159 lines
90 KiB
Plaintext
159 lines
90 KiB
Plaintext
[00:00] Crash dump logging enabled: /Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/comfy-test-logs/DepthAnythingV3-1716/macos-cpu/crash_dump.log
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[00:00]
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[00:00] [1/3] REGISTRATION
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[00:00] ----------------------------------------
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[00:00]
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[DEBUG] server=None, server_url=http://127.0.0.1:8188, api=None
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[00:00]
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Connecting to existing server at http://127.0.0.1:8188...
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[00:00] Connecting to existing server at http://127.0.0.1:8188...
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[00:00] Connected to server! (attempt 1, 0.0s)
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[00:00] Checking for import errors in server logs...
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[00:00] No import errors detected
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[00:00] Found 1116 registered nodes
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[00:00] [REGISTRATION] PASSED
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[00:00]
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[00:00] [2/3] INSTANTIATION
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[00:00] ----------------------------------------
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[00:00]
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[DEBUG] server=<comfy_test.comfyui.server.ExternalComfyUIServer object at 0x1048a7490>, server_url=http://127.0.0.1:8188, api=<comfy_test.comfyui.api.ComfyUIAPI object at 0x1048a7310>
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[00:00] Testing node constructors...
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[00:01] All 15 node(s) instantiated successfully!
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[00:01] [INSTANTIATION] PASSED
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[00:01]
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[00:01] [3/3] EXECUTION
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[00:01] ----------------------------------------
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[00:01]
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[DEBUG] server=<comfy_test.comfyui.server.ExternalComfyUIServer object at 0x1048a7490>, server_url=http://127.0.0.1:8188, api=<comfy_test.comfyui.api.ComfyUIAPI object at 0x1048a7310>
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[00:01] CPU runner - will execute 4 workflow(s)
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[00:01] Running 7 workflow(s) (all with videos)...
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[00:01] Starting headless browser...
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[00:02] macOS — using Apple Metal GPU via ANGLE
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[00:04] Capturing execution frames: advanced.json
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[00:13] Frame 1 saved (frame_000.jpg, t=0.0s)
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[00:13] Validating workflow...
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[00:13] Queuing workflow for execution...
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[00:15] Frame 2 saved (frame_001.jpg, t=2.6s)
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[00:15] [capture-periodic] freeze=4ms shot=467ms unfreeze=27ms saved=True
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[00:18] Frame 3 saved (frame_002.jpg, t=5.2s)
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[00:18] [capture-periodic] freeze=5ms shot=352ms unfreeze=43ms saved=True
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[00:20] [capture-loop] iter=50 t=7.2s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=4 ram=3.8/7.0GB (60%) swap=0.0/0.0GB (0%) cpu=60% browser_rss=0.70GB
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[00:24] Frame 4 saved (frame_003.jpg, t=10.0s)
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[00:24] [capture-periodic] freeze=5ms shot=1115ms unfreeze=109ms saved=True
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[00:27] Frame 5 saved (frame_004.jpg, t=13.4s)
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[00:27] [capture-periodic] freeze=13ms shot=909ms unfreeze=220ms saved=True
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[00:30] Frame 6 saved (frame_005.jpg, t=16.7s)
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[00:30] [capture-periodic] freeze=17ms shot=930ms unfreeze=186ms saved=True
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[00:31] [capture-loop] iter=100 t=18.4s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=22 ram=3.7/7.0GB (62%) swap=0.0/0.0GB (0%) cpu=90% browser_rss=0.58GB
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[00:33] Frame 7 saved (frame_006.jpg, t=20.0s)
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[00:33] [capture-periodic] freeze=39ms shot=651ms unfreeze=38ms saved=True
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[00:36] Frame 8 saved (frame_007.jpg, t=22.9s)
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[00:36] [capture-periodic] freeze=54ms shot=441ms unfreeze=35ms saved=True
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[00:38] Frame 9 saved (frame_008.jpg, t=25.5s)
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[00:38] [capture-periodic] freeze=4ms shot=272ms unfreeze=27ms saved=True
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[00:39] [capture-loop] iter=150 t=26.5s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=4 ram=3.7/7.0GB (62%) swap=0.0/0.0GB (0%) cpu=71% browser_rss=0.60GB
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[00:46] [capture-loop] iter=200 t=33.8s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=8 ram=3.5/7.0GB (65%) swap=0.0/0.0GB (0%) cpu=52% browser_rss=0.58GB
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[00:54] [capture-loop] iter=250 t=41.2s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=5 ram=3.8/7.0GB (76%) swap=0.0/0.0GB (0%) cpu=65% browser_rss=0.44GB
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[01:00] [capture-loop] iter=300 t=47.7s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=7 ram=4.4/7.0GB (80%) swap=0.0/0.0GB (0%) cpu=60% browser_rss=0.44GB
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[01:07] [capture-loop] iter=350 t=54.8s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=19 ram=4.9/7.0GB (88%) swap=0.0/0.0GB (0%) cpu=52% browser_rss=0.44GB
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[01:20] [capture-loop] iter=400 t=67.3s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=5 ram=2.7/7.0GB (77%) swap=0.3/1.0GB (28%) cpu=70% browser_rss=0.26GB
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[01:25] Node executed (1 total), capturing...
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[01:26] Frame 10 saved (frame_009.jpg, t=72.7s)
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[01:26] [capture-node] freeze=563ms shot=433ms unfreeze=4ms saved=True
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[01:26] Node executed (8 total), capturing...
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[01:27] Frame 11 saved (frame_010.jpg, t=74.0s)
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[01:27] [capture-node] freeze=4ms shot=356ms unfreeze=0ms saved=True
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[01:27] Execution complete (t=74.0s)
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[01:27] Captured 11 unique frames over 74.37s
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[01:27] [debug] iframes: 0
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[01:27] [timing] trigger_3d_previews: 0.0s
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[01:29] Saved high-quality screenshot: advanced_executed.png
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[01:29] [timing] final_screenshot: 0.3s
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[01:29] Capturing execution frames: advanced_3d.json
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[01:38] Frame 1 saved (frame_000.jpg, t=0.0s)
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[01:38] Validating workflow...
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[01:38] Queuing workflow for execution...
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[01:41] Frame 2 saved (frame_001.jpg, t=2.4s)
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[01:41] [capture-periodic] freeze=6ms shot=847ms unfreeze=40ms saved=True
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[01:43] Frame 3 saved (frame_002.jpg, t=5.3s)
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[01:43] [capture-periodic] freeze=4ms shot=298ms unfreeze=12ms saved=True
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[01:45] [capture-loop] iter=50 t=7.3s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=5 ram=5.3/7.0GB (82%) swap=0.6/1.0GB (57%) cpu=66% browser_rss=0.49GB
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[01:46] Frame 4 saved (frame_003.jpg, t=7.8s)
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[01:46] [capture-periodic] freeze=7ms shot=289ms unfreeze=48ms saved=True
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[01:47] Node executed (2 total), capturing...
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[01:47] Frame 5 saved (frame_004.jpg, t=9.2s)
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[01:47] [capture-node] freeze=6ms shot=330ms unfreeze=0ms saved=True
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[01:47] Execution complete (t=9.2s)
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[01:47] Captured 5 unique frames over 9.65s
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[01:47] [debug] iframes: 1
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[01:47] [debug] iframe[0]: src=http://127.0.0.1:8188/extensions/ComfyUI-DepthAnythingV3/viewer_vtk.html?v=17783, canvas=486x430, rafFrozen=True
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[01:47] [timing] trigger_3d_previews: 0.0s
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[01:49] Saved high-quality screenshot: advanced_3d_executed.png
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[01:50] [timing] final_screenshot: 0.3s
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[01:50] Capturing execution frames: advanced_3d_multiview.json
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[01:57] Frame 1 saved (frame_000.jpg, t=0.0s)
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[01:57] Validating workflow...
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[01:57] Queuing workflow for execution...
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[01:57] Node executed (1 total), capturing...
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[01:59] Frame 2 saved (frame_001.jpg, t=1.6s)
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[01:59] [capture-node] freeze=12ms shot=925ms unfreeze=94ms saved=True
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[02:01] Frame 3 saved (frame_002.jpg, t=4.8s)
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[02:01] [capture-periodic] freeze=4ms shot=602ms unfreeze=25ms saved=True
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[02:04] Frame 4 saved (frame_003.jpg, t=7.4s)
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[02:04] [capture-periodic] freeze=4ms shot=534ms unfreeze=33ms saved=True
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[02:05] [capture-loop] iter=50 t=9.1s state={'complete': False, 'error': None, 'executedCount': 1, 'wsState': 1} eval_ms=5 ram=5.1/7.0GB (80%) swap=0.5/1.0GB (53%) cpu=69% browser_rss=0.55GB
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[02:28] Frame 5 saved (frame_004.jpg, t=10.1s)
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[02:28] [capture-periodic] freeze=5ms shot=20373ms unfreeze=555ms saved=True
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[02:32] Frame 6 saved (frame_005.jpg, t=33.8s)
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[02:32] [capture-periodic] freeze=20ms shot=1831ms unfreeze=33ms saved=True
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[02:35] [capture-loop] iter=100 t=39.4s state={'complete': False, 'error': None, 'executedCount': 1, 'wsState': 1} eval_ms=13 ram=4.8/7.0GB (73%) swap=1.0/2.0GB (50%) cpu=67% browser_rss=0.20GB
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[02:59] Frame 7 saved (frame_006.jpg, t=43.7s)
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[02:59] [capture-periodic] freeze=19ms shot=18753ms unfreeze=256ms saved=True
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[03:03] Frame 8 saved (frame_007.jpg, t=64.9s)
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[03:03] [capture-periodic] freeze=6ms shot=1074ms unfreeze=106ms saved=True
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[03:03] Execution complete (t=64.9s)
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[03:03] Execution error: {'prompt_id': '3bed6e0d-25f9-4926-af93-460fe72bc08b', 'node_id': '38', 'node_type': 'DA3_MultiViewPointCloud', 'executed': ['27', '39', '21', '3'], 'exception_message': 'Depth input appears to be normalized (max=1.0302) instead of raw/metric depth. Multi-view point cloud fusion requires raw metric depth values. Please use DepthAnythingV3_MultiView node with normalization_mode=\'Raw\' and connect the depth output to this node\'s depths input. If you think this is a mistake, feel free to toggle allow_around_1.\n\nWorker traceback:\nTraceback (most recent call last):\n File "/var/folders/tb/y368xp_x10s3ty1b_mtl5mxr0000gn/T/comfyui_pvenv__zn50zv9/persistent_worker.py", line 1762, in main\n result = method(**inputs)\n ^^^^^^^^^^^^^^^^\n File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/comfy_api/latest/_io.py", line 1833, in EXECUTE_NORMALIZED\n to_return = cls.execute(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/custom_nodes/ComfyUI-DepthAnythingV3/nodes/nodes_multiview.py", line 690, in execute\n raise ValueError(\nValueError: Depth input appears to be normalized (max=1.0302) instead of raw/metric depth. Multi-view point cloud fusion requires raw metric depth values. Please use DepthAnythingV3_MultiView node with normalization_mode=\'Raw\' and connect the depth output to this node\'s depths input. If you think this is a mistake, feel free to toggle allow_around_1.\n\n', 'exception_type': 'comfy_env.isolation.workers.base.WorkerError', 'traceback': [' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/execution.py", line 535, in execute\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n', ' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/execution.py", line 335, in get_output_data\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n', ' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/execution.py", line 309, in _async_map_node_over_list\n await process_inputs(input_dict, i)\n', ' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/execution.py", line 297, in process_inputs\n result = f(**inputs)\n ^^^^^^^^^^^\n', ' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/.venv/lib/python3.11/site-packages/comfy_env/isolation/metadata.py", line 536, in proxy\n result = worker.call_method(\n ^^^^^^^^^^^^^^^^^^^\n', ' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/.venv/lib/python3.11/site-packages/comfy_env/isolation/workers/subprocess.py", line 674, in call_method\n raise WorkerError(\n'], 'current_inputs': {'extrinsics': ['{\n "extrinsics": [\n {\n "image_0": [\n [\n 0.9999998211860657,\n -0.0005656706052832305,\n -0.00022657914087176323,\n 0.00018741225358098745\n ],\n [\n 0.000565818976610899,\n 0.9999996423721313,\n 0.0006551882834173739,\n -0.0001278371928492561\n ],\n [\n 0.0002262084453832358,\n -0.0006553163402713835,\n 0.9999997615814209,\n 0.00023603401496075094\n ]\n ]\n }\n ]\n}', '{\n "extrinsics": [\n {\n "image_0": [\n [\n 0.9999998211860657,\n 0.00017460108210798353,\n 0.0005202052416279912,\n 0.0003719621745403856\n ],\n [\n -0.0001742378663038835,\n 0.9999997615814209,\n -0.0006981720798648894,\n 2.779594979074318e-05\n ],\n [\n -0.0005203270702622831,\n 0.0006980813923291862,\n 0.9999996423721313,\n -0.00018597673624753952\n ]\n ]\n }\n ]\n}'], 'intrinsics': ['{\n "intrinsics": [\n {\n "image_0": [\n [\n 1086.2222900390625,\n 0.0,\n 604.0\n ],\n [\n 0.0,\n 1073.156494140625,\n 340.0\n ],\n [\n 0.0,\n 0.0,\n 1.0\n ]\n ]\n }\n ]\n}', '{\n "intrinsics": [\n {\n "image_0": [\n [\n 1206.2451171875,\n 0.0,\n 604.0\n ],\n [\n 0.0,\n 1191.7357177734375,\n 340.0\n ],\n [\n 0.0,\n 0.0,\n 1.0\n ]\n ]\n }\n ]\n}'], 'confidence_threshold': [0.3], 'downsample': [4], 'use_icp': [False], 'allow_around_1': [False], 'filter_outliers': [True], 'outlier_percentage': [5], 'depths': ['tensor([[[[2.2783, 2.2783, 2.2783],\n [2.3971, 2.3971, 2.3971],\n [2.4024, 2.4024, 2.4024],\n [2.4413, 2.4413, 2.4413],\n [2.4575, 2.4575, 2.4575],\n [2.5005, 2.5005, 2.5005],\n ...,\n [0.5850, 0.5850, 0.5850],\n [0.6002, 0.6002, 0.6002],\n [0.6126, 0.6126, 0.6126],\n [0.6116, 0.6116, 0.6116],\n [0.5946, 0.5946, 0.5946],\n [0.6213, 0.6213, 0.6213]],\n\n [[2.4074, 2.4074, 2.4074],\n [2.3734, 2.3734, 2.3734],\n [2.3657, 2.3657, 2.3657],\n [2.3895, 2.3895, 2.3895],\n [2.4327, 2.4327, 2.4327],\n [2.4825, 2.4825, 2.4825],\n ...,\n [0.5775, 0.5775, 0.5775],\n [0.5878, 0.5878, 0.5878],\n [0.6050, 0.6050, 0.6050],\n [0.6096, 0.6096, 0.6096],\n [0.6084, 0.6084, 0.6084],\n [0.5969, 0.5969, 0.5969]],\n\n [[2.3300, 2.3300, 2.3300],\n [2.3779, 2.3779, 2.3779],\n [2.3220, 2.3220, 2.3220],\n [2.3551, 2.3551, 2.3551],\n [2.3910, 2.3910, 2.3910],\n [2.4299, 2.4299, 2.4299],\n ...,\n [0.5814, 0.5814, 0.5814],\n [0.5922, 0.5922, 0.5922],\n [0.6092, 0.6092, 0.6092],\n [0.6136, 0.6136, 0.6136],\n [0.6157, 0.6157, 0.6157],\n [0.6142, 0.6142, 0.6142]],\n\n [[2.2869, 2.2869, 2.2869],\n [2.3868, 2.3868, 2.3868],\n [2.3343, 2.3343, 2.3343],\n [2.3674, 2.3674, 2.3674],\n [2.4019, 2.4019, 2.4019],\n [2.4264, 2.4264, 2.4264],\n ...,\n [0.5805, 0.5805, 0.5805],\n [0.5912, 0.5912, 0.5912],\n [0.6062, 0.6062, 0.6062],\n [0.6109, 0.6109, 0.6109],\n [0.6102, 0.6102, 0.6102],\n [0.6125, 0.6125, 0.6125]],\n\n [[2.2942, 2.2942, 2.2942],\n [2.4084, 2.4084, 2.4084],\n [2.3634, 2.3634, 2.3634],\n [2.3800, 2.3800, 2.3800],\n [2.4075, 2.4075, 2.4075],\n [2.4276, 2.4276, 2.4276],\n ...,\n [0.5763, 0.5763, 0.5763],\n [0.5869, 0.5869, 0.5869],\n [0.6009, 0.6009, 0.6009],\n [0.6054, 0.6054, 0.6054],\n [0.6034, 0.6034, 0.6034],\n [0.6058, 0.6058, 0.6058]],\n\n [[2.3065, 2.3065, 2.3065],\n [2.4346, 2.4346, 2.4346],\n [2.3916, 2.3916, 2.3916],\n [2.4178, 2.4178, 2.4178],\n [2.4234, 2.4234, 2.4234],\n [2.4390, 2.4390, 2.4390],\n ...,\n [0.5719, 0.5719, 0.5719],\n [0.5821, 0.5821, 0.5821],\n [0.5960, 0.5960, 0.5960],\n [0.6006, 0.6006, 0.6006],\n [0.5946, 0.5946, 0.5946],\n [0.6008, 0.6008, 0.6008]],\n\n ...,\n\n [[0.5395, 0.5395, 0.5395],\n [0.5402, 0.5402, 0.5402],\n [0.5399, 0.5399, 0.5399],\n [0.5397, 0.5397, 0.5397],\n [0.5394, 0.5394, 0.5394],\n [0.5392, 0.5392, 0.5392],\n ...,\n [0.5638, 0.5638, 0.5638],\n [0.5638, 0.5638, 0.5638],\n [0.5647, 0.5647, 0.5647],\n [0.5654, 0.5654, 0.5654],\n [0.5665, 0.5665, 0.5665],\n [0.5654, 0.5654, 0.5654]],\n\n [[0.5388, 0.5388, 0.5388],\n [0.5388, 0.5388, 0.5388],\n [0.5383, 0.5383, 0.5383],\n [0.5376, 0.5376, 0.5376],\n [0.5375, 0.5375, 0.5375],\n [0.5371, 0.5371, 0.5371],\n ...,\n [0.5628, 0.5628, 0.5628],\n [0.5629, 0.5629, 0.5629],\n [0.5637, 0.5637, 0.5637],\n [0.5642, 0.5642, 0.5642],\n [0.5656, 0.5656, 0.5656],\n [0.5643, 0.5643, 0.5643]],\n\n [[0.5371, 0.5371, 0.5371],\n [0.5365, 0.5365, 0.5365],\n [0.5369, 0.5369, 0.5369],\n [0.5368, 0.5368, 0.5368],\n [0.5363, 0.5363, 0.5363],\n [0.5360, 0.5360, 0.5360],\n ...,\n [0.5621, 0.5621, 0.5621],\n [0.5625, 0.5625, 0.5625],\n [0.5628, 0.5628, 0.5628],\n [0.5628, 0.5628, 0.5628],\n [0.5639, 0.5639, 0.5639],\n [0.5640, 0.5640, 0.5640]],\n\n [[0.5345, 0.5345, 0.5345],\n [0.5358, 0.5358, 0.5358],\n [0.5354, 0.5354, 0.5354],\n [0.5354, 0.5354, 0.5354],\n [0.5354, 0.5354, 0.5354],\n [0.5347, 0.5347, 0.5347],\n ...,\n [0.5614, 0.5614, 0.5614],\n [0.5608, 0.5608, 0.5608],\n [0.5612, 0.5612, 0.5612],\n [0.5596, 0.5596, 0.5596],\n [0.5615, 0.5615, 0.5615],\n [0.5612, 0.5612, 0.5612]],\n\n [[0.5333, 0.5333, 0.5333],\n [0.5347, 0.5347, 0.5347],\n [0.5344, 0.5344, 0.5344],\n [0.5348, 0.5348, 0.5348],\n [0.5347, 0.5347, 0.5347],\n [0.5335, 0.5335, 0.5335],\n ...,\n [0.5602, 0.5602, 0.5602],\n [0.5598, 0.5598, 0.5598],\n [0.5607, 0.5607, 0.5607],\n [0.5583, 0.5583, 0.5583],\n [0.5604, 0.5604, 0.5604],\n [0.5585, 0.5585, 0.5585]],\n\n [[0.5335, 0.5335, 0.5335],\n [0.5316, 0.5316, 0.5316],\n [0.5332, 0.5332, 0.5332],\n [0.5330, 0.5330, 0.5330],\n [0.5345, 0.5345, 0.5345],\n [0.5335, 0.5335, 0.5335],\n ...,\n [0.5599, 0.5599, 0.5599],\n [0.5602, 0.5602, 0.5602],\n [0.5606, 0.5606, 0.5606],\n [0.5591, 0.5591, 0.5591],\n [0.5583, 0.5583, 0.5583],\n [0.5668, 0.5668, 0.5668]]]])', 'tensor([[[[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n ...,\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]]]])'], 'images': ['tensor([[[[0.6157, 0.8706, 1.0000],\n [0.6157, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5960, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000]],\n\n [[0.6156, 0.8706, 1.0000],\n [0.6156, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5960, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000]],\n\n [[0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5960, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000]],\n\n [[0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6115, 0.8707, 1.0000],\n [0.6115, 0.8707, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5960, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000]],\n\n [[0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6117, 0.8706, 1.0000],\n [0.6043, 0.8743, 1.0000],\n [0.6042, 0.8744, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5960, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000]],\n\n [[0.6119, 0.8706, 1.0000],\n [0.6119, 0.8706, 1.0000],\n [0.6119, 0.8706, 1.0000],\n [0.6119, 0.8706, 1.0000],\n [0.6044, 0.8743, 1.0000],\n [0.6043, 0.8743, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5962, 0.8669, 1.0000],\n [0.5963, 0.8668, 1.0000],\n [0.5963, 0.8668, 1.0000],\n [0.5963, 0.8668, 1.0000]],\n\n ...,\n\n [[0.3221, 0.4157, 0.4939],\n [0.3143, 0.4078, 0.4860],\n [0.3073, 0.3894, 0.4640],\n [0.3038, 0.3858, 0.4603],\n [0.3077, 0.3894, 0.4641],\n [0.3268, 0.4083, 0.4830],\n ...,\n [0.3298, 0.4474, 0.5415],\n [0.3519, 0.4696, 0.5637],\n [0.3087, 0.4263, 0.5204],\n [0.3040, 0.4217, 0.5158],\n [0.3109, 0.4286, 0.5227],\n [0.3292, 0.4468, 0.5410]],\n\n [[0.3253, 0.4194, 0.4979],\n [0.3178, 0.4119, 0.4903],\n [0.3212, 0.4037, 0.4782],\n [0.3213, 0.4037, 0.4782],\n [0.3251, 0.4074, 0.4819],\n [0.3299, 0.4121, 0.4866],\n ...,\n [0.3258, 0.4435, 0.5376],\n [0.3245, 0.4421, 0.5362],\n [0.3036, 0.4213, 0.5154],\n [0.2789, 0.3965, 0.4906],\n [0.2723, 0.3900, 0.4841],\n [0.2868, 0.4045, 0.4986]],\n\n [[0.3254, 0.4195, 0.4979],\n [0.3252, 0.4192, 0.4976],\n [0.3292, 0.4116, 0.4862],\n [0.3331, 0.4154, 0.4899],\n [0.3331, 0.4154, 0.4900],\n [0.3402, 0.4224, 0.4970],\n ...,\n [0.3396, 0.4572, 0.5513],\n [0.2806, 0.3983, 0.4924],\n [0.2508, 0.3685, 0.4626],\n [0.2639, 0.3815, 0.4757],\n [0.2753, 0.3930, 0.4871],\n [0.2619, 0.3795, 0.4736]],\n\n [[0.3217, 0.4159, 0.4943],\n [0.3217, 0.4158, 0.4942],\n [0.3294, 0.4119, 0.4864],\n [0.3369, 0.4193, 0.4938],\n [0.3295, 0.4119, 0.4864],\n [0.3255, 0.4077, 0.4822],\n ...,\n [0.3356, 0.4532, 0.5473],\n [0.2898, 0.4075, 0.5016],\n [0.2957, 0.4134, 0.5075],\n [0.2848, 0.4024, 0.4966],\n [0.3068, 0.4244, 0.5185],\n [0.3292, 0.4468, 0.5409]],\n\n [[0.3253, 0.4194, 0.4979],\n [0.3216, 0.4157, 0.4941],\n [0.3293, 0.4118, 0.4863],\n [0.3332, 0.4155, 0.4901],\n [0.3292, 0.4116, 0.4861],\n [0.3107, 0.3930, 0.4675],\n ...,\n [0.2715, 0.3891, 0.4832],\n [0.2478, 0.3655, 0.4596],\n [0.2519, 0.3696, 0.4637],\n [0.2293, 0.3470, 0.4411],\n [0.2068, 0.3244, 0.4185],\n [0.2181, 0.3358, 0.4299]],\n\n [[0.3177, 0.4118, 0.4902],\n [0.3216, 0.4156, 0.4940],\n [0.3255, 0.4079, 0.4825],\n [0.3256, 0.4080, 0.4825],\n [0.3331, 0.4155, 0.4900],\n [0.3295, 0.4117, 0.4862],\n ...,\n [0.2394, 0.3571, 0.4512],\n [0.2326, 0.3502, 0.4444],\n [0.3011, 0.4187, 0.5128],\n [0.3132, 0.4308, 0.5250],\n [0.3054, 0.4230, 0.5171],\n [0.2860, 0.4036, 0.4978]]]])', 'tensor([[[[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n [[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n [[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n [[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n [[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n [[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n ...,\n\n [[0.3561, 0.3953, 0.4659],\n [0.3455, 0.3847, 0.4553],\n [0.3416, 0.3808, 0.4514],\n [0.3418, 0.3810, 0.4516],\n [0.3451, 0.3843, 0.4549],\n [0.3455, 0.3847, 0.4553],\n ...,\n [0.2467, 0.3761, 0.4663],\n [0.2778, 0.4072, 0.4974],\n [0.2873, 0.4167, 0.5069],\n [0.3226, 0.4520, 0.5422],\n [0.3729, 0.5023, 0.5925],\n [0.4193, 0.5487, 0.6389]],\n\n [[0.3646, 0.4038, 0.4744],\n [0.3606, 0.3998, 0.4704],\n [0.3531, 0.3924, 0.4630],\n [0.3527, 0.3919, 0.4625],\n [0.3456, 0.3849, 0.4555],\n [0.3455, 0.3848, 0.4553],\n ...,\n [0.2781, 0.4075, 0.4977],\n [0.2974, 0.4268, 0.5170],\n [0.3052, 0.4346, 0.5248],\n [0.2921, 0.4215, 0.5117],\n [0.3112, 0.4406, 0.5308],\n [0.3202, 0.4496, 0.5398]],\n\n [[0.3685, 0.4077, 0.4783],\n [0.3722, 0.4114, 0.4820],\n [0.3681, 0.4073, 0.4779],\n [0.3607, 0.3999, 0.4705],\n [0.3567, 0.3959, 0.4665],\n [0.3566, 0.3958, 0.4664],\n ...,\n [0.2873, 0.4167, 0.5069],\n [0.3071, 0.4365, 0.5267],\n [0.3154, 0.4448, 0.5350],\n [0.3008, 0.4302, 0.5204],\n [0.2836, 0.4130, 0.5032],\n [0.2765, 0.4059, 0.4961]],\n\n [[0.3685, 0.4078, 0.4784],\n [0.3723, 0.4115, 0.4821],\n [0.3685, 0.4078, 0.4783],\n [0.3646, 0.4038, 0.4744],\n [0.3608, 0.4001, 0.4706],\n [0.3606, 0.3999, 0.4704],\n ...,\n [0.2235, 0.3529, 0.4431],\n [0.2386, 0.3680, 0.4582],\n [0.2645, 0.3939, 0.4841],\n [0.2758, 0.4052, 0.4954],\n [0.2945, 0.4239, 0.5141],\n [0.2983, 0.4277, 0.5179]],\n\n [[0.3646, 0.4039, 0.4745],\n [0.3609, 0.4001, 0.4707],\n [0.3646, 0.4038, 0.4744],\n [0.3646, 0.4038, 0.4744],\n [0.3645, 0.4038, 0.4744],\n [0.3609, 0.4001, 0.4707],\n ...,\n [0.3101, 0.4396, 0.5298],\n [0.3056, 0.4350, 0.5252],\n [0.2981, 0.4275, 0.5177],\n [0.3020, 0.4314, 0.5216],\n [0.3246, 0.4540, 0.5442],\n [0.3323, 0.4617, 0.5519]],\n\n [[0.3569, 0.3961, 0.4667],\n [0.3569, 0.3961, 0.4667],\n [0.3569, 0.3961, 0.4667],\n [0.3569, 0.3962, 0.4667],\n [0.3607, 0.4000, 0.4705],\n [0.3610, 0.4002, 0.4708],\n ...,\n [0.3834, 0.5128, 0.6030],\n [0.3604, 0.4898, 0.5800],\n [0.3257, 0.4551, 0.5453],\n [0.3175, 0.4469, 0.5371],\n [0.2944, 0.4238, 0.5140],\n [0.2904, 0.4198, 0.5100]]]])'], 'confidence': ['tensor([[[[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n ...,\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [1.3101e-09, 1.3101e-09, 1.3101e-09],\n [1.6468e-07, 1.6468e-07, 1.6468e-07],\n [1.5277e-06, 1.5277e-06, 1.5277e-06]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n ...,\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [2.3837e-09, 2.3837e-09, 2.3837e-09],\n [4.7627e-07, 4.7627e-07, 4.7627e-07]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n ...,\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [2.6038e-09, 2.6038e-09, 2.6038e-09],\n [5.2025e-07, 5.2025e-07, 5.2025e-07]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n ...,\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [7.8522e-10, 7.8522e-10, 7.8522e-10],\n [1.5689e-07, 1.5689e-07, 1.5689e-07]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n ...,\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [5.3943e-10, 5.3943e-10, 5.3943e-10],\n [1.0778e-07, 1.0778e-07, 1.0778e-07]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n ...,\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [7.9339e-10, 7.9339e-10, 7.9339e-10],\n [1.5852e-07, 1.5852e-07, 1.5852e-07]],\n\n ...,\n\n [[6.9341e-01, 6.9341e-01, 6.9341e-01],\n [7.1799e-01, 7.1799e-01, 7.1799e-01],\n [7.1019e-01, 7.1019e-01, 7.1019e-01],\n [7.0631e-01, 7.0631e-01, 7.0631e-01],\n [6.9907e-01, 6.9907e-01, 6.9907e-01],\n [6.7305e-01, 6.7305e-01, 6.7305e-01],\n ...,\n [7.2666e-01, 7.2666e-01, 7.2666e-01],\n [7.3909e-01, 7.3909e-01, 7.3909e-01],\n [7.3024e-01, 7.3024e-01, 7.3024e-01],\n [7.5258e-01, 7.5258e-01, 7.5258e-01],\n [7.7059e-01, 7.7059e-01, 7.7059e-01],\n [8.0613e-01, 8.0613e-01, 8.0613e-01]],\n\n [[7.4227e-01, 7.4227e-01, 7.4227e-01],\n [7.4080e-01, 7.4080e-01, 7.4080e-01],\n [7.2267e-01, 7.2267e-01, 7.2267e-01],\n [7.1428e-01, 7.1428e-01, 7.1428e-01],\n [7.0517e-01, 7.0517e-01, 7.0517e-01],\n [6.8194e-01, 6.8194e-01, 6.8194e-01],\n ...,\n [7.4598e-01, 7.4598e-01, 7.4598e-01],\n [7.5767e-01, 7.5767e-01, 7.5767e-01],\n [7.4881e-01, 7.4881e-01, 7.4881e-01],\n [7.6793e-01, 7.6793e-01, 7.6793e-01],\n [7.8683e-01, 7.8683e-01, 7.8683e-01],\n [7.9820e-01, 7.9820e-01, 7.9820e-01]],\n\n [[8.0560e-01, 8.0560e-01, 8.0560e-01],\n [7.6401e-01, 7.6401e-01, 7.6401e-01],\n [7.2580e-01, 7.2580e-01, 7.2580e-01],\n [7.1010e-01, 7.1010e-01, 7.1010e-01],\n [7.0087e-01, 7.0087e-01, 7.0087e-01],\n [6.7798e-01, 6.7798e-01, 6.7798e-01],\n ...,\n [7.3870e-01, 7.3870e-01, 7.3870e-01],\n [7.4850e-01, 7.4850e-01, 7.4850e-01],\n [7.3721e-01, 7.3721e-01, 7.3721e-01],\n [7.5312e-01, 7.5312e-01, 7.5312e-01],\n [7.9021e-01, 7.9021e-01, 7.9021e-01],\n [7.8266e-01, 7.8266e-01, 7.8266e-01]],\n\n [[8.1176e-01, 8.1176e-01, 8.1176e-01],\n [7.6108e-01, 7.6108e-01, 7.6108e-01],\n [7.1788e-01, 7.1788e-01, 7.1788e-01],\n [7.0467e-01, 7.0467e-01, 7.0467e-01],\n [7.0413e-01, 7.0413e-01, 7.0413e-01],\n [6.8829e-01, 6.8829e-01, 6.8829e-01],\n ...,\n [7.3936e-01, 7.3936e-01, 7.3936e-01],\n [7.5389e-01, 7.5389e-01, 7.5389e-01],\n [7.3625e-01, 7.3625e-01, 7.3625e-01],\n [7.5464e-01, 7.5464e-01, 7.5464e-01],\n [7.8965e-01, 7.8965e-01, 7.8965e-01],\n [7.9548e-01, 7.9548e-01, 7.9548e-01]],\n\n [[7.9422e-01, 7.9422e-01, 7.9422e-01],\n [7.7065e-01, 7.7065e-01, 7.7065e-01],\n [7.3907e-01, 7.3907e-01, 7.3907e-01],\n [7.2047e-01, 7.2047e-01, 7.2047e-01],\n [7.1502e-01, 7.1502e-01, 7.1502e-01],\n [6.9604e-01, 6.9604e-01, 6.9604e-01],\n ...,\n [7.4609e-01, 7.4609e-01, 7.4609e-01],\n [7.6319e-01, 7.6319e-01, 7.6319e-01],\n [7.5987e-01, 7.5987e-01, 7.5987e-01],\n [7.8462e-01, 7.8462e-01, 7.8462e-01],\n [8.3637e-01, 8.3637e-01, 8.3637e-01],\n [7.5797e-01, 7.5797e-01, 7.5797e-01]],\n\n [[9.9909e-01, 9.9909e-01, 9.9909e-01],\n [8.1340e-01, 8.1340e-01, 8.1340e-01],\n [8.4776e-01, 8.4776e-01, 8.4776e-01],\n [8.3745e-01, 8.3745e-01, 8.3745e-01],\n [7.7048e-01, 7.7048e-01, 7.7048e-01],\n [7.3428e-01, 7.3428e-01, 7.3428e-01],\n ...,\n [7.9207e-01, 7.9207e-01, 7.9207e-01],\n [7.7252e-01, 7.7252e-01, 7.7252e-01],\n [7.2407e-01, 7.2407e-01, 7.2407e-01],\n [7.6479e-01, 7.6479e-01, 7.6479e-01],\n [8.8026e-01, 8.8026e-01, 8.8026e-01],\n [7.8775e-01, 7.8775e-01, 7.8775e-01]]]])', 'tensor([[[[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n ...,\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]],\n\n [[1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n ...,\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.],\n [1., 1., 1.]]]])'], 'sky_mask': ['tensor([[[0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n ...,\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.]]])', 'tensor([[[0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n ...,\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0.]]])']}, 'current_outputs': ['38', '48', '27', '21', '45', '39', '44', '3'], 'timestamp': 1778347143975}
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[03:06] [4/7] SKIPPED (not in cpu list) bas_relief.json
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[03:07] [5/7] SKIPPED (not in cpu list) da3_streaming.json
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[03:07] Capturing execution frames: simple.json
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[03:17] Frame 1 saved (frame_000.jpg, t=0.0s)
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[03:17] Validating workflow...
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[03:17] Queuing workflow for execution...
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[03:20] Frame 2 saved (frame_001.jpg, t=2.5s)
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[03:20] [capture-periodic] freeze=5ms shot=641ms unfreeze=17ms saved=True
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[03:23] Frame 3 saved (frame_002.jpg, t=5.3s)
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[03:23] [capture-periodic] freeze=8ms shot=812ms unfreeze=55ms saved=True
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[03:25] [capture-loop] iter=50 t=8.2s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=4 ram=2.1/7.0GB (32%) swap=0.7/2.0GB (36%) cpu=65% browser_rss=0.46GB
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[03:28] Frame 4 saved (frame_003.jpg, t=10.6s)
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[03:28] [capture-periodic] freeze=3ms shot=235ms unfreeze=19ms saved=True
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[03:30] Frame 5 saved (frame_004.jpg, t=13.0s)
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[03:30] [capture-periodic] freeze=5ms shot=218ms unfreeze=24ms saved=True
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[03:31] [capture-loop] iter=100 t=14.6s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=4 ram=3.4/7.0GB (50%) swap=0.7/2.0GB (35%) cpu=28% browser_rss=0.47GB
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[03:39] [capture-loop] iter=150 t=22.3s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=8 ram=4.8/7.0GB (75%) swap=0.7/2.0GB (34%) cpu=76% browser_rss=0.40GB
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[03:49] [capture-loop] iter=200 t=32.4s state={'complete': False, 'error': None, 'executedCount': 0, 'wsState': 1} eval_ms=14 ram=5.0/7.0GB (81%) swap=0.7/2.0GB (34%) cpu=87% browser_rss=0.31GB
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[03:57] Frame 6 saved (frame_005.jpg, t=33.2s)
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[03:57] [capture-periodic] freeze=8ms shot=7330ms unfreeze=93ms saved=True
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[04:00] Frame 7 saved (frame_006.jpg, t=42.8s)
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[04:00] [capture-periodic] freeze=7ms shot=387ms unfreeze=34ms saved=True
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[04:03] Node executed (1 total), capturing...
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[04:04] Frame 8 saved (frame_007.jpg, t=46.6s)
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[04:04] [capture-node] freeze=13ms shot=419ms unfreeze=0ms saved=True
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[04:04] Execution complete (t=46.6s)
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[04:04] Captured 8 unique frames over 47.09s
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[04:04] [debug] iframes: 0
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[04:04] [timing] trigger_3d_previews: 0.0s
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[04:06] Saved high-quality screenshot: simple_executed.png
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[04:06] [timing] final_screenshot: 0.6s
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[04:07] [7/7] SKIPPED (not in cpu list) video_multiview_depth.json
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[04:08] Results saved to /Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/comfy-test-logs/DepthAnythingV3-1716/macos-cpu/results.json
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[04:08] Model report: 4 files, 1.5 GB -> /Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/comfy-test-logs/DepthAnythingV3-1716/macos-cpu/models.json
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[04:08] Saved: /Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/comfy-test-logs/DepthAnythingV3-1716/macos-cpu/index.html
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[04:08]
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macos: FAILED
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[04:08] Error: Workflow execution failed (1 error(s))
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[04:08] Details: advanced_3d_multiview.json: Workflow execution failed: {'prompt_id': '3bed6e0d-25f9-4926-af93-460fe72bc08b', 'node_id': '38', 'node_type': 'DA3_MultiViewPointCloud', 'executed': ['27', '39', '21', '3'], 'exception_message': 'Depth input appears to be normalized (max=1.0302) instead of raw/metric depth. Multi-view point cloud fusion requires raw metric depth values. Please use DepthAnythingV3_MultiView node with normalization_mode=\'Raw\' and connect the depth output to this node\'s depths input. If you think this is a mistake, feel free to toggle allow_around_1.\n\nWorker traceback:\nTraceback (most recent call last):\n File "/var/folders/tb/y368xp_x10s3ty1b_mtl5mxr0000gn/T/comfyui_pvenv__zn50zv9/persistent_worker.py", line 1762, in main\n result = method(**inputs)\n ^^^^^^^^^^^^^^^^\n File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/comfy_api/latest/_io.py", line 1833, in EXECUTE_NORMALIZED\n to_return = cls.execute(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/custom_nodes/ComfyUI-DepthAnythingV3/nodes/nodes_multiview.py", line 690, in execute\n raise ValueError(\nValueError: Depth input appears to be normalized (max=1.0302) instead of raw/metric depth. Multi-view point cloud fusion requires raw metric depth values. Please use DepthAnythingV3_MultiView node with normalization_mode=\'Raw\' and connect the depth output to this node\'s depths input. If you think this is a mistake, feel free to toggle allow_around_1.\n\n', 'exception_type': 'comfy_env.isolation.workers.base.WorkerError', 'traceback': [' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/execution.py", line 535, in execute\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n', ' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/execution.py", line 335, in get_output_data\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n', ' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/execution.py", line 309, in _async_map_node_over_list\n await process_inputs(input_dict, i)\n', ' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/execution.py", line 297, in process_inputs\n result = f(**inputs)\n ^^^^^^^^^^^\n', ' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/.venv/lib/python3.11/site-packages/comfy_env/isolation/metadata.py", line 536, in proxy\n result = worker.call_method(\n ^^^^^^^^^^^^^^^^^^^\n', ' File "/Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/.venv/lib/python3.11/site-packages/comfy_env/isolation/workers/subprocess.py", line 674, in call_method\n raise WorkerError(\n'], 'current_inputs': {'extrinsics': ['{\n "extrinsics": [\n {\n "image_0": [\n [\n 0.9999998211860657,\n -0.0005656706052832305,\n -0.00022657914087176323,\n 0.00018741225358098745\n ],\n [\n 0.000565818976610899,\n 0.9999996423721313,\n 0.0006551882834173739,\n -0.0001278371928492561\n ],\n [\n 0.0002262084453832358,\n -0.0006553163402713835,\n 0.9999997615814209,\n 0.00023603401496075094\n ]\n ]\n }\n ]\n}', '{\n "extrinsics": [\n {\n "image_0": [\n [\n 0.9999998211860657,\n 0.00017460108210798353,\n 0.0005202052416279912,\n 0.0003719621745403856\n ],\n [\n -0.0001742378663038835,\n 0.9999997615814209,\n -0.0006981720798648894,\n 2.779594979074318e-05\n ],\n [\n -0.0005203270702622831,\n 0.0006980813923291862,\n 0.9999996423721313,\n -0.00018597673624753952\n ]\n ]\n }\n ]\n}'], 'intrinsics': ['{\n "intrinsics": [\n {\n "image_0": [\n [\n 1086.2222900390625,\n 0.0,\n 604.0\n ],\n [\n 0.0,\n 1073.156494140625,\n 340.0\n ],\n [\n 0.0,\n 0.0,\n 1.0\n ]\n ]\n }\n ]\n}', '{\n "intrinsics": [\n {\n "image_0": [\n [\n 1206.2451171875,\n 0.0,\n 604.0\n ],\n [\n 0.0,\n 1191.7357177734375,\n 340.0\n ],\n [\n 0.0,\n 0.0,\n 1.0\n ]\n ]\n }\n ]\n}'], 'confidence_threshold': [0.3], 'downsample': [4], 'use_icp': [False], 'allow_around_1': [False], 'filter_outliers': [True], 'outlier_percentage': [5], 'depths': ['tensor([[[[2.2783, 2.2783, 2.2783],\n [2.3971, 2.3971, 2.3971],\n [2.4024, 2.4024, 2.4024],\n [2.4413, 2.4413, 2.4413],\n [2.4575, 2.4575, 2.4575],\n [2.5005, 2.5005, 2.5005],\n ...,\n [0.5850, 0.5850, 0.5850],\n [0.6002, 0.6002, 0.6002],\n [0.6126, 0.6126, 0.6126],\n [0.6116, 0.6116, 0.6116],\n [0.5946, 0.5946, 0.5946],\n [0.6213, 0.6213, 0.6213]],\n\n [[2.4074, 2.4074, 2.4074],\n [2.3734, 2.3734, 2.3734],\n [2.3657, 2.3657, 2.3657],\n [2.3895, 2.3895, 2.3895],\n [2.4327, 2.4327, 2.4327],\n [2.4825, 2.4825, 2.4825],\n ...,\n [0.5775, 0.5775, 0.5775],\n [0.5878, 0.5878, 0.5878],\n [0.6050, 0.6050, 0.6050],\n [0.6096, 0.6096, 0.6096],\n [0.6084, 0.6084, 0.6084],\n [0.5969, 0.5969, 0.5969]],\n\n [[2.3300, 2.3300, 2.3300],\n [2.3779, 2.3779, 2.3779],\n [2.3220, 2.3220, 2.3220],\n [2.3551, 2.3551, 2.3551],\n [2.3910, 2.3910, 2.3910],\n [2.4299, 2.4299, 2.4299],\n ...,\n [0.5814, 0.5814, 0.5814],\n [0.5922, 0.5922, 0.5922],\n [0.6092, 0.6092, 0.6092],\n [0.6136, 0.6136, 0.6136],\n [0.6157, 0.6157, 0.6157],\n [0.6142, 0.6142, 0.6142]],\n\n [[2.2869, 2.2869, 2.2869],\n [2.3868, 2.3868, 2.3868],\n [2.3343, 2.3343, 2.3343],\n [2.3674, 2.3674, 2.3674],\n [2.4019, 2.4019, 2.4019],\n [2.4264, 2.4264, 2.4264],\n ...,\n [0.5805, 0.5805, 0.5805],\n [0.5912, 0.5912, 0.5912],\n [0.6062, 0.6062, 0.6062],\n [0.6109, 0.6109, 0.6109],\n [0.6102, 0.6102, 0.6102],\n [0.6125, 0.6125, 0.6125]],\n\n [[2.2942, 2.2942, 2.2942],\n [2.4084, 2.4084, 2.4084],\n [2.3634, 2.3634, 2.3634],\n [2.3800, 2.3800, 2.3800],\n [2.4075, 2.4075, 2.4075],\n [2.4276, 2.4276, 2.4276],\n ...,\n [0.5763, 0.5763, 0.5763],\n [0.5869, 0.5869, 0.5869],\n [0.6009, 0.6009, 0.6009],\n [0.6054, 0.6054, 0.6054],\n [0.6034, 0.6034, 0.6034],\n [0.6058, 0.6058, 0.6058]],\n\n [[2.3065, 2.3065, 2.3065],\n [2.4346, 2.4346, 2.4346],\n [2.3916, 2.3916, 2.3916],\n [2.4178, 2.4178, 2.4178],\n [2.4234, 2.4234, 2.4234],\n [2.4390, 2.4390, 2.4390],\n ...,\n [0.5719, 0.5719, 0.5719],\n [0.5821, 0.5821, 0.5821],\n [0.5960, 0.5960, 0.5960],\n [0.6006, 0.6006, 0.6006],\n [0.5946, 0.5946, 0.5946],\n [0.6008, 0.6008, 0.6008]],\n\n ...,\n\n [[0.5395, 0.5395, 0.5395],\n [0.5402, 0.5402, 0.5402],\n [0.5399, 0.5399, 0.5399],\n [0.5397, 0.5397, 0.5397],\n [0.5394, 0.5394, 0.5394],\n [0.5392, 0.5392, 0.5392],\n ...,\n [0.5638, 0.5638, 0.5638],\n [0.5638, 0.5638, 0.5638],\n [0.5647, 0.5647, 0.5647],\n [0.5654, 0.5654, 0.5654],\n [0.5665, 0.5665, 0.5665],\n [0.5654, 0.5654, 0.5654]],\n\n [[0.5388, 0.5388, 0.5388],\n [0.5388, 0.5388, 0.5388],\n [0.5383, 0.5383, 0.5383],\n [0.5376, 0.5376, 0.5376],\n [0.5375, 0.5375, 0.5375],\n [0.5371, 0.5371, 0.5371],\n ...,\n [0.5628, 0.5628, 0.5628],\n [0.5629, 0.5629, 0.5629],\n [0.5637, 0.5637, 0.5637],\n [0.5642, 0.5642, 0.5642],\n [0.5656, 0.5656, 0.5656],\n [0.5643, 0.5643, 0.5643]],\n\n [[0.5371, 0.5371, 0.5371],\n [0.5365, 0.5365, 0.5365],\n [0.5369, 0.5369, 0.5369],\n [0.5368, 0.5368, 0.5368],\n [0.5363, 0.5363, 0.5363],\n [0.5360, 0.5360, 0.5360],\n ...,\n [0.5621, 0.5621, 0.5621],\n [0.5625, 0.5625, 0.5625],\n [0.5628, 0.5628, 0.5628],\n [0.5628, 0.5628, 0.5628],\n [0.5639, 0.5639, 0.5639],\n [0.5640, 0.5640, 0.5640]],\n\n [[0.5345, 0.5345, 0.5345],\n [0.5358, 0.5358, 0.5358],\n [0.5354, 0.5354, 0.5354],\n [0.5354, 0.5354, 0.5354],\n [0.5354, 0.5354, 0.5354],\n [0.5347, 0.5347, 0.5347],\n ...,\n [0.5614, 0.5614, 0.5614],\n [0.5608, 0.5608, 0.5608],\n [0.5612, 0.5612, 0.5612],\n [0.5596, 0.5596, 0.5596],\n [0.5615, 0.5615, 0.5615],\n [0.5612, 0.5612, 0.5612]],\n\n [[0.5333, 0.5333, 0.5333],\n [0.5347, 0.5347, 0.5347],\n [0.5344, 0.5344, 0.5344],\n [0.5348, 0.5348, 0.5348],\n [0.5347, 0.5347, 0.5347],\n [0.5335, 0.5335, 0.5335],\n ...,\n [0.5602, 0.5602, 0.5602],\n [0.5598, 0.5598, 0.5598],\n [0.5607, 0.5607, 0.5607],\n [0.5583, 0.5583, 0.5583],\n [0.5604, 0.5604, 0.5604],\n [0.5585, 0.5585, 0.5585]],\n\n [[0.5335, 0.5335, 0.5335],\n [0.5316, 0.5316, 0.5316],\n [0.5332, 0.5332, 0.5332],\n [0.5330, 0.5330, 0.5330],\n [0.5345, 0.5345, 0.5345],\n [0.5335, 0.5335, 0.5335],\n ...,\n [0.5599, 0.5599, 0.5599],\n [0.5602, 0.5602, 0.5602],\n [0.5606, 0.5606, 0.5606],\n [0.5591, 0.5591, 0.5591],\n [0.5583, 0.5583, 0.5583],\n [0.5668, 0.5668, 0.5668]]]])', 'tensor([[[[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n ...,\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]],\n\n [[1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n ...,\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302],\n [1.0302, 1.0302, 1.0302]]]])'], 'images': ['tensor([[[[0.6157, 0.8706, 1.0000],\n [0.6157, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5960, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000]],\n\n [[0.6156, 0.8706, 1.0000],\n [0.6156, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5960, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000]],\n\n [[0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5960, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000]],\n\n [[0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6115, 0.8707, 1.0000],\n [0.6115, 0.8707, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5960, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000]],\n\n [[0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6118, 0.8706, 1.0000],\n [0.6117, 0.8706, 1.0000],\n [0.6043, 0.8743, 1.0000],\n [0.6042, 0.8744, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5960, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000],\n [0.5961, 0.8667, 1.0000]],\n\n [[0.6119, 0.8706, 1.0000],\n [0.6119, 0.8706, 1.0000],\n [0.6119, 0.8706, 1.0000],\n [0.6119, 0.8706, 1.0000],\n [0.6044, 0.8743, 1.0000],\n [0.6043, 0.8743, 1.0000],\n ...,\n [0.5922, 0.8706, 1.0000],\n [0.5922, 0.8705, 1.0000],\n [0.5962, 0.8669, 1.0000],\n [0.5963, 0.8668, 1.0000],\n [0.5963, 0.8668, 1.0000],\n [0.5963, 0.8668, 1.0000]],\n\n ...,\n\n [[0.3221, 0.4157, 0.4939],\n [0.3143, 0.4078, 0.4860],\n [0.3073, 0.3894, 0.4640],\n [0.3038, 0.3858, 0.4603],\n [0.3077, 0.3894, 0.4641],\n [0.3268, 0.4083, 0.4830],\n ...,\n [0.3298, 0.4474, 0.5415],\n [0.3519, 0.4696, 0.5637],\n [0.3087, 0.4263, 0.5204],\n [0.3040, 0.4217, 0.5158],\n [0.3109, 0.4286, 0.5227],\n [0.3292, 0.4468, 0.5410]],\n\n [[0.3253, 0.4194, 0.4979],\n [0.3178, 0.4119, 0.4903],\n [0.3212, 0.4037, 0.4782],\n [0.3213, 0.4037, 0.4782],\n [0.3251, 0.4074, 0.4819],\n [0.3299, 0.4121, 0.4866],\n ...,\n [0.3258, 0.4435, 0.5376],\n [0.3245, 0.4421, 0.5362],\n [0.3036, 0.4213, 0.5154],\n [0.2789, 0.3965, 0.4906],\n [0.2723, 0.3900, 0.4841],\n [0.2868, 0.4045, 0.4986]],\n\n [[0.3254, 0.4195, 0.4979],\n [0.3252, 0.4192, 0.4976],\n [0.3292, 0.4116, 0.4862],\n [0.3331, 0.4154, 0.4899],\n [0.3331, 0.4154, 0.4900],\n [0.3402, 0.4224, 0.4970],\n ...,\n [0.3396, 0.4572, 0.5513],\n [0.2806, 0.3983, 0.4924],\n [0.2508, 0.3685, 0.4626],\n [0.2639, 0.3815, 0.4757],\n [0.2753, 0.3930, 0.4871],\n [0.2619, 0.3795, 0.4736]],\n\n [[0.3217, 0.4159, 0.4943],\n [0.3217, 0.4158, 0.4942],\n [0.3294, 0.4119, 0.4864],\n [0.3369, 0.4193, 0.4938],\n [0.3295, 0.4119, 0.4864],\n [0.3255, 0.4077, 0.4822],\n ...,\n [0.3356, 0.4532, 0.5473],\n [0.2898, 0.4075, 0.5016],\n [0.2957, 0.4134, 0.5075],\n [0.2848, 0.4024, 0.4966],\n [0.3068, 0.4244, 0.5185],\n [0.3292, 0.4468, 0.5409]],\n\n [[0.3253, 0.4194, 0.4979],\n [0.3216, 0.4157, 0.4941],\n [0.3293, 0.4118, 0.4863],\n [0.3332, 0.4155, 0.4901],\n [0.3292, 0.4116, 0.4861],\n [0.3107, 0.3930, 0.4675],\n ...,\n [0.2715, 0.3891, 0.4832],\n [0.2478, 0.3655, 0.4596],\n [0.2519, 0.3696, 0.4637],\n [0.2293, 0.3470, 0.4411],\n [0.2068, 0.3244, 0.4185],\n [0.2181, 0.3358, 0.4299]],\n\n [[0.3177, 0.4118, 0.4902],\n [0.3216, 0.4156, 0.4940],\n [0.3255, 0.4079, 0.4825],\n [0.3256, 0.4080, 0.4825],\n [0.3331, 0.4155, 0.4900],\n [0.3295, 0.4117, 0.4862],\n ...,\n [0.2394, 0.3571, 0.4512],\n [0.2326, 0.3502, 0.4444],\n [0.3011, 0.4187, 0.5128],\n [0.3132, 0.4308, 0.5250],\n [0.3054, 0.4230, 0.5171],\n [0.2860, 0.4036, 0.4978]]]])', 'tensor([[[[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n [[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n [[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n [[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n [[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n [[0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6196, 0.8784, 1.0000],\n [0.6195, 0.8784, 1.0000],\n ...,\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000],\n [0.6000, 0.8784, 1.0000]],\n\n ...,\n\n [[0.3561, 0.3953, 0.4659],\n [0.3455, 0.3847, 0.4553],\n [0.3416, 0.3808, 0.4514],\n [0.3418, 0.3810, 0.4516],\n [0.3451, 0.3843, 0.4549],\n [0.3455, 0.3847, 0.4553],\n ...,\n [0.2467, 0.3761, 0.4663],\n [0.2778, 0.4072, 0.4974],\n [0.2873, 0.4167, 0.5069],\n [0.3226, 0.4520, 0.5422],\n [0.3729, 0.5023, 0.5925],\n [0.4193, 0.5487, 0.6389]],\n\n [[0.3646, 0.4038, 0.4744],\n [0.3606, 0.3998, 0.4704],\n [0.3531, 0.3924, 0.4630],\n [0.3527, 0.3919, 0.4625],\n [0.3456, 0.3849, 0.4555],\n [0.3455, 0.3848, 0.4553],\n ...,\n [0.2781, 0.4075, 0.4977],\n [0.2974, 0.4268, 0.5170],\n [0.3052, 0.4346, 0.5248],\n [0.2921, 0.4215, 0.5117],\n [0.3112, 0.4406, 0.5308],\n [0.3202, 0.4496, 0.5398]],\n\n [[0.3685, 0.4077, 0.4783],\n [0.3722, 0.4114, 0.4820],\n [0.3681, 0.4073, 0.4779],\n [0.3607, 0.3999, 0.4705],\n [0.3567, 0.3959, 0.4665],\n [0.3566, 0.3958, 0.4664],\n ...,\n [0.2873, 0.4167, 0.5069],\n [0.3071, 0.4365, 0.5267],\n [0.3154, 0.4448, 0.5350],\n [0.3008, 0.4302, 0.5204],\n [0.2836, 0.4130, 0.5032],\n [0.2765, 0.4059, 0.4961]],\n\n [[0.3685, 0.4078, 0.4784],\n [0.3723, 0.4115, 0.4821],\n [0.3685, 0.4078, 0.4783],\n [0.3646, 0.4038, 0.4744],\n [0.3608, 0.4001, 0.4706],\n [0.3606, 0.3999, 0.4704],\n ...,\n [0.2235, 0.3529, 0.4431],\n [0.2386, 0.3680, 0.4582],\n [0.2645, 0.3939, 0.4841],\n [0.2758, 0.4052, 0.4954],\n [0.2945, 0.4239, 0.5141],\n [0.2983, 0.4277, 0.5179]],\n\n [[0.3646, 0.4039, 0.4745],\n [0.3609, 0.4001, 0.4707],\n [0.3646, 0.4038, 0.4744],\n [0.3646, 0.4038, 0.4744],\n [0.3645, 0.4038, 0.4744],\n [0.3609, 0.4001, 0.4707],\n ...,\n [0.3101, 0.4396, 0.5298],\n [0.3056, 0.4350, 0.5252],\n [0.2981, 0.4275, 0.5177],\n [0.3020, 0.4314, 0.5216],\n [0.3246, 0.4540, 0.5442],\n [0.3323, 0.4617, 0.5519]],\n\n [[0.3569, 0.3961, 0.4667],\n [0.3569, 0.3961, 0.4667],\n [0.3569, 0.3961, 0.4667],\n [0.3569, 0.3962, 0.4667],\n [0.3607, 0.4000, 0.4705],\n [0.3610, 0.4002, 0.4708],\n ...,\n [0.3834, 0.5128, 0.6030],\n [0.3604, 0.4898, 0.5800],\n [0.3257, 0.4551, 0.5453],\n [0.3175, 0.4469, 0.5371],\n [0.2944, 0.4238, 0.5140],\n [0.2904, 0.4198, 0.5100]]]])'], 'confidence': ['tensor([[[[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n ...,\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [1.3101e-09, 1.3101e-09, 1.3101e-09],\n [1.6468e-07, 1.6468e-07, 1.6468e-07],\n [1.5277e-06, 1.5277e-06, 1.5277e-06]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n ...,\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [2.3837e-09, 2.3837e-09, 2.3837e-09],\n 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Details:
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Workflow: /Users/runner/work/comfy-gpu-ci/comfy-gpu-ci/ComfyUI/custom_nodes/ComfyUI-DepthAnythingV3/workflows/advanced_3d_multiview.json
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Node error: DA3_MultiViewPointCloud
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