jd7h/luciddreamer 🔢📝 → 🖼️
About
High-Fidelity Text-to-3D Generation via Interval Score Matching
Example Output
Prompt:
"A dog on a skateboard, hair waving in the wind, HDR, photorealistic, 8K"
Output
Performance Metrics
1004.99s
Prediction Time
1104.81s
Total Time
All Input Parameters
{
"cfg": 7.5,
"prompt": "A dog on a skateboard, hair waving in the wind, HDR, photorealistic, 8K",
"iterations": 1000,
"neg_prompt": "unrealistic, blurry, low quality, out of focus, ugly, low contrast, dull, low resolution, distorted, boring",
"init_prompt": "dog"
}
Input Parameters
- cfg
- CFG
- seed
- Seed. Leave blank for a random seed.
- prompt (required)
- Your prompt
- iterations
- Number of iterations
- neg_prompt
- Negative prompt
- init_prompt
- Optional Point-E init prompt
Output Schema
Output
Example Execution Logs
Using seed: 2212729883 Test iter: [1, 200, 400, 600, 800, 1000] Save iter: [500, 1000] Optimizing Output folder: ./output/Replicate [22/12 16:16:11] Tensorboard not available: not logging progress [22/12 16:16:11] Reading Test Transforms [22/12 16:16:11] creating base model...[22/12 16:16:12] 0%| | 0.00/890M [00:00<?, ?iB/s] 1%|▍ | 10.9M/890M [00:00<00:08, 115MiB/s] 3%|▉ | 22.7M/890M [00:00<00:07, 120MiB/s] 4%|█▍ | 34.2M/890M [00:00<00:07, 114MiB/s] 5%|█▉ | 45.1M/890M [00:00<00:08, 106MiB/s] 6%|██▌ | 57.7M/890M [00:00<00:07, 115MiB/s] 8%|███ | 68.7M/890M [00:00<00:07, 111MiB/s] 9%|███▍ | 79.4M/890M [00:00<00:07, 111MiB/s] 10%|███▉ | 90.0M/890M [00:00<00:07, 110MiB/s] 12%|████▋ | 103M/890M [00:00<00:07, 118MiB/s] 13%|█████▏ | 115M/890M [00:01<00:06, 120MiB/s] 14%|█████▋ | 127M/890M [00:01<00:06, 123MiB/s] 16%|██████▎ | 140M/890M [00:01<00:06, 125MiB/s] 17%|██████▊ | 152M/890M [00:01<00:06, 114MiB/s] 18%|███████▎ | 163M/890M [00:01<00:07, 107MiB/s] 19%|███████▊ | 173M/890M [00:01<00:07, 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[00:08<00:00, 119MiB/s] 97%|██████████████████████████████████████▉ | 866M/890M [00:08<00:00, 120MiB/s] 99%|███████████████████████████████████████▍| 878M/890M [00:08<00:00, 120MiB/s] 100%|███████████████████████████████████████▉| 890M/890M [00:08<00:00, 121MiB/s] 100%|████████████████████████████████████████| 890M/890M [00:08<00:00, 110MiB/s] creating upsample model... [22/12 16:16:28] downloading base checkpoint... [22/12 16:16:33] 0%| | 0.00/161M [00:00<?, ?iB/s] 6%|▌ | 9.18M/161M [00:00<00:01, 90.8MiB/s] 11%|█▏ | 18.3M/161M [00:00<00:01, 74.8MiB/s] 16%|█▌ | 26.2M/161M [00:00<00:01, 76.4MiB/s] 21%|██ | 34.0M/161M [00:00<00:01, 76.3MiB/s] 26%|██▌ | 42.3M/161M [00:00<00:01, 78.6MiB/s] 31%|███ | 50.3M/161M [00:00<00:01, 78.7MiB/s] 37%|███▋ | 59.1M/161M [00:00<00:01, 81.6MiB/s] 42%|████▏ | 67.4M/161M [00:00<00:01, 81.8MiB/s] 47%|████▋ | 76.0M/161M [00:00<00:01, 82.6MiB/s] 52%|█████▏ | 84.2M/161M [00:01<00:00, 80.5MiB/s] 57%|█████▋ | 92.3M/161M [00:01<00:00, 75.6MiB/s] 62%|██████▏ | 99.9M/161M [00:01<00:00, 73.4MiB/s] 68%|██████▊ | 109M/161M [00:01<00:00, 77.9MiB/s] 73%|███████▎ | 117M/161M [00:01<00:00, 78.7MiB/s] 78%|███████▊ | 126M/161M [00:01<00:00, 81.0MiB/s] 83%|████████▎ | 134M/161M [00:01<00:00, 73.2MiB/s] 88%|████████▊ | 141M/161M [00:01<00:00, 68.7MiB/s] 92%|█████████▏| 149M/161M [00:01<00:00, 70.8MiB/s] 97%|█████████▋| 157M/161M [00:02<00:00, 71.5MiB/s] 100%|██████████| 161M/161M [00:02<00:00, 76.3MiB/s] downloading upsampler checkpoint... [22/12 16:16:35] 0%| | 0.00/162M [00:00<?, ?iB/s] 6%|▌ | 8.98M/162M [00:00<00:01, 84.4MiB/s] 11%|█ | 17.7M/162M [00:00<00:01, 85.6MiB/s] 16%|█▌ | 26.3M/162M [00:00<00:01, 68.1MiB/s] 21%|██▏ | 34.6M/162M [00:00<00:01, 72.9MiB/s] 26%|██▋ | 42.8M/162M [00:00<00:01, 76.0MiB/s] 31%|███▏ | 50.7M/162M [00:00<00:01, 72.0MiB/s] 36%|███▋ | 58.7M/162M [00:00<00:01, 74.6MiB/s] 41%|████ | 66.3M/162M [00:00<00:01, 73.9MiB/s] 46%|████▋ | 75.0M/162M [00:00<00:01, 77.9MiB/s] 51%|█████ | 82.9M/162M [00:01<00:01, 76.4MiB/s] 56%|█████▋ | 91.5M/162M [00:01<00:00, 79.1MiB/s] 61%|██████▏ | 99.4M/162M [00:01<00:00, 76.0MiB/s] 66%|██████▌ | 107M/162M [00:01<00:00, 75.1MiB/s] 71%|███████ | 115M/162M [00:01<00:00, 72.0MiB/s] 75%|███████▌ | 122M/162M [00:01<00:00, 67.8MiB/s] 79%|███████▉ | 129M/162M [00:01<00:00, 65.5MiB/s] 84%|████████▎ | 136M/162M [00:01<00:00, 66.2MiB/s] 89%|████████▉ | 144M/162M [00:01<00:00, 70.9MiB/s] 94%|█████████▍| 153M/162M [00:02<00:00, 76.2MiB/s] 99%|█████████▉| 160M/162M [00:02<00:00, 62.2MiB/s] 100%|██████████| 162M/162M [00:02<00:00, 71.7MiB/s] 0it [00:00, ?it/s] 1it [00:01, 1.13s/it] 4it [00:01, 3.98it/s] 7it [00:01, 7.11it/s] 10it [00:01, 10.06it/s] 13it [00:01, 12.68it/s] 16it [00:01, 14.89it/s] 19it [00:01, 16.66it/s] 22it [00:02, 18.06it/s] 25it [00:02, 19.11it/s] 28it [00:02, 19.89it/s] 31it [00:02, 20.46it/s] 34it [00:02, 20.85it/s] 37it [00:02, 21.15it/s] 40it [00:02, 21.35it/s] 43it [00:03, 21.48it/s] 46it [00:03, 21.57it/s] 49it [00:03, 21.63it/s] 52it [00:03, 21.66it/s] 55it [00:03, 21.69it/s] 58it [00:03, 21.74it/s] 61it [00:03, 21.78it/s] 64it [00:04, 21.79it/s] 67it [00:04, 16.75it/s] 69it [00:04, 11.47it/s] 71it [00:05, 9.06it/s] 73it [00:05, 7.75it/s] 74it [00:05, 7.28it/s] 75it [00:05, 6.86it/s] 76it [00:05, 6.51it/s] 77it [00:06, 6.23it/s] 78it [00:06, 6.03it/s] 79it [00:06, 5.87it/s] 80it [00:06, 5.76it/s] 81it [00:06, 5.68it/s] 82it [00:07, 5.62it/s] 83it [00:07, 5.58it/s] 84it [00:07, 5.54it/s] 85it [00:07, 5.52it/s] 86it [00:07, 5.50it/s] 87it [00:07, 5.50it/s] 88it [00:08, 5.49it/s] 89it [00:08, 5.48it/s] 90it [00:08, 5.48it/s] 91it [00:08, 5.48it/s] 92it [00:08, 5.47it/s] 93it [00:09, 5.47it/s] 94it [00:09, 5.47it/s] 95it [00:09, 5.47it/s] 96it [00:09, 5.46it/s] 97it [00:09, 5.45it/s] 98it [00:09, 5.45it/s] 99it [00:10, 5.46it/s] 100it [00:10, 5.46it/s] 101it [00:10, 5.46it/s] 102it [00:10, 5.45it/s] 103it [00:10, 5.45it/s] 104it [00:11, 5.42it/s] 105it [00:11, 5.44it/s] 106it [00:11, 5.45it/s] 107it [00:11, 5.44it/s] 108it [00:11, 5.44it/s] 109it [00:11, 5.44it/s] 110it [00:12, 5.43it/s] 111it [00:12, 5.43it/s] 112it [00:12, 5.43it/s] 113it [00:12, 5.43it/s] 114it [00:12, 5.43it/s] 115it [00:13, 5.42it/s] 116it [00:13, 5.42it/s] 117it [00:13, 5.42it/s] 118it [00:13, 5.42it/s] 119it [00:13, 5.42it/s] 120it [00:14, 5.42it/s] 121it [00:14, 5.41it/s] 122it [00:14, 5.42it/s] 123it [00:14, 5.42it/s] 124it [00:14, 5.42it/s] 125it [00:14, 5.42it/s] 126it [00:15, 5.42it/s] 127it [00:15, 5.42it/s] 128it [00:15, 5.42it/s] 129it [00:15, 5.42it/s] 130it [00:15, 8.29it/s] Generating random point cloud (81920)... [22/12 16:16:53] Number of points at initialisation : 81920 [22/12 16:16:54] train_process is in : ./output/Replicate/train_process/ [22/12 16:16:54] [INFO] loading stable diffusion... [22/12 16:16:57] [INFO] loaded stable diffusion! [22/12 16:16:59] test views is in : ./output/Replicate/test_six_views/1_iteration [22/12 16:17:15] [ITER 1] Eval Done! [22/12 16:17:15] videos is in : ./output/Replicate/videos/1_iteration [22/12 16:17:15] Generating Video using 240 different view points[22/12 16:17:21] [ITER 1] Video Save Done! [22/12 16:17:24] Training progress: 0%| | 0/1000 [00:00<?, ?it/s] Training progress: 0%| | 0/1000 [00:32<?, ?it/s, Loss=1.0017186] Training progress: 1%| | 10/1000 [00:32<53:16, 3.23s/it, Loss=1.0017186] Training progress: 1%| | 10/1000 [00:40<53:16, 3.23s/it, Loss=1.0077757] Training progress: 2%|▏ | 20/1000 [00:40<29:57, 1.83s/it, Loss=1.0077757] Training progress: 2%|▏ | 20/1000 [00:49<29:57, 1.83s/it, Loss=1.0079711] Training progress: 3%|▎ | 30/1000 [00:49<22:13, 1.37s/it, Loss=1.0079711] Training progress: 3%|▎ | 30/1000 [00:57<22:13, 1.37s/it, Loss=1.0078438] Training progress: 4%|▍ | 40/1000 [00:57<18:36, 1.16s/it, Loss=1.0078438] Training progress: 4%|▍ | 40/1000 [01:05<18:36, 1.16s/it, Loss=1.0082182] Training progress: 5%|▌ | 50/1000 [01:05<16:07, 1.02s/it, Loss=1.0082182] Training progress: 5%|▌ | 50/1000 [01:13<16:07, 1.02s/it, Loss=1.0086312] Training progress: 6%|▌ | 60/1000 [01:13<14:56, 1.05it/s, Loss=1.0086312] Training progress: 6%|▌ | 60/1000 [01:21<14:56, 1.05it/s, Loss=1.0084402] Training progress: 7%|▋ | 70/1000 [01:21<14:01, 1.11it/s, Loss=1.0084402] Training progress: 7%|▋ | 70/1000 [01:29<14:01, 1.11it/s, Loss=1.0085526] Training progress: 8%|▊ | 80/1000 [01:29<13:33, 1.13it/s, Loss=1.0085526] Training progress: 8%|▊ | 80/1000 [01:38<13:33, 1.13it/s, Loss=1.0085533] Training progress: 9%|▉ | 90/1000 [01:38<13:09, 1.15it/s, Loss=1.0085533] Training progress: 9%|▉ | 90/1000 [01:48<13:09, 1.15it/s, Loss=1.0085533] Training progress: 10%|█ | 100/1000 [01:48<13:34, 1.11it/s, Loss=1.0085533] Training progress: 10%|█ | 100/1000 [01:56<13:34, 1.11it/s, Loss=1.0088473] Training progress: 11%|█ | 110/1000 [01:56<12:57, 1.15it/s, Loss=1.0088473] Training progress: 11%|█ | 110/1000 [02:04<12:57, 1.15it/s, Loss=1.0088198] Training progress: 12%|█▏ | 120/1000 [02:04<12:33, 1.17it/s, Loss=1.0088198] Training progress: 12%|█▏ | 120/1000 [02:12<12:33, 1.17it/s, Loss=1.0089299] Training progress: 13%|█▎ | 130/1000 [02:12<12:04, 1.20it/s, Loss=1.0089299] Training progress: 13%|█▎ | 130/1000 [02:20<12:04, 1.20it/s, Loss=1.0090425] Training progress: 14%|█▍ | 140/1000 [02:20<11:48, 1.21it/s, Loss=1.0090425] Training progress: 14%|█▍ | 140/1000 [02:28<11:48, 1.21it/s, Loss=1.0093045] Training progress: 15%|█▌ | 150/1000 [02:28<11:36, 1.22it/s, Loss=1.0093045] Training progress: 15%|█▌ | 150/1000 [02:36<11:36, 1.22it/s, Loss=1.0089162] Training progress: 16%|█▌ | 160/1000 [02:36<11:19, 1.24it/s, Loss=1.0089162] Training progress: 16%|█▌ | 160/1000 [02:44<11:19, 1.24it/s, Loss=1.0091812] Training progress: 17%|█▋ | 170/1000 [02:44<11:13, 1.23it/s, Loss=1.0091812] Training progress: 17%|█▋ | 170/1000 [02:52<11:13, 1.23it/s, Loss=1.0082853] Training progress: 18%|█▊ | 180/1000 [02:52<11:06, 1.23it/s, Loss=1.0082853] Training progress: 18%|█▊ | 180/1000 [03:00<11:06, 1.23it/s, Loss=1.0082300] Training progress: 19%|█▉ | 190/1000 [03:00<10:48, 1.25it/s, Loss=1.0082300] Training progress: 19%|█▉ | 190/1000 [03:09<10:48, 1.25it/s, Loss=1.0085656] test views is in : ./output/Replicate/test_six_views/200_iteration[22/12 16:20:08] [ITER 200] Eval Done! [22/12 16:20:09] videos is in : ./output/Replicate/videos/200_iteration[22/12 16:20:09] Generating Video using 240 different view points[22/12 16:20:15] [ITER 200] Video Save Done! [22/12 16:20:17] Training progress: 20%|██ | 200/1000 [03:09<11:08, 1.20it/s, Loss=1.0085656] Training progress: 20%|██ | 200/1000 [03:27<11:08, 1.20it/s, Loss=1.0087679] Training progress: 21%|██ | 210/1000 [03:27<14:44, 1.12s/it, Loss=1.0087679] Training progress: 21%|██ | 210/1000 [03:35<14:44, 1.12s/it, Loss=1.0089540] Training progress: 22%|██▏ | 220/1000 [03:35<13:32, 1.04s/it, Loss=1.0089540] Training progress: 22%|██▏ | 220/1000 [03:44<13:32, 1.04s/it, Loss=1.0088401] Training progress: 23%|██▎ | 230/1000 [03:44<12:39, 1.01it/s, Loss=1.0088401] Training progress: 23%|██▎ | 230/1000 [03:52<12:39, 1.01it/s, Loss=1.0080839] Training progress: 24%|██▍ | 240/1000 [03:52<12:04, 1.05it/s, Loss=1.0080839] Training progress: 24%|██▍ | 240/1000 [04:01<12:04, 1.05it/s, Loss=1.0084546] Training progress: 25%|██▌ | 250/1000 [04:01<11:26, 1.09it/s, Loss=1.0084546] Training progress: 25%|██▌ | 250/1000 [04:09<11:26, 1.09it/s, Loss=1.0087927] Training progress: 26%|██▌ | 260/1000 [04:09<10:56, 1.13it/s, Loss=1.0087927] Training progress: 26%|██▌ | 260/1000 [04:17<10:56, 1.13it/s, Loss=1.0085855] Training progress: 27%|██▋ | 270/1000 [04:17<10:30, 1.16it/s, Loss=1.0085855] Training progress: 27%|██▋ | 270/1000 [04:26<10:30, 1.16it/s, Loss=1.0083972] Training progress: 28%|██▊ | 280/1000 [04:26<10:20, 1.16it/s, Loss=1.0083972] Training progress: 28%|██▊ | 280/1000 [04:34<10:20, 1.16it/s, Loss=1.0090715] Training progress: 29%|██▉ | 290/1000 [04:34<10:08, 1.17it/s, Loss=1.0090715] Training progress: 29%|██▉ | 290/1000 [04:44<10:08, 1.17it/s, Loss=1.0085778] Training progress: 30%|███ | 300/1000 [04:44<10:18, 1.13it/s, Loss=1.0085778] Training progress: 30%|███ | 300/1000 [04:52<10:18, 1.13it/s, Loss=1.0078171] Training progress: 31%|███ | 310/1000 [04:52<09:56, 1.16it/s, Loss=1.0078171] Training progress: 31%|███ | 310/1000 [05:01<09:56, 1.16it/s, Loss=1.0089422] Training progress: 32%|███▏ | 320/1000 [05:01<10:04, 1.12it/s, Loss=1.0089422] Training progress: 32%|███▏ | 320/1000 [05:10<10:04, 1.12it/s, Loss=1.0096785] Training progress: 33%|███▎ | 330/1000 [05:10<09:47, 1.14it/s, Loss=1.0096785] Training progress: 33%|███▎ | 330/1000 [05:18<09:47, 1.14it/s, Loss=1.0101533] Training progress: 34%|███▍ | 340/1000 [05:18<09:31, 1.15it/s, Loss=1.0101533] Training progress: 34%|███▍ | 340/1000 [05:26<09:31, 1.15it/s, Loss=1.0105944] Training progress: 35%|███▌ | 350/1000 [05:26<09:15, 1.17it/s, Loss=1.0105944] Training progress: 35%|███▌ | 350/1000 [05:35<09:15, 1.17it/s, Loss=1.0102142] Training progress: 36%|███▌ | 360/1000 [05:35<09:04, 1.18it/s, Loss=1.0102142] Training progress: 36%|███▌ | 360/1000 [05:44<09:04, 1.18it/s, Loss=1.0089403] Training progress: 37%|███▋ | 370/1000 [05:44<08:59, 1.17it/s, Loss=1.0089403] Training progress: 37%|███▋ | 370/1000 [05:52<08:59, 1.17it/s, Loss=1.0095749] Training progress: 38%|███▊ | 380/1000 [05:52<08:44, 1.18it/s, Loss=1.0095749] Training progress: 38%|███▊ | 380/1000 [06:00<08:44, 1.18it/s, Loss=1.0104323] Training progress: 39%|███▉ | 390/1000 [06:00<08:28, 1.20it/s, Loss=1.0104323] Training progress: 39%|███▉ | 390/1000 [06:09<08:28, 1.20it/s, Loss=1.0101397] test views is in : ./output/Replicate/test_six_views/400_iteration [22/12 16:23:08] [ITER 400] Eval Done! [22/12 16:23:09] videos is in : ./output/Replicate/videos/400_iteration [22/12 16:23:09] Generating Video using 240 different view points[22/12 16:23:15] [ITER 400] Video Save Done! [22/12 16:23:18] Training progress: 40%|████ | 400/1000 [06:09<08:33, 1.17it/s, Loss=1.0101397] Training progress: 40%|████ | 400/1000 [06:27<08:33, 1.17it/s, Loss=1.0088887] Training progress: 41%|████ | 410/1000 [06:27<11:11, 1.14s/it, Loss=1.0088887] Training progress: 41%|████ | 410/1000 [06:36<11:11, 1.14s/it, Loss=1.0095410] Training progress: 42%|████▏ | 420/1000 [06:36<10:23, 1.08s/it, Loss=1.0095410] Training progress: 42%|████▏ | 420/1000 [06:45<10:23, 1.08s/it, Loss=1.0092835] Training progress: 43%|████▎ | 430/1000 [06:45<09:41, 1.02s/it, Loss=1.0092835] Training progress: 43%|████▎ | 430/1000 [06:54<09:41, 1.02s/it, Loss=1.0091632] Training progress: 44%|████▍ | 440/1000 [06:54<09:09, 1.02it/s, Loss=1.0091632] Training progress: 44%|████▍ | 440/1000 [07:03<09:09, 1.02it/s, Loss=1.0088365] Training progress: 45%|████▌ | 450/1000 [07:03<08:45, 1.05it/s, Loss=1.0088365] Training progress: 45%|████▌ | 450/1000 [07:11<08:45, 1.05it/s, Loss=1.0097462] Training progress: 46%|████▌ | 460/1000 [07:11<08:13, 1.09it/s, Loss=1.0097462] Training progress: 46%|████▌ | 460/1000 [07:19<08:13, 1.09it/s, Loss=1.0092854] Training progress: 47%|████▋ | 470/1000 [07:19<07:49, 1.13it/s, Loss=1.0092854] Training progress: 47%|████▋ | 470/1000 [07:28<07:49, 1.13it/s, Loss=1.0093460] Training progress: 48%|████▊ | 480/1000 [07:28<07:39, 1.13it/s, Loss=1.0093460] Training progress: 48%|████▊ | 480/1000 [07:37<07:39, 1.13it/s, Loss=1.0090952] scale up theta_range to: [60, 90] [22/12 16:24:43] scale up radius_range to: [4.9399999999999995, 5.225] [22/12 16:24:43] scale up phi_range to: [-180, 180] [22/12 16:24:43] scale up fovy_range to: [0.24, 0.6] [22/12 16:24:43] Training progress: 49%|████▉ | 490/1000 [07:37<07:25, 1.14it/s, Loss=1.0090952] Training progress: 49%|████▉ | 490/1000 [07:45<07:25, 1.14it/s, Loss=1.0091098] [ITER 500] Saving Gaussians [22/12 16:24:45] Training progress: 50%|█████ | 500/1000 [07:45<07:20, 1.14it/s, Loss=1.0091098] Training progress: 50%|█████ | 500/1000 [07:57<07:20, 1.14it/s, Loss=1.0093191] Training progress: 51%|█████ | 510/1000 [07:57<07:47, 1.05it/s, Loss=1.0093191] Training progress: 51%|█████ | 510/1000 [08:05<07:47, 1.05it/s, Loss=1.0097375] Training progress: 52%|█████▏ | 520/1000 [08:05<07:20, 1.09it/s, Loss=1.0097375] Training progress: 52%|█████▏ | 520/1000 [08:14<07:20, 1.09it/s, Loss=1.0100511] Training progress: 53%|█████▎ | 530/1000 [08:14<07:02, 1.11it/s, Loss=1.0100511] Training progress: 53%|█████▎ | 530/1000 [08:23<07:02, 1.11it/s, Loss=1.0102542] Training progress: 54%|█████▍ | 540/1000 [08:23<06:58, 1.10it/s, Loss=1.0102542] Training progress: 54%|█████▍ | 540/1000 [08:32<06:58, 1.10it/s, Loss=1.0098752] Training progress: 55%|█████▌ | 550/1000 [08:32<06:42, 1.12it/s, Loss=1.0098752] Training progress: 55%|█████▌ | 550/1000 [08:40<06:42, 1.12it/s, Loss=1.0098831] Training progress: 56%|█████▌ | 560/1000 [08:40<06:26, 1.14it/s, Loss=1.0098831] Training progress: 56%|█████▌ | 560/1000 [08:49<06:26, 1.14it/s, Loss=1.0099793] Training progress: 57%|█████▋ | 570/1000 [08:49<06:14, 1.15it/s, Loss=1.0099793] Training progress: 57%|█████▋ | 570/1000 [08:57<06:14, 1.15it/s, Loss=1.0098103] Training progress: 58%|█████▊ | 580/1000 [08:57<06:02, 1.16it/s, Loss=1.0098103] Training progress: 58%|█████▊ | 580/1000 [09:06<06:02, 1.16it/s, Loss=1.0090983] Training progress: 59%|█████▉ | 590/1000 [09:06<05:56, 1.15it/s, Loss=1.0090983] Training progress: 59%|█████▉ | 590/1000 [09:15<05:56, 1.15it/s, Loss=1.0095025] test views is in : ./output/Replicate/test_six_views/600_iteration [22/12 16:26:14] [ITER 600] Eval Done! [22/12 16:26:15] videos is in : ./output/Replicate/videos/600_iteration[22/12 16:26:15] Generating Video using 240 different view points[22/12 16:26:21] [ITER 600] Video Save Done! [22/12 16:26:24] Training progress: 60%|██████ | 600/1000 [09:15<05:55, 1.13it/s, Loss=1.0095025] Training progress: 60%|██████ | 600/1000 [09:34<05:55, 1.13it/s, Loss=1.0120878] Training progress: 61%|██████ | 610/1000 [09:34<07:41, 1.18s/it, Loss=1.0120878] Training progress: 61%|██████ | 610/1000 [09:43<07:41, 1.18s/it, Loss=1.0099001] Training progress: 62%|██████▏ | 620/1000 [09:43<06:56, 1.10s/it, Loss=1.0099001] Training progress: 62%|██████▏ | 620/1000 [09:51<06:56, 1.10s/it, Loss=1.0100498] Training progress: 63%|██████▎ | 630/1000 [09:51<06:19, 1.03s/it, Loss=1.0100498] Training progress: 63%|██████▎ | 630/1000 [10:01<06:19, 1.03s/it, Loss=1.0104325] Training progress: 64%|██████▍ | 640/1000 [10:01<06:01, 1.01s/it, Loss=1.0104325] Training progress: 64%|██████▍ | 640/1000 [10:10<06:01, 1.01s/it, Loss=1.0113608] Training progress: 65%|██████▌ | 650/1000 [10:10<05:38, 1.03it/s, Loss=1.0113608] Training progress: 65%|██████▌ | 650/1000 [10:19<05:38, 1.03it/s, Loss=1.0094696] Training progress: 66%|██████▌ | 660/1000 [10:19<05:19, 1.06it/s, Loss=1.0094696] Training progress: 66%|██████▌ | 660/1000 [10:27<05:19, 1.06it/s, Loss=1.0095921] Training progress: 67%|██████▋ | 670/1000 [10:27<05:04, 1.08it/s, Loss=1.0095921] Training progress: 67%|██████▋ | 670/1000 [10:36<05:04, 1.08it/s, Loss=1.0090344] Training progress: 68%|██████▊ | 680/1000 [10:36<04:49, 1.11it/s, Loss=1.0090344] Training progress: 68%|██████▊ | 680/1000 [10:45<04:49, 1.11it/s, Loss=1.0103945] Training progress: 69%|██████▉ | 690/1000 [10:45<04:35, 1.12it/s, Loss=1.0103945] Training progress: 69%|██████▉ | 690/1000 [10:54<04:35, 1.12it/s, Loss=1.0091865] Training progress: 70%|███████ | 700/1000 [10:54<04:32, 1.10it/s, Loss=1.0091865] Training progress: 70%|███████ | 700/1000 [11:02<04:32, 1.10it/s, Loss=1.0109836] Training progress: 71%|███████ | 710/1000 [11:02<04:17, 1.13it/s, Loss=1.0109836] Training progress: 71%|███████ | 710/1000 [11:11<04:17, 1.13it/s, Loss=1.0101475] Training progress: 72%|███████▏ | 720/1000 [11:11<04:08, 1.13it/s, Loss=1.0101475] Training progress: 72%|███████▏ | 720/1000 [11:20<04:08, 1.13it/s, Loss=1.0097659] Training progress: 73%|███████▎ | 730/1000 [11:20<04:01, 1.12it/s, Loss=1.0097659] Training progress: 73%|███████▎ | 730/1000 [11:29<04:01, 1.12it/s, Loss=1.0101017] Training progress: 74%|███████▍ | 740/1000 [11:29<03:51, 1.12it/s, Loss=1.0101017] Training progress: 74%|███████▍ | 740/1000 [11:37<03:51, 1.12it/s, Loss=1.0095184] Training progress: 75%|███████▌ | 750/1000 [11:37<03:37, 1.15it/s, Loss=1.0095184] Training progress: 75%|███████▌ | 750/1000 [11:47<03:37, 1.15it/s, Loss=1.0111929] Training progress: 76%|███████▌ | 760/1000 [11:47<03:33, 1.12it/s, Loss=1.0111929] Training progress: 76%|███████▌ | 760/1000 [11:55<03:33, 1.12it/s, Loss=1.0105028] Training progress: 77%|███████▋ | 770/1000 [11:55<03:21, 1.14it/s, Loss=1.0105028] Training progress: 77%|███████▋ | 770/1000 [12:04<03:21, 1.14it/s, Loss=1.0102045] Training progress: 78%|███████▊ | 780/1000 [12:04<03:10, 1.16it/s, Loss=1.0102045] Training progress: 78%|███████▊ | 780/1000 [12:12<03:10, 1.16it/s, Loss=1.0098310] Training progress: 79%|███████▉ | 790/1000 [12:12<03:01, 1.16it/s, Loss=1.0098310] Training progress: 79%|███████▉ | 790/1000 [12:22<03:01, 1.16it/s, Loss=1.0101976] test views is in : ./output/Replicate/test_six_views/800_iteration [22/12 16:29:21] [ITER 800] Eval Done! [22/12 16:29:22] videos is in : ./output/Replicate/videos/800_iteration [22/12 16:29:22] Generating Video using 240 different view points[22/12 16:29:28] [ITER 800] Video Save Done! [22/12 16:29:31] Training progress: 80%|████████ | 800/1000 [12:22<02:57, 1.12it/s, Loss=1.0101976] Training progress: 80%|████████ | 800/1000 [12:41<02:57, 1.12it/s, Loss=1.0115836] Training progress: 81%|████████ | 810/1000 [12:41<03:45, 1.19s/it, Loss=1.0115836] Training progress: 81%|████████ | 810/1000 [12:50<03:45, 1.19s/it, Loss=1.0098869] Training progress: 82%|████████▏ | 820/1000 [12:50<03:18, 1.10s/it, Loss=1.0098869] Training progress: 82%|████████▏ | 820/1000 [12:59<03:18, 1.10s/it, Loss=1.0102600] Training progress: 83%|████████▎ | 830/1000 [12:59<02:57, 1.05s/it, Loss=1.0102600] Training progress: 83%|████████▎ | 830/1000 [13:08<02:57, 1.05s/it, Loss=1.0097042] Training progress: 84%|████████▍ | 840/1000 [13:08<02:39, 1.01it/s, Loss=1.0097042] Training progress: 84%|████████▍ | 840/1000 [13:16<02:39, 1.01it/s, Loss=1.0103961] Training progress: 85%|████████▌ | 850/1000 [13:16<02:24, 1.04it/s, Loss=1.0103961] Training progress: 85%|████████▌ | 850/1000 [13:26<02:24, 1.04it/s, Loss=1.0108702] Training progress: 86%|████████▌ | 860/1000 [13:26<02:13, 1.05it/s, Loss=1.0108702] Training progress: 86%|████████▌ | 860/1000 [13:34<02:13, 1.05it/s, Loss=1.0092877] Training progress: 87%|████████▋ | 870/1000 [13:34<02:00, 1.07it/s, Loss=1.0092877] Training progress: 87%|████████▋ | 870/1000 [13:43<02:00, 1.07it/s, Loss=1.0103984] Training progress: 88%|████████▊ | 880/1000 [13:43<01:49, 1.10it/s, Loss=1.0103984] Training progress: 88%|████████▊ | 880/1000 [13:52<01:49, 1.10it/s, Loss=1.0098017] Training progress: 89%|████████▉ | 890/1000 [13:52<01:39, 1.11it/s, Loss=1.0098017] Training progress: 89%|████████▉ | 890/1000 [14:01<01:39, 1.11it/s, Loss=1.0112966] Training progress: 90%|█████████ | 900/1000 [14:01<01:31, 1.09it/s, Loss=1.0112966] Training progress: 90%|█████████ | 900/1000 [14:11<01:31, 1.09it/s, Loss=1.0114046] Training progress: 91%|█████████ | 910/1000 [14:11<01:22, 1.09it/s, Loss=1.0114046] Training progress: 91%|█████████ | 910/1000 [14:20<01:22, 1.09it/s, Loss=1.0115868] Training progress: 92%|█████████▏| 920/1000 [14:20<01:12, 1.10it/s, Loss=1.0115868] Training progress: 92%|█████████▏| 920/1000 [14:29<01:12, 1.10it/s, Loss=1.0097545] Training progress: 93%|█████████▎| 930/1000 [14:29<01:03, 1.10it/s, Loss=1.0097545] Training progress: 93%|█████████▎| 930/1000 [14:37<01:03, 1.10it/s, Loss=1.0098565] Training progress: 94%|█████████▍| 940/1000 [14:37<00:53, 1.12it/s, Loss=1.0098565] Training progress: 94%|█████████▍| 940/1000 [14:46<00:53, 1.12it/s, Loss=1.0107825] Training progress: 95%|█████████▌| 950/1000 [14:46<00:43, 1.14it/s, Loss=1.0107825] Training progress: 95%|█████████▌| 950/1000 [14:54<00:43, 1.14it/s, Loss=1.0096509] Training progress: 96%|█████████▌| 960/1000 [14:54<00:34, 1.14it/s, Loss=1.0096509] Training progress: 96%|█████████▌| 960/1000 [15:04<00:34, 1.14it/s, Loss=1.0093848] Training progress: 97%|█████████▋| 970/1000 [15:04<00:26, 1.12it/s, Loss=1.0093848] Training progress: 97%|█████████▋| 970/1000 [15:13<00:26, 1.12it/s, Loss=1.0099435] Training progress: 98%|█████████▊| 980/1000 [15:13<00:17, 1.12it/s, Loss=1.0099435] Training progress: 98%|█████████▊| 980/1000 [15:21<00:17, 1.12it/s, Loss=1.0103432] scale up theta_range to: [60, 90][22/12 16:32:28] scale up radius_range to: [4.693, 5.0] [22/12 16:32:28] scale up phi_range to: [-180, 180] [22/12 16:32:28] scale up fovy_range to: [0.18, 0.6] [22/12 16:32:28] Training progress: 99%|█████████▉| 990/1000 [15:21<00:08, 1.13it/s, Loss=1.0103432] Training progress: 99%|█████████▉| 990/1000 [15:31<00:08, 1.13it/s, Loss=1.0096740] Training progress: 100%|██████████| 1000/1000 [15:31<00:00, 1.11it/s, Loss=1.0096740] Training progress: 100%|██████████| 1000/1000 [15:31<00:00, 1.07it/s, Loss=1.0096740] test views is in : ./output/Replicate/test_six_views/1000_iteration[22/12 16:32:30] [ITER 1000] Eval Done! [22/12 16:32:31] videos is in : ./output/Replicate/videos/1000_iteration [22/12 16:32:31] Generating Video using 240 different view points[22/12 16:32:37] [ITER 1000] Video Save Done! [22/12 16:32:42] [ITER 1000] Saving Gaussians [22/12 16:32:42] Training complete.[22/12 16:32:52]
Version Details
- Version ID
fbf8e0dfef4ca0c0de45cf1afbf12c81667ee29fd79852852262aee4f167fbf5- Version Created
- December 22, 2023