Update sam2point/configs.py
Browse files- sam2point/configs.py +71 -34
sam2point/configs.py
CHANGED
@@ -10,60 +10,74 @@ sample_2 = {'path': 'data/S3DIS/Area_1_conferenceRoom_1.txt',
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sample_3 = {'path': 'data/S3DIS/Area_2_WC_1.txt',
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'point_prompts': [[0.31414868, 0.59265659, 0.50951199], [0.6628697, 0.90842333, 0.34036394],[0.63868905, 0.36414687, 0.94954508],
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[0.11171063, 0.85788337, 0.18072787],
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[0.88589129, 0.59049676, 0.44830438],],
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'box_prompts': [[0.35, 0.8, 0.05, 0.45, 1.0, 0.4], [0.48, 0.65, 0.0, 0.55, 0.99, 0.99], [0.57, 0.2, 0.85, 0.7, 0.48, 1.0],
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[0.61, 0., 0.33, 0.71, 0.13, 0.51],],
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'mask_prompts': [[0.31414868, 0.59265659, 0.50951199], [0.6628697, 0.90842333, 0.34036394],[0.63868905, 0.36414687, 0.94954508],
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[0.11171063, 0.85788337, 0.18072787],
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[0.88589129, 0.59049676, 0.44830438],],
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}
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sample_4 = {'path': 'data/S3DIS/Area_4_lobby_2.txt',
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'point_prompts': [[0.19949431, 0.28597082, 0.25131625],
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[0.72566372, 0.3617284, 0.65601966], [0.50316056, 0.57519641, 0.32186732],
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[0.46396966, 0.52345679, 0.54756055],],
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'box_prompts': [[0.42, 0.45, 0.3, 0.49, 0.54, 0.65], [0.45, 0.57, 0.27, 0.55, 0.63, 0.36], [0.17, 0.35, 0., 0.25, 0.4, 0.3],
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[0.15, 0.25, 0.4, 0.19, 0.33, 0.62], [0.17, 0.78, 0.27, 0.2, 0.84, 0.43]],
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'mask_prompts': [[0.
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[0.46396966, 0.52345679, 0.54756055],],
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}
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sample_1 = {'path': 'data/S3DIS/Area_5_office_3.txt',
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'point_prompts': [
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[0.90161319, 0.51668286, 0.21546617], [0.98404538, 0.29024943, 0.51013408],
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[0.76369438, 0.32458698, 0.23542251]],
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'box_prompts': [[0., 0.48, 0.23, 0.12, 0.61, 0.31], [0.4, 0.25, 0., 0.6, 0.6, 0.3], [0.45, 0.85, 0.45, 0.65, 0.99, 0.55],
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[0.38, 0.95, 0.25, 0.48, 1.00, 0.42], [0.65, 0.45, 0., 0.75, 0.6, 0.3]],
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'mask_prompts': [[0.45080659, 0.88824101, 0.22856252],
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[0.90161319, 0.51668286, 0.21546617], [0.98404538, 0.29024943, 0.51013408],
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[0.76369438, 0.32458698, 0.23542251]],
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}
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sample_0 = {'path': 'data/S3DIS/Area_6_office_9.txt',
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'point_prompts': [[0.16548, 0.27853667, 0.1886402], [0.46150787, 0.09795895, 0.26989673], [0.2904479, 0.5073498, 0.28115318],
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[0.9304859, 0.40291342, 0.32013769], [0.802557, 0.5818576, 0.19074],
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[0.52659518, 0.5240772, 0.40165232], [0.29337714, 0.8905976, 0.2722375], [0.563984, 0.925, 0.3803788],],
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'box_prompts': [[0.1, 0.2, 0.0, 0.2, 0.3, 0.4], [0.1, 0.02, 0.2, 0.9, 0.2, 0.3], [0.7, 0.5, 0., 0.9, 0.7, 0.4],
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[0.85, 0.3, 0.02, 0.98, 0.5, 0.8], [0.4, 0.4, 0.3, 0.6, 0.6, 0.5], ],
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'mask_prompts': [[0.16548, 0.27853667, 0.1886402], [0.46150787, 0.09795895, 0.26989673], [0.2904479, 0.5073498, 0.28115318],
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[0.9304859, 0.40291342, 0.32013769], [0.802557, 0.5818576, 0.19074],
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[0.52659518, 0.5240772, 0.40165232], [0.29337714, 0.8905976, 0.2722375], [0.563984, 0.925, 0.3803788],]
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}
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S3DIS_samples = [sample_2, sample_3, sample_4, sample_1, sample_0]
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[0.48, 0.95, 0.58, 0.8, 0.99, 0.9]],
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'mask_prompts': [[0.50845712, 0.4027696, 0.19570725], [0.26778319, 0.9830749, 0.44313431]],
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}
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sample_2 = {'path': 'data/ScanNet/scene0010_01.pth',
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'point_prompts': [[0.86644632, 0.26297486, 0.5173167]],
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'box_prompts': [[0.6, 0.72, 0.0, 0.75, 0.85, 0.6], [0.75, 0.70, 0.5, 0.92, 0.92, 0.75], [0.05, 0.92, 0.05, 0.27, 1.0, 0.82],
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[0.35, 0.03, 0.15, 0.5, 0.1, 0.42], ],
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'mask_prompts': [[0.86644632, 0.26297486, 0.5173167]],
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@@ -72,14 +86,18 @@ sample_2 = {'path': 'data/ScanNet/scene0010_01.pth',
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sample_3 = {'path': 'data/ScanNet/scene0016_02.pth',
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'point_prompts': [[0.2898192, 0.5845358, 0.7862434], [0.8251329,0.1763976,0.2942619]],
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'mask_prompts': [[0.2898192, 0.5845358, 0.7862434]],
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}
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sample_4 = {'path': 'data/ScanNet/scene0019_01.pth',
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'point_prompts': [[0.52182293, 0.69650459, 0.36580974], [0.6603151, 0.26341686, 0.33537653],[0.03188787, 0.65648252, 0.43863711]],
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'mask_prompts': [[0.52182293, 0.69650459, 0.36580974], [0.6603151, 0.26341686, 0.33537653], [0.17163187, 0.30585486, 0.31457961], [0.03188787, 0.65648252, 0.43863711]],
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}
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@@ -94,33 +112,34 @@ sample_6 = {'path': 'data/ScanNet/scene0002_00.pth',
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'mask_prompts': [[0.56711978, 0.74271345, 0.1753805 ], [0.61877084, 0.47617316, 0.23380645]],
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}
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ScanNet_samples = [sample_1, sample_2, sample_3, sample_4, sample_5, sample_6]
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sample_0 = {'path': 'data/Objaverse/plant.npy',
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'point_prompts': [[0.50455284, 0.47794762, 0.0007253083], [0.28331658, 0.19435011, 0.77393067]],
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'voxel_size': [0.038, 0.04],
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'
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'
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'voxel_size_mask': [0.038]
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}
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sample_1 = {'path': 'data/Objaverse/human.npy',
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'point_prompts': [[0.57825595, 0.5005686, 0.11494722], [0.7136412, 0.49501216, 0.5020814 ], [0.7136412, 0.49501216, 0.5020814 ]],
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'voxel_size': [0.055, 0.045, 0.05],
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'box_prompts': [[0., 0.17, -0.01, 0.72, 0.80, 0.3], [-0.01, 0., 0.28, 0.8, 1, 0.82], [-0.01, 0.28, 0.89, 1, 0.72, 1.02]],
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'voxel_size_box': [0.055, 0.045, 0.055],
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'mask_prompts': [[0.57825595, 0.5005686, 0.11494722], [0.7136412, 0.49501216, 0.5020814 ]],
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'voxel_size_mask': [0.055, 0.055],
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}
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sample_2 = {'path': 'data/Objaverse/lock.npy',
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'point_prompts': [[0.6513301, 0.6753892, 0.52316076], [0.21359734, 0.6097132 , 0.7939796 ], [0.44947368, 0.21654338, 0.58450174]],
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'voxel_size': [0.04, 0.05, 0.05],
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'box_prompts': [[0.61, 0.4, 0.35, 0.8, 0.8, 0.6], [0.42, -0.02, -0.02, 1.02, 0.4, 1]],
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'voxel_size_box': [0.04, 0.011],
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'mask_prompts': [[0.6513301, 0.6753892, 0.52316076], [0.21359734, 0.6097132 , 0.7939796 ], [0.9157764, 0.1995991, 0.14024617]],
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'voxel_size_mask': [0.04, 0.055, 0.04],
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}
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@@ -152,11 +171,11 @@ sample_5 = {'path': 'data/Objaverse/skateboard.npy',
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}
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sample_6 = {'path': 'data/Objaverse/popcorn_machine.npy',
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'point_prompts': [[0.278306, 0.4913014, 0.7318756], [0.5867118, 0.1180351, 0.5844101]],
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'voxel_size': [0.04, 0.04],
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'box_prompts': [[0.208, 0.157, 0.493, 0.779, 0.89, 0.925]],
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'voxel_size_box': [0.04],
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'mask_prompts': [[0.278306, 0.4913014, 0.7318756], [0.5867118, 0.1180351, 0.5844101]],
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'voxel_size_mask': [0.04, 0.04],
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}
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@@ -182,7 +201,7 @@ sample_8 = {'path': 'data/Objaverse/bus_shelter.npy',
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sample_9 = {'path': 'data/Objaverse/thor_hammer.npy',
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'point_prompts': [[0.6211515, 0.5109989, 0.3867725], [0.44443, 0.2363458, 0.7229376]],
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'voxel_size': [0.05, 0.05, 0.05],
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'box_prompts': [[0,0,0.723,1,1,1]],
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'voxel_size_box': [0.05, 0.05],
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'mask_prompts': [[0.44443, 0.2363458, 0.7229376]],
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'voxel_size_mask': [0.05],
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@@ -191,7 +210,7 @@ sample_9 = {'path': 'data/Objaverse/thor_hammer.npy',
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sample_10 = {'path': 'data/Objaverse/horse.npy',
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'point_prompts': [[0.3359364, 0.7555879, 0.6848574], [0.9221735, 0.1779197, 0.1927067]],
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'voxel_size': [0.04, 0.04],
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'box_prompts': [[0.65,0,0.3,1,1,0.79], [0.37, 0, 0, 1, 1, 0.2]],
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'voxel_size_box': [0.04, 0.04],
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'mask_prompts': [[0.3359364, 0.7555879, 0.6848574], [0.9221735, 0.1779197, 0.1927067]],
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'voxel_size_mask': [0.04, 0.04],
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@@ -202,13 +221,28 @@ sample_11 = {'path': 'data/Objaverse/dinner_booth.npy',
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[0.9192697, 0.4469184, 0.0017635],
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[0.4987888, 0.6916906, 0.5106028]],
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'voxel_size': [0.04, 0.04],
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'box_prompts': [[0.65,0,0.3,1,1,0.79], [0.37, 0, 0, 1, 1, 0.2]],
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'voxel_size_box': [0.04, 0.04],
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'mask_prompts': [[0.3359364, 0.7555879, 0.6848574], [0.9221735, 0.1779197, 0.1927067]],
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'voxel_size_mask': [0.04, 0.04],
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}
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Objaverse_samples = [sample_0, sample_1, sample_2, sample_3, sample_4, sample_5, sample_6, sample_7, sample_8, sample_9, sample_10, sample_11]
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sample_0 = {'path': 'data/KITTI/scene1.npy',
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@@ -317,8 +351,8 @@ sample_4 = {'path': 'data/Semantic3D/patch1.npy',
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'voxel_size': [0.017, 0.017, 0.017, 0.017],
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'box_prompts': [],
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'voxel_size_box': [],
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'mask_prompts': [[0.1857393, 0.2675134, 0.2463012]],
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'voxel_size_mask': [0.01],
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}
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sample_5 = {'path': 'data/Semantic3D/patch50.npy',
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Semantic3D_samples = [sample_0, sample_1, sample_2, sample_3, sample_4, sample_5, sample_6]
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sample_3 = {'path': 'data/S3DIS/Area_2_WC_1.txt',
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'point_prompts': [[0.31414868, 0.59265659, 0.50951199], [0.6628697, 0.90842333, 0.34036394],[0.63868905, 0.36414687, 0.94954508],
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[0.11171063, 0.85788337, 0.18072787], #[0.76159073, 0.82289417, 0.68899917],
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[0.88589129, 0.59049676, 0.44830438],],
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'box_prompts': [[0.35, 0.8, 0.05, 0.45, 1.0, 0.4], [0.48, 0.65, 0.0, 0.55, 0.99, 0.99], [0.57, 0.2, 0.85, 0.7, 0.48, 1.0],
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[0.61, 0., 0.33, 0.71, 0.13, 0.51],], # [0.51, 0., 0., 0.61, 0.15, 0.37],
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'mask_prompts': [[0.31414868, 0.59265659, 0.50951199], [0.6628697, 0.90842333, 0.34036394],[0.63868905, 0.36414687, 0.94954508],
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[0.11171063, 0.85788337, 0.18072787], #[0.76159073, 0.82289417, 0.68899917],
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[0.88589129, 0.59049676, 0.44830438],],
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}
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sample_4 = {'path': 'data/S3DIS/Area_4_lobby_2.txt',
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'point_prompts': [[0.19949431, 0.28597082, 0.25131625], #[0.30316056, 0.87452301, 0.33696034],
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[0.72566372, 0.3617284, 0.65601966], [0.50316056, 0.57519641, 0.32186732],
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[0.46396966, 0.52345679, 0.54756055],],
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'box_prompts': [[0.42, 0.45, 0.3, 0.49, 0.54, 0.65], [0.45, 0.57, 0.27, 0.55, 0.63, 0.36], [0.17, 0.35, 0., 0.25, 0.4, 0.3],
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[0.15, 0.25, 0.4, 0.19, 0.33, 0.62], [0.17, 0.78, 0.27, 0.2, 0.84, 0.43]],
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'mask_prompts': [#[0.19949431, 0.28597082, 0.25131625], [0.30316056, 0.87452301, 0.33696034],
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[0.72566372, 0.3617284, 0.65601966], [0.50316056, 0.57519641, 0.32186732],
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[0.46396966, 0.52345679, 0.54756055],],
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}
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sample_1 = {'path': 'data/S3DIS/Area_5_office_3.txt',
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'point_prompts': [ #[0.45080659, 0.88824101, 0.22856252], [0.55965254, 0.72432783, 0.00623636], [0.36589257, 0.93683188, 0.64826941],
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[0.90161319, 0.51668286, 0.21546617], [0.98404538, 0.29024943, 0.51013408],
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[0.76369438, 0.32458698, 0.23542251]],
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'box_prompts': [[0., 0.48, 0.23, 0.12, 0.61, 0.31], [0.4, 0.25, 0., 0.6, 0.6, 0.3], [0.45, 0.85, 0.45, 0.65, 0.99, 0.55],
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[0.38, 0.95, 0.25, 0.48, 1.00, 0.42], [0.65, 0.45, 0., 0.75, 0.6, 0.3]],
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'mask_prompts': [[0.45080659, 0.88824101, 0.22856252],
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[0.90161319, 0.51668286, 0.21546617], [0.98404538, 0.29024943, 0.51013408],
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[0.76369438, 0.32458698, 0.23542251]], #[0.55965254, 0.72432783, 0.00623636], [0.36589257, 0.93683188, 0.64826941],
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}
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sample_0 = {'path': 'data/S3DIS/Area_6_office_9.txt',
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'point_prompts': [[0.16548, 0.27853667, 0.1886402], [0.46150787, 0.09795895, 0.26989673], [0.2904479, 0.5073498, 0.28115318],
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[0.9304859, 0.40291342, 0.32013769], [0.802557, 0.5818576, 0.19074],
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[0.52659518, 0.5240772, 0.40165232], [0.29337714, 0.8905976, 0.2722375], [0.563984, 0.925, 0.3803788],],
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# [0.73819816, 0.913756, 0.2815835 ], [0.338812, 0.48102965, 0.34078142]],
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'box_prompts': [[0.1, 0.2, 0.0, 0.2, 0.3, 0.4], [0.1, 0.02, 0.2, 0.9, 0.2, 0.3], [0.7, 0.5, 0., 0.9, 0.7, 0.4],
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[0.85, 0.3, 0.02, 0.98, 0.5, 0.8], [0.4, 0.4, 0.3, 0.6, 0.6, 0.5], ],
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'mask_prompts': [[0.16548, 0.27853667, 0.1886402], [0.46150787, 0.09795895, 0.26989673], [0.2904479, 0.5073498, 0.28115318],
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[0.9304859, 0.40291342, 0.32013769], [0.802557, 0.5818576, 0.19074],
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[0.52659518, 0.5240772, 0.40165232], [0.29337714, 0.8905976, 0.2722375], [0.563984, 0.925, 0.3803788],]
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# [0.73819816, 0.913756, 0.2815835 ], [0.338812, 0.48102965, 0.34078142]],
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}
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S3DIS_samples = [sample_2, sample_3, sample_4, sample_1, sample_0]
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# sample_0 = {'path': 'data/ScanNet/scene0001_01.pth',
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# 'point_prompts': [[0.48574361, 0.70011979, 0.21237852],
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# [0.28947121, 0.15144145, 0.24688229], [0.3489365, 0.53977334, 0.02221746],
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# [0.48059669, 0.88824904, 0.25690538]], #[0.48760539, 0.12294616, 0.25476629], #[0.48738128, 0.63986588, 0.25412986],
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+
# 'box_prompts': [[0.25, 0.63, 0., 0.57, 0.75, 0.37], [0.42, 0.83, 0., 0.54, 0.94, 0.3], [0.4, 0.05, 0.0, 0.53, 0.2, 0.3],
|
69 |
+
# [0.12, 0.35, 0.0, 0.22, 0.45, 0.24], [0.88, 0.2, 0.1, 0.95, 0.8, 0.48]],
|
70 |
+
# }
|
71 |
+
|
72 |
+
|
73 |
+
sample_1 = {'path': 'data/ScanNet/scene0005_01.pth', #[0.04293748, 0.38949549, 0.314679], [0.24069363, 0.51310396, 0.01414406],
|
74 |
+
'point_prompts': [[0.50845712, 0.4027696, 0.19570725], [0.26778319, 0.9830749, 0.44313431]], #[0.6458742, 0.33051795, 0.31433141], [0.11679079, 0.60943264, 0.40539789],
|
75 |
+
'box_prompts': [[0.6, 0.6, 0., 0.83, 0.9, 0.33], [0.0, 0.57, 0.05, 0.15, 0.67, 0.48], #[0.41, 0.65, 0., 0.56, 0.77, 0.35],
|
76 |
[0.48, 0.95, 0.58, 0.8, 0.99, 0.9]],
|
77 |
'mask_prompts': [[0.50845712, 0.4027696, 0.19570725], [0.26778319, 0.9830749, 0.44313431]],
|
78 |
}
|
79 |
sample_2 = {'path': 'data/ScanNet/scene0010_01.pth',
|
80 |
+
'point_prompts': [[0.86644632, 0.26297486, 0.5173167]], #[0.15311202, 0.44485098, 0.4582684], [0.89919734, 0.40822271, 0.6298126 ]], #,[0.66389197, 0.49352551, 0.2987611], [0.09592603, 0.20024474, 0.67744112]
|
81 |
'box_prompts': [[0.6, 0.72, 0.0, 0.75, 0.85, 0.6], [0.75, 0.70, 0.5, 0.92, 0.92, 0.75], [0.05, 0.92, 0.05, 0.27, 1.0, 0.82],
|
82 |
[0.35, 0.03, 0.15, 0.5, 0.1, 0.42], ],
|
83 |
'mask_prompts': [[0.86644632, 0.26297486, 0.5173167]],
|
|
|
86 |
|
87 |
sample_3 = {'path': 'data/ScanNet/scene0016_02.pth',
|
88 |
'point_prompts': [[0.2898192, 0.5845358, 0.7862434], [0.8251329,0.1763976,0.2942619]],
|
89 |
+
# [[0.77345204, 0.5883323, 0.21049459], [0.82484114, 0.16314957, 0.23850442], [0.97325081, 0.28361404, 0.15121479],
|
90 |
+
# [0.29043797, 0.58934051, 0.82521498], [0.46316043, 0.34840286, 0.01032902], [0.3637068, 0.50896871, 0.63058698]],
|
91 |
+
'box_prompts': [[0.72, 0.36, 0.1, 0.9, 0.75, 0.75], [0.27, 0.54, 0.7, 0.3, 0.65, 0.9],], #[0.86, 0.12, 0.33, 0.99, 0.24, 0.54], [0.42, 0.5, 0.05, 0.55, 0.68, 0.42]
|
92 |
'mask_prompts': [[0.2898192, 0.5845358, 0.7862434]],
|
93 |
}
|
94 |
|
95 |
|
96 |
sample_4 = {'path': 'data/ScanNet/scene0019_01.pth',
|
97 |
+
'point_prompts': [[0.52182293, 0.69650459, 0.36580974], [0.6603151, 0.26341686, 0.33537653],[0.03188787, 0.65648252, 0.43863711]], #
|
98 |
+
# [0.79430991, 0.31488013, 0.2448331], [0.14427963, 0.69153076, 0.20673281], [0.17163187, 0.30585486, 0.31457961],
|
99 |
+
'box_prompts': [[0.55, 0.22, 0.05, 0.72, 0.3, 0.58], [0.0, 0.27, 0.05, 0.2, 0.35, 0.45]], #[0.03, 0.59, 0.05, 0.2, 0.85, 0.35],
|
100 |
+
# [0.43, 0.65, 0.05, 0.64, 0.72, 0.65]],
|
101 |
'mask_prompts': [[0.52182293, 0.69650459, 0.36580974], [0.6603151, 0.26341686, 0.33537653], [0.17163187, 0.30585486, 0.31457961], [0.03188787, 0.65648252, 0.43863711]],
|
102 |
}
|
103 |
|
|
|
112 |
'mask_prompts': [[0.56711978, 0.74271345, 0.1753805 ], [0.61877084, 0.47617316, 0.23380645]],
|
113 |
}
|
114 |
|
115 |
+
ScanNet_samples = [sample_1, sample_2, sample_3, sample_4, sample_5, sample_6] #sample_0,
|
116 |
|
117 |
|
118 |
sample_0 = {'path': 'data/Objaverse/plant.npy',
|
119 |
+
'point_prompts': [[0.50455284, 0.47794762, 0.0007253083], [0.28331658, 0.19435011, 0.77393067]], #[7006, 1458],
|
120 |
'voxel_size': [0.038, 0.04],
|
121 |
+
# 'voxel_size': [0.03, 0.04],
|
122 |
+
'box_prompts': [[0.08, 0.18, -0.02, 0.68, 0.73, 0.315]], #, [0, 0, 0.3, 1, 1, 1.01]], #[0.11, 0.43, 0.82, 0.5, 1.01, 1.01]],
|
123 |
+
'voxel_size_box': [0.04, 0.05], #0.01,
|
124 |
+
'mask_prompts': [[0.50455284, 0.47794762, 0.0007253083]], #[7006, 1458], , [0.28331658, 0.19435011, 0.77393067]
|
125 |
'voxel_size_mask': [0.038]
|
126 |
}
|
127 |
|
128 |
|
129 |
sample_1 = {'path': 'data/Objaverse/human.npy',
|
130 |
+
'point_prompts': [[0.57825595, 0.5005686, 0.11494722], [0.7136412, 0.49501216, 0.5020814 ], [0.7136412, 0.49501216, 0.5020814 ]], #[1112, 2133, 2133],
|
131 |
'voxel_size': [0.055, 0.045, 0.05],
|
132 |
'box_prompts': [[0., 0.17, -0.01, 0.72, 0.80, 0.3], [-0.01, 0., 0.28, 0.8, 1, 0.82], [-0.01, 0.28, 0.89, 1, 0.72, 1.02]],
|
133 |
'voxel_size_box': [0.055, 0.045, 0.055],
|
134 |
+
'mask_prompts': [[0.57825595, 0.5005686, 0.11494722], [0.7136412, 0.49501216, 0.5020814 ]], #[1112, 2133, 2133],
|
135 |
'voxel_size_mask': [0.055, 0.055],
|
136 |
}
|
137 |
sample_2 = {'path': 'data/Objaverse/lock.npy',
|
138 |
+
'point_prompts': [[0.6513301, 0.6753892, 0.52316076], [0.21359734, 0.6097132 , 0.7939796 ], [0.44947368, 0.21654338, 0.58450174]], #[1029, 2064, 3541], #, [0.67447126, 0.6777649 , 0.51486933]
|
139 |
+
'voxel_size': [0.04, 0.05, 0.05], #, 0.05
|
140 |
+
'box_prompts': [[0.61, 0.4, 0.35, 0.8, 0.8, 0.6], [0.42, -0.02, -0.02, 1.02, 0.4, 1]], #[0., 0.25, -0.02, 0.4, 0.82, 1],
|
141 |
+
'voxel_size_box': [0.04, 0.011], # 0.05, 0.04
|
142 |
+
'mask_prompts': [[0.6513301, 0.6753892, 0.52316076], [0.21359734, 0.6097132 , 0.7939796 ], [0.9157764, 0.1995991, 0.14024617]], #[1029, 2064, 3541],
|
143 |
'voxel_size_mask': [0.04, 0.055, 0.04],
|
144 |
}
|
145 |
|
|
|
171 |
}
|
172 |
|
173 |
sample_6 = {'path': 'data/Objaverse/popcorn_machine.npy',
|
174 |
+
'point_prompts': [[0.278306, 0.4913014, 0.7318756], [0.5867118, 0.1180351, 0.5844101]], #, [0.8857, 0.8296, 0.6090]],
|
175 |
'voxel_size': [0.04, 0.04],
|
176 |
'box_prompts': [[0.208, 0.157, 0.493, 0.779, 0.89, 0.925]],
|
177 |
'voxel_size_box': [0.04],
|
178 |
+
'mask_prompts': [[0.278306, 0.4913014, 0.7318756], [0.5867118, 0.1180351, 0.5844101]], #, [0.8857, 0.8296, 0.6090]],
|
179 |
'voxel_size_mask': [0.04, 0.04],
|
180 |
}
|
181 |
|
|
|
201 |
sample_9 = {'path': 'data/Objaverse/thor_hammer.npy',
|
202 |
'point_prompts': [[0.6211515, 0.5109989, 0.3867725], [0.44443, 0.2363458, 0.7229376]],
|
203 |
'voxel_size': [0.05, 0.05, 0.05],
|
204 |
+
'box_prompts': [[0,0,0.723,1,1,1]], #, [0.353, 0.41, 0, 0.636, 0.586, 0.725]],
|
205 |
'voxel_size_box': [0.05, 0.05],
|
206 |
'mask_prompts': [[0.44443, 0.2363458, 0.7229376]],
|
207 |
'voxel_size_mask': [0.05],
|
|
|
210 |
sample_10 = {'path': 'data/Objaverse/horse.npy',
|
211 |
'point_prompts': [[0.3359364, 0.7555879, 0.6848574], [0.9221735, 0.1779197, 0.1927067]],
|
212 |
'voxel_size': [0.04, 0.04],
|
213 |
+
'box_prompts': [[0.65,0,0.3,1,1,0.79], [0.37, 0, 0, 1, 1, 0.2]], #, [0.353, 0.41, 0, 0.636, 0.586, 0.725]],
|
214 |
'voxel_size_box': [0.04, 0.04],
|
215 |
'mask_prompts': [[0.3359364, 0.7555879, 0.6848574], [0.9221735, 0.1779197, 0.1927067]],
|
216 |
'voxel_size_mask': [0.04, 0.04],
|
|
|
221 |
[0.9192697, 0.4469184, 0.0017635],
|
222 |
[0.4987888, 0.6916906, 0.5106028]],
|
223 |
'voxel_size': [0.04, 0.04],
|
224 |
+
'box_prompts': [[0.65,0,0.3,1,1,0.79], [0.37, 0, 0, 1, 1, 0.2]], #, [0.353, 0.41, 0, 0.636, 0.586, 0.725]],
|
225 |
'voxel_size_box': [0.04, 0.04],
|
226 |
'mask_prompts': [[0.3359364, 0.7555879, 0.6848574], [0.9221735, 0.1779197, 0.1927067]],
|
227 |
'voxel_size_mask': [0.04, 0.04],
|
228 |
}
|
229 |
+
# sculpture.npy
|
230 |
+
# horse.npy
|
231 |
+
# pipe.npy
|
232 |
+
# dinner_booth.npy
|
233 |
+
# ornament.npy
|
234 |
+
# blender.npy
|
235 |
+
# bowl.npy
|
236 |
+
# human_face.npy
|
237 |
+
# table.npy
|
238 |
+
# telescope.npy
|
239 |
+
# planet.npy
|
240 |
+
# lamp.npy
|
241 |
+
# dragon.npy
|
242 |
|
243 |
Objaverse_samples = [sample_0, sample_1, sample_2, sample_3, sample_4, sample_5, sample_6, sample_7, sample_8, sample_9, sample_10, sample_11]
|
244 |
+
# sample_1, sample_2,
|
245 |
+
|
246 |
|
247 |
|
248 |
sample_0 = {'path': 'data/KITTI/scene1.npy',
|
|
|
351 |
'voxel_size': [0.017, 0.017, 0.017, 0.017],
|
352 |
'box_prompts': [],
|
353 |
'voxel_size_box': [],
|
354 |
+
'mask_prompts': [[0.1857393, 0.2675134, 0.2463012]], #[[0.51603703, 0.51312565, 0.50598845]],
|
355 |
+
'voxel_size_mask': [0.01], #[0.01],
|
356 |
}
|
357 |
|
358 |
sample_5 = {'path': 'data/Semantic3D/patch50.npy',
|
|
|
377 |
Semantic3D_samples = [sample_0, sample_1, sample_2, sample_3, sample_4, sample_5, sample_6]
|
378 |
|
379 |
|
380 |
+
|
381 |
+
|
382 |
+
VOXEL = {"point": "voxel_size", "box": "voxel_size_box", "mask": "voxel_size_mask"}
|
383 |
+
|