=0.00888, distort=0.00000, normal=0.00000, Points=68178] +Looking for config file in output/nerf_synthetic/hotdog/cfg_args +Config file found: output/nerf_synthetic/hotdog/cfg_args +Rendering output/nerf_synthetic/hotdog +Traceback (most recent call last): + File "/home/work/workspace/gs-baselines/2DGS/render.py", line 51, in + scene = Scene(dataset, gaussians, load_iteration=iteration, shuffle=False) + File "/home/work/workspace/gs-baselines/2DGS/scene/__init__.py", line 35, in __init__ + self.loaded_iter = searchForMaxIteration(os.path.join(self.model_path, "point_cloud")) + File "/home/work/workspace/gs-baselines/2DGS/utils/system_utils.py", line 27, in searchForMaxIteration + saved_iters = [int(fname.split("_")[-1]) for fname in os.listdir(folder)] +FileNotFoundError: [Errno 2] No such file or directory: 'output/nerf_synthetic/hotdog/point_cloud' +Scene: output/nerf_synthetic/hotdog +Unable to compute metrics for model output/nerf_synthetic/hotdog +Optimizing output/nerf_synthetic/hotdog +Output folder: output/nerf_synthetic/hotdog [12/11 13:28:08] +Found transforms_train.json file, assuming Blender data set! [12/11 13:28:08] +Reading Training Transforms [12/11 13:28:08] +Reading Test Transforms [12/11 13:28:15] +Loading Training Cameras [12/11 13:28:28] +Loading Test Cameras [12/11 13:28:29] +Number of points at initialisation : 10000 [12/11 13:28:30] + Training progress: 0%| | 0/30000 [00:00 + training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 119, in training + training_report(tb_writer, iteration, Ll1, loss, l1_loss, iter_start.elapsed_time(iter_end), testing_iterations, scene, render, (pipe, background)) + File "/home/work/workspace/cuda124/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context + return func(*args, **kwargs) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 219, in training_report + depth = colormap(depth.cpu().numpy()[0], cmap='turbo') + File "/home/work/workspace/gs-baselines/2DGS/utils/general_utils.py", line 177, in colormap + data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8) +AttributeError: 'FigureCanvasAgg' object has no attribute 'tostring_rgb'. Did you mean: 'tostring_argb'? + Training progress: 17%|█▋ | 5000/30000 [01:20<06:42, 62.04it/s, Loss=0.01201, distort=0.00000, normal=0.00000, Points=133535] +Looking for config file in output/nerf_synthetic/lego/cfg_args +Config file found: output/nerf_synthetic/lego/cfg_args +Rendering output/nerf_synthetic/lego +Traceback (most recent call last): + File "/home/work/workspace/gs-baselines/2DGS/render.py", line 51, in + scene = Scene(dataset, gaussians, load_iteration=iteration, shuffle=False) + File "/home/work/workspace/gs-baselines/2DGS/scene/__init__.py", line 35, in __init__ + self.loaded_iter = searchForMaxIteration(os.path.join(self.model_path, "point_cloud")) + File "/home/work/workspace/gs-baselines/2DGS/utils/system_utils.py", line 27, in searchForMaxIteration + saved_iters = [int(fname.split("_")[-1]) for fname in os.listdir(folder)] +FileNotFoundError: [Errno 2] No such file or directory: 'output/nerf_synthetic/lego/point_cloud' +Scene: output/nerf_synthetic/lego +Unable to compute metrics for model output/nerf_synthetic/lego +Optimizing output/nerf_synthetic/lego +Output folder: output/nerf_synthetic/lego [12/11 13:28:09] +Found transforms_train.json file, assuming Blender data set! [12/11 13:28:09] +Reading Training Transforms [12/11 13:28:09] +Reading Test Transforms [12/11 13:28:16] +Loading Training Cameras [12/11 13:28:31] +Loading Test Cameras [12/11 13:28:32] +Number of points at initialisation : 10000 [12/11 13:28:33] + Training progress: 0%| | 0/30000 [00:00 + training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 119, in training + training_report(tb_writer, iteration, Ll1, loss, l1_loss, iter_start.elapsed_time(iter_end), testing_iterations, scene, render, (pipe, background)) + File "/home/work/workspace/cuda124/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context + return func(*args, **kwargs) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 219, in training_report + depth = colormap(depth.cpu().numpy()[0], cmap='turbo') + File "/home/work/workspace/gs-baselines/2DGS/utils/general_utils.py", line 177, in colormap + data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8) +AttributeError: 'FigureCanvasAgg' object has no attribute 'tostring_rgb'. Did you mean: 'tostring_argb'? + Training progress: 17%|█▋ | 5000/30000 [01:14<06:14, 66.77it/s, Loss=0.01707, distort=0.00000, normal=0.00000, Points=111207] +Looking for config file in output/nerf_synthetic/materials/cfg_args +Config file found: output/nerf_synthetic/materials/cfg_args +Rendering output/nerf_synthetic/materials +Traceback (most recent call last): + File "/home/work/workspace/gs-baselines/2DGS/render.py", line 51, in + scene = Scene(dataset, gaussians, load_iteration=iteration, shuffle=False) + File "/home/work/workspace/gs-baselines/2DGS/scene/__init__.py", line 35, in __init__ + self.loaded_iter = searchForMaxIteration(os.path.join(self.model_path, "point_cloud")) + File "/home/work/workspace/gs-baselines/2DGS/utils/system_utils.py", line 27, in searchForMaxIteration + saved_iters = [int(fname.split("_")[-1]) for fname in os.listdir(folder)] +FileNotFoundError: [Errno 2] No such file or directory: 'output/nerf_synthetic/materials/point_cloud' +Scene: output/nerf_synthetic/materials +Unable to compute metrics for model output/nerf_synthetic/materials +Optimizing output/nerf_synthetic/materials +Output folder: output/nerf_synthetic/materials [12/11 13:28:09] +Found transforms_train.json file, assuming Blender data set! [12/11 13:28:09] +Reading Training Transforms [12/11 13:28:09] +Reading Test Transforms [12/11 13:28:15] +Loading Training Cameras [12/11 13:28:27] +Loading Test Cameras [12/11 13:28:28] +Number of points at initialisation : 10000 [12/11 13:28:29] + Training progress: 0%| | 0/30000 [00:00 + training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 119, in training + training_report(tb_writer, iteration, Ll1, loss, l1_loss, iter_start.elapsed_time(iter_end), testing_iterations, scene, render, (pipe, background)) + File "/home/work/workspace/cuda124/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context + return func(*args, **kwargs) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 219, in training_report + depth = colormap(depth.cpu().numpy()[0], cmap='turbo') + File "/home/work/workspace/gs-baselines/2DGS/utils/general_utils.py", line 177, in colormap + data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8) +AttributeError: 'FigureCanvasAgg' object has no attribute 'tostring_rgb'. Did you mean: 'tostring_argb'? + Training progress: 17%|█▋ | 5000/30000 [01:09<05:45, 72.44it/s, Loss=0.00865, distort=0.00000, normal=0.00000, Points=100914] +Looking for config file in output/nerf_synthetic/mic/cfg_args +Config file found: output/nerf_synthetic/mic/cfg_args +Rendering output/nerf_synthetic/mic +Traceback (most recent call last): + File "/home/work/workspace/gs-baselines/2DGS/render.py", line 51, in + scene = Scene(dataset, gaussians, load_iteration=iteration, shuffle=False) + File "/home/work/workspace/gs-baselines/2DGS/scene/__init__.py", line 35, in __init__ + self.loaded_iter = searchForMaxIteration(os.path.join(self.model_path, "point_cloud")) + File "/home/work/workspace/gs-baselines/2DGS/utils/system_utils.py", line 27, in searchForMaxIteration + saved_iters = [int(fname.split("_")[-1]) for fname in os.listdir(folder)] +FileNotFoundError: [Errno 2] No such file or directory: 'output/nerf_synthetic/mic/point_cloud' +Scene: output/nerf_synthetic/mic +Unable to compute metrics for model output/nerf_synthetic/mic +Optimizing output/nerf_synthetic/mic +Output folder: output/nerf_synthetic/mic [12/11 13:28:09] +Found transforms_train.json file, assuming Blender data set! [12/11 13:28:09] +Reading Training Transforms [12/11 13:28:09] +Reading Test Transforms [12/11 13:28:15] +Loading Training Cameras [12/11 13:28:28] +Loading Test Cameras [12/11 13:28:29] +Number of points at initialisation : 10000 [12/11 13:28:30] + Training progress: 0%| | 0/30000 [00:00 + training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 119, in training + training_report(tb_writer, iteration, Ll1, loss, l1_loss, iter_start.elapsed_time(iter_end), testing_iterations, scene, render, (pipe, background)) + File "/home/work/workspace/cuda124/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context + return func(*args, **kwargs) + File "/home/work/workspace/gs-baselines/2DGS/train.py", line 219, in training_report + depth = colormap(depth.cpu().numpy()[0], cmap='turbo') + File "/home/work/workspace/gs-baselines/2DGS/utils/general_utils.py", line 177, in colormap + data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8) +AttributeError: 'FigureCanvasAgg' object has no attribute 'tostring_rgb'. Did you mean: 'tostring_argb'? + Training progress: 17%|█▋ | 5000/30000 [01:49<09:05, 45.80it/s, Loss=0.04103, distort=0.00000, normal=0.00000, Points=96129] +Looking for config file in output/nerf_synthetic/ship/cfg_args +Config file found: output/nerf_synthetic/ship/cfg_args +Rendering output/nerf_synthetic/ship +Traceback (most recent call last): + File "/home/work/workspace/gs-baselines/2DGS/render.py", line 51, in + scene = Scene(dataset, gaussians, load_iteration=iteration, shuffle=False) + File "/home/work/workspace/gs-baselines/2DGS/scene/__init__.py", line 35, in __init__ + self.loaded_iter = searchForMaxIteration(os.path.join(self.model_path, "point_cloud")) + File "/home/work/workspace/gs-baselines/2DGS/utils/system_utils.py", line 27, in searchForMaxIteration + saved_iters = [int(fname.split("_")[-1]) for fname in os.listdir(folder)] +FileNotFoundError: [Errno 2] No such file or directory: 'output/nerf_synthetic/ship/point_cloud' +Scene: output/nerf_synthetic/ship +Unable to compute metrics for model output/nerf_synthetic/ship +Optimizing output/nerf_synthetic/ship +Output folder: output/nerf_synthetic/ship [12/11 13:28:08] +Found transforms_train.json file, assuming Blender data set! [12/11 13:28:08] +Reading Training Transforms [12/11 13:28:08] +Reading Test Transforms [12/11 13:28:15] +Loading Training Cameras [12/11 13:28:29] +Loading Test Cameras [12/11 13:28:30] +Number of points at initialisation : 10000 [12/11 13:28:31] + Training progress: 0%| | 0/30000 [00:00