Add files using upload-large-folder tool

scans/table/recon/table_v1/intrinsics.json

@@ -0,0 +1,14 @@
+{
+  "session": "converted_datasets/sessions/session_20261011_161849_867460",
+  "stream_id": "zed_12933256_left_rgb",
+  "fx": 1463.005859375,
+  "fy": 1463.005859375,
+  "cx": 1172.2901611328125,
+  "cy": 608.9979248046875,
+  "width": 2208,
+  "height": 1242,
+  "distortion_model": "zed_sdk",
+  "distortion_coefficients": null,
+  "stride": 6,
+  "num_frames": 302
+}

scans/table/recon/table_v2/gsplat_full/RUN_README.md

@@ -0,0 +1,28 @@
+# gsplat COLMAP training run
+
+- generation timestamp: 2026-10-15 17:15:14 UTC
+- repo git commit: 46f912eefa2dce720b79df547085b8bbdb858ad2
+- gsplat version: 1.5.3
+- gsplat examples dir: /home/shaunak/Code/grasp/gsplat/examples
+- dataset path: /home/shaunak/Code/grasp/recon_runs/table_v2
+- dataset image count: 302
+- camera: PINHOLE 2208x1242 fx=1463.005859375 fy=1463.005859375 cx=1172.2901611328125 cy=608.9979248046875
+- registered image count: 291
+- points3D count: 27476
+- resolved init_type: sfm
+- resolved normalize_world_space: True
+- resolved data_factor: 2
+- dry run: False
+
+## Command
+
+```bash
+cd /home/shaunak/Code/grasp/gsplat/examples
+/home/shaunak/Code/grasp/belt_perception/.venv/bin/python simple_trainer.py default --data-dir /home/shaunak/Code/grasp/recon_runs/table_v2 --result-dir /home/shaunak/Code/grasp/recon_runs/table_v2/gsplat_full --data-factor 2 --init-type sfm --init-num-pts 100000 --max-steps 30000 --test-every 8 --normalize-world-space --disable-viewer --no-disable-video --save-ply
+```
+
+## Notes
+
+- empty points3D requires random init
+- normalize_world_space is disabled for empty points3D exports
+- data_factor must match an existing images/ or images_N/ directory

scans/table/recon/table_v2/gsplat_full/cfg.yml

@@ -0,0 +1,105 @@
+antialiased: false
+app_embed_dim: 16
+app_opt: false
+app_opt_lr: 0.001
+app_opt_reg: 1.0e-06
+batch_size: 1
+bilateral_grid_fused: false
+bilateral_grid_shape: !!python/tuple
+- 16
+- 16
+- 8
+camera_model: pinhole
+ckpt: null
+color_correct_method: affine
+compression: null
+data_dir: /home/shaunak/Code/grasp/recon_runs/table_v2
+data_factor: 2
+data_type: colmap
+depth_lambda: 0.01
+depth_loss: false
+disable_video: false
+disable_viewer: true
+eval_steps:
+- 7000
+- 30000
+far_plane: 10000000000.0
+global_scale: 1.0
+init_extent: 3.0
+init_num_pts: 100000
+init_opa: 0.1
+init_scale: 1.0
+init_type: sfm
+load_exposure: true
+lpips_net: alex
+max_steps: 30000
+means_lr: 0.00016
+ncore_camera_ids: []
+ncore_duration_sec: null
+ncore_intrinsics_component_group: default
+ncore_lidar_color_generic_data_name: rgb
+ncore_lidar_ids: []
+ncore_masks_component_group: default
+ncore_max_lidar_points: 500000
+ncore_poses_component_group: default
+ncore_seek_offset_sec: null
+near_plane: 0.01
+normalize_world_space: true
+opacities_lr: 0.05
+opacity_reg: 0.0
+packed: false
+patch_size: null
+ply_steps:
+- 7000
+- 30000
+port: 8080
+pose_noise: 0.0
+pose_opt: false
+pose_opt_lr: 1.0e-05
+pose_opt_reg: 1.0e-06
+post_processing: null
+ppisp_controller_activation_num_steps: 25000
+ppisp_controller_distillation: true
+ppisp_use_controller: true
+quats_lr: 0.001
+random_bkgd: false
+render_traj_path: interp
+result_dir: /home/shaunak/Code/grasp/recon_runs/table_v2/gsplat_full
+save_ply: true
+save_steps:
+- 7000
+- 30000
+scale_reg: 0.0
+scales_lr: 0.005
+sh0_lr: 0.0025
+shN_lr: 0.000125
+sh_degree: 3
+sh_degree_interval: 1000
+sh_fp16: false
+sparse_grad: false
+ssim_lambda: 0.2
+steps_scaler: 1.0
+strategy: !!python/object:gsplat.strategy.default.DefaultStrategy
+  absgrad: false
+  grow_grad2d: 0.0002
+  grow_scale2d: 0.05
+  grow_scale3d: 0.01
+  key_for_gradient: means2d
+  pause_refine_after_reset: 0
+  prune_opa: 0.005
+  prune_scale2d: 0.15
+  prune_scale3d: 0.1
+  refine_every: 100
+  refine_scale2d_stop_iter: 0
+  refine_start_iter: 500
+  refine_stop_iter: 15000
+  reset_every: 3000
+  revised_opacity: false
+  verbose: true
+tb_every: 100
+tb_save_image: false
+test_every: 8
+use_color_correction_metric: false
+visible_adam: false
+with_eval3d: false
+with_ut: false

scans/table/recon/table_v2/gsplat_full/stats/train_step29999_rank0.json

@@ -0,0 +1 @@
+{"mem": 1.737058162689209, "ellipse_time": 5574.137261629105, "num_GS": 1031968}

scans/table/recon/table_v2/gsplat_full/stats/train_step6999_rank0.json

@@ -0,0 +1 @@
+{"mem": 1.274853229522705, "ellipse_time": 1209.080563545227, "num_GS": 779286}

scans/table/recon/table_v2/gsplat_full/stats/val_step29999.json

@@ -0,0 +1 @@
+{"psnr": 25.53499412536621, "ssim": 0.8571839332580566, "lpips": 0.249567449092865, "ellipse_time": 0.007898292026004276, "num_GS": 1031968}

scans/table/recon/table_v2/gsplat_full/stats/val_step6999.json

@@ -0,0 +1 @@
+{"psnr": 24.753389358520508, "ssim": 0.8550090193748474, "lpips": 0.27767589688301086, "ellipse_time": 0.006776970786017341, "num_GS": 779286}

scans/table/recon/table_v2/gsplat_smoke/RUN_README.md

@@ -0,0 +1,28 @@
+# gsplat COLMAP training run
+
+- generation timestamp: 2026-10-15 17:10:29 UTC
+- repo git commit: 46f912eefa2dce720b79df547085b8bbdb858ad2
+- gsplat version: 1.5.3
+- gsplat examples dir: /home/shaunak/Code/grasp/gsplat/examples
+- dataset path: /home/shaunak/Code/grasp/recon_runs/table_v2
+- dataset image count: 302
+- camera: PINHOLE 2208x1242 fx=1463.005859375 fy=1463.005859375 cx=1172.2901611328125 cy=608.9979248046875
+- registered image count: 291
+- points3D count: 27476
+- resolved init_type: sfm
+- resolved normalize_world_space: True
+- resolved data_factor: 2
+- dry run: False
+
+## Command
+
+```bash
+cd /home/shaunak/Code/grasp/gsplat/examples
+/home/shaunak/Code/grasp/belt_perception/.venv/bin/python simple_trainer.py default --data-dir /home/shaunak/Code/grasp/recon_runs/table_v2 --result-dir /home/shaunak/Code/grasp/recon_runs/table_v2/gsplat_smoke --data-factor 2 --init-type sfm --init-num-pts 100000 --max-steps 20 --test-every 8 --normalize-world-space --disable-viewer --disable-video --no-save-ply
+```
+
+## Notes
+
+- empty points3D requires random init
+- normalize_world_space is disabled for empty points3D exports
+- data_factor must match an existing images/ or images_N/ directory

scans/table/recon/table_v2/gsplat_smoke/cfg.yml

@@ -0,0 +1,105 @@
+antialiased: false
+app_embed_dim: 16
+app_opt: false
+app_opt_lr: 0.001
+app_opt_reg: 1.0e-06
+batch_size: 1
+bilateral_grid_fused: false
+bilateral_grid_shape: !!python/tuple
+- 16
+- 16
+- 8
+camera_model: pinhole
+ckpt: null
+color_correct_method: affine
+compression: null
+data_dir: /home/shaunak/Code/grasp/recon_runs/table_v2
+data_factor: 2
+data_type: colmap
+depth_lambda: 0.01
+depth_loss: false
+disable_video: true
+disable_viewer: true
+eval_steps:
+- 7000
+- 30000
+far_plane: 10000000000.0
+global_scale: 1.0
+init_extent: 3.0
+init_num_pts: 100000
+init_opa: 0.1
+init_scale: 1.0
+init_type: sfm
+load_exposure: true
+lpips_net: alex
+max_steps: 20
+means_lr: 0.00016
+ncore_camera_ids: []
+ncore_duration_sec: null
+ncore_intrinsics_component_group: default
+ncore_lidar_color_generic_data_name: rgb
+ncore_lidar_ids: []
+ncore_masks_component_group: default
+ncore_max_lidar_points: 500000
+ncore_poses_component_group: default
+ncore_seek_offset_sec: null
+near_plane: 0.01
+normalize_world_space: true
+opacities_lr: 0.05
+opacity_reg: 0.0
+packed: false
+patch_size: null
+ply_steps:
+- 7000
+- 30000
+port: 8080
+pose_noise: 0.0
+pose_opt: false
+pose_opt_lr: 1.0e-05
+pose_opt_reg: 1.0e-06
+post_processing: null
+ppisp_controller_activation_num_steps: 25000
+ppisp_controller_distillation: true
+ppisp_use_controller: true
+quats_lr: 0.001
+random_bkgd: false
+render_traj_path: interp
+result_dir: /home/shaunak/Code/grasp/recon_runs/table_v2/gsplat_smoke
+save_ply: false
+save_steps:
+- 7000
+- 30000
+scale_reg: 0.0
+scales_lr: 0.005
+sh0_lr: 0.0025
+shN_lr: 0.000125
+sh_degree: 3
+sh_degree_interval: 1000
+sh_fp16: false
+sparse_grad: false
+ssim_lambda: 0.2
+steps_scaler: 1.0
+strategy: !!python/object:gsplat.strategy.default.DefaultStrategy
+  absgrad: false
+  grow_grad2d: 0.0002
+  grow_scale2d: 0.05
+  grow_scale3d: 0.01
+  key_for_gradient: means2d
+  pause_refine_after_reset: 0
+  prune_opa: 0.005
+  prune_scale2d: 0.15
+  prune_scale3d: 0.1
+  refine_every: 100
+  refine_scale2d_stop_iter: 0
+  refine_start_iter: 500
+  refine_stop_iter: 15000
+  reset_every: 3000
+  revised_opacity: false
+  verbose: true
+tb_every: 100
+tb_save_image: false
+test_every: 8
+use_color_correction_metric: false
+visible_adam: false
+with_eval3d: false
+with_ut: false

scans/table/recon/table_v2/gsplat_smoke/stats/train_step0019_rank0.json

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+{"mem": 0.21768426895141602, "ellipse_time": 3.844325304031372, "num_GS": 27476}

scans/table/recon/table_v2/intrinsics.json

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+{
+  "session": "converted_datasets/sessions/session_20261011_161849_867460",
+  "stream_id": "zed_12933256_left_rgb",
+  "fx": 1463.005859375,
+  "fy": 1463.005859375,
+  "cx": 1172.2901611328125,
+  "cy": 608.9979248046875,
+  "width": 2208,
+  "height": 1242,
+  "distortion_model": "zed_sdk",
+  "distortion_coefficients": null,
+  "stride": 6,
+  "pick": "sharpest",
+  "num_frames": 302
+}

scans/table/recon/table_v2/sharpness.csv

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scans/table/recon/table_v2/sparse/0/cameras.txt

@@ -0,0 +1,4 @@
+# Camera list with one line of data per camera:
+#   CAMERA_ID, MODEL, WIDTH, HEIGHT, PARAMS[]
+# Number of cameras: 1
+1 PINHOLE 2208 1242 1463.005859375 1463.005859375 1172.2901611328125 608.9979248046875

scans/table/recon/table_v2/sparse/0/frames.txt

@@ -0,0 +1,294 @@
+# Frame list with one line of data per frame:
+#   FRAME_ID, RIG_ID, RIG_FROM_WORLD[QW, QX, QY, QZ, TX, TY, TZ], NUM_DATA_IDS, DATA_IDS[] as (SENSOR_TYPE, SENSOR_ID, DATA_ID)
+# Number of frames: 291
+1 1 0.48593437872866285 -0.12874619715849434 0.78260924010219524 0.36717158603775329 0.54954433928312796 -1.709529257340155 3.89749506361288 1 CAMERA 1 1
+2 1 0.32260060259993495 -0.067333773350515422 0.85023588492741053 0.41048015073842925 1.3663680347721352 -1.8195044699528073 3.7456321120196323 1 CAMERA 1 2
+3 1 0.5012511972122986 -0.12355332119623499 0.77716576388631908 0.35985440049777295 0.36664565710877745 -1.7460422442469099 3.9178370456741343 1 CAMERA 1 3
+4 1 0.50886625581233569 -0.11509874892486255 0.76364792508981405 0.38032782990137287 0.29024502289016979 -1.9615457301385542 3.8172300049659187 1 CAMERA 1 4
+5 1 0.14103993302091011 -0.042836238665334814 0.91348866665181361 0.37922453750931712 2.0341208262344819 -1.1127060451263118 3.5960510538736976 1 CAMERA 1 5
+6 1 0.41435495542000894 -0.12495214625881777 0.80782934610259605 0.40013582648851809 1.0478793329763012 -1.7894475239229033 3.7884250168020959 1 CAMERA 1 6
+7 1 0.42943366831154939 -0.13024823980542524 0.79987785218126628 0.39851918666227232 1.0662882370877409 -1.7764891777933753 3.7699942273611544 1 CAMERA 1 7
+8 1 0.49846064919473826 -0.13092786131156295 0.77947478109043411 0.35610945224854684 0.39950753469344397 -1.6657072729489328 3.9579757715297386 1 CAMERA 1 8
+9 1 0.24963431861110105 -0.064488707560062475 0.88202752259033801 0.39440000375501366 1.6195310320689082 -1.4421321767561668 3.5860216969336389 1 CAMERA 1 9
+10 1 0.50190513300985595 -0.14839527293793839 0.76805121753809469 0.36900868237249362 0.56412282418913207 -1.6954893383847112 3.9097906427070876 1 CAMERA 1 10
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scans/table/recon/table_v2/sparse/0/rigs.txt

@@ -0,0 +1,4 @@
+# Rig calib list with one line of data per calib:
+#   RIG_ID, NUM_SENSORS, REF_SENSOR_TYPE, REF_SENSOR_ID, SENSORS[] as (SENSOR_TYPE, SENSOR_ID, HAS_POSE, [QW, QX, QY, QZ, TX, TY, TZ])
+# Number of rigs: 1
+1 1 CAMERA 1

scans/table/recon/waft_test3.log

@@ -0,0 +1,98 @@
+using MLP layer as FFN
+Loading pretrained weights from Hugging Face hub (timm/vit_small_patch16_224.augreg_in21k_ft_in1k)
+HTTP Request: HEAD https://huggingface.co/timm/vit_small_patch16_224.augreg_in21k_ft_in1k/resolve/main/model.safetensors "HTTP/1.1 302 Found"
+[timm/vit_small_patch16_224.augreg_in21k_ft_in1k] Safe alternative available for 'pytorch_model.bin' (as 'model.safetensors'). Loading weights using safetensors.
+Loading pretrained weights from Hugging Face hub (timm/vit_small_patch16_224.augreg_in21k_ft_in1k)
+HTTP Request: HEAD https://huggingface.co/timm/vit_small_patch16_224.augreg_in21k_ft_in1k/resolve/main/model.safetensors "HTTP/1.1 302 Found"
+[timm/vit_small_patch16_224.augreg_in21k_ft_in1k] Safe alternative available for 'pytorch_model.bin' (as 'model.safetensors'). Loading weights using safetensors.
+/home/shaunak/Code/grasp/belt_perception/third_party/WAFT-Stereo/model/utils.py:68: UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details.
+  warped_feature = F.grid_sample(feature, sample_grid, mode='bilinear', padding_mode=padding_mode)
+Warning: checkpoint for depth anything v2 vitl not found, using random weights.
+Traceback (most recent call last):
+  File "/home/shaunak/Code/grasp/belt_perception/scripts/append_frontier_stereo_depth_to_session.py", line 166, in <module>
+    raise SystemExit(main())
+                     ^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/scripts/append_frontier_stereo_depth_to_session.py", line 144, in main
+    result = execute_append(
+             ^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/dataset_converter/derived_depth/append.py", line 480, in execute_append
+    frame_rows, video_row, summary_row = export_stream_from_frames(
+                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/dataset_converter/session_export.py", line 1078, in export_stream_from_frames
+    for frame in frames:
+  File "/home/shaunak/Code/grasp/belt_perception/dataset_converter/derived_depth/append.py", line 351, in generate_source_frames
+    depth_m = runner.infer_batch(
+              ^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/belt_perception/waft_stereo_wrapper/runner.py", line 184, in infer_batch
+    disparity = self.infer_disparity(left_batch, right_batch)
+                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/belt_perception/waft_stereo_wrapper/runner.py", line 171, in infer_disparity
+    output = self.model.heirarchical_inference(
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/third_party/WAFT-Stereo/algorithms/waft.py", line 204, in heirarchical_inference
+    output = self.inference(sample, size=size, factor=factor_list[i], disp_init=disp_init)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/third_party/WAFT-Stereo/algorithms/waft.py", line 121, in inference
+    output = self.forward(sample, disp_init=disp_init)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/third_party/WAFT-Stereo/algorithms/waft.py", line 67, in forward
+    fmap1, fmap2, net = self.encoder(torch.stack([image1, image2], dim=1))
+                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
+    return forward_call(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/third_party/WAFT-Stereo/model/encoder/dav2.py", line 59, in forward
+    fmap_feats = self.fmap_upsample(fmap_feats)
+                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
+    return forward_call(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/third_party/WAFT-Stereo/model/layers/dpt.py", line 220, in forward
+    out_rn[-i] = self.refine[-i](out_rn[-i], up_feat, size=out_rn[-i].shape[2:])
+                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
+    return forward_call(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/third_party/WAFT-Stereo/model/layers/dpt.py", line 115, in forward
+    output = self.resConfUnit2(output)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
+    return forward_call(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/third_party/WAFT-Stereo/model/layers/block.py", line 20, in forward
+    return self.conv(x) + self.skip_conv(x)
+           ^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
+    return forward_call(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/container.py", line 253, in forward
+    input = module(input)
+            ^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
+    return forward_call(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/conv.py", line 553, in forward
+    return self._conv_forward(input, self.weight, self.bias)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shaunak/Code/grasp/belt_perception/.venv/lib/python3.11/site-packages/torch/nn/modules/conv.py", line 548, in _conv_forward
+    return F.conv2d(
+           ^^^^^^^^^
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1.48 GiB. GPU 0 has a total capacity of 7.62 GiB of which 343.62 MiB is free. Including non-PyTorch memory, this process has 7.27 GiB memory in use. Of the allocated memory 7.03 GiB is allocated by PyTorch, and 127.60 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)