Prediction

{
  "id": "bmqkjzlb4dtxi3plebcqg6sffu",
  "model": "zsxkib/diffbir",
  "version": "51ed1464d8bbbaca811153b051d3b09ab42f0bdeb85804ae26ba323d7a66a4ac",
  "input": {
    "background_upsampler": "DiffBIR",
    "background_upsampler_tile": 400,
    "background_upsampler_tile_stride": 400,
    "color_fix_type": "wavelet",
    "disable_preprocess_model": false,
    "face_detection_model": "retinaface_resnet50",
    "guidance_repeat": 5,
    "guidance_scale": 0,
    "guidance_space": "latent",
    "guidance_time_start": 1001,
    "guidance_time_stop": -1,
    "has_aligned": false,
    "input": "https://replicate.delivery/pbxt/JgdLVwRXXl4oaGqmF4Wdl7vOapnTlay32dE7B3UNgxSwylvQ/Audrey_Hepburn.jpg",
    "only_center_face": false,
    "reload_restoration_model": false,
    "repeat_times": 1,
    "restoration_model_type": "general_scenes",
    "seed": 231,
    "steps": 50,
    "super_resolution_factor": 2,
    "tile_size": 512,
    "tile_stride": 256,
    "tiled": false,
    "upscaling_model_type": "faces",
    "use_guidance": false
  },
  "logs": "ckptckptckpt weights/face_full_v1.ckpt\nSwitching from mode 'FULL' to 'FACE'...\nBuilding and loading 'FACE' mode model...\nControlLDM: Running in eps-prediction mode\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nDiffusionWrapper has 865.91 M params.\nmaking attention of type 'vanilla-xformers' with 512 in_channels\nbuilding MemoryEfficientAttnBlock with 512 in_channels...\nWorking with z of shape (1, 4, 32, 32) = 4096 dimensions.\nmaking attention of type 'vanilla-xformers' with 512 in_channels\nbuilding MemoryEfficientAttnBlock with 512 in_channels...\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up [LPIPS] perceptual loss: trunk [alex], v[0.1], spatial [off]\nLoading model from: /root/.pyenv/versions/3.9.18/lib/python3.9/site-packages/lpips/weights/v0.1/alex.pth\nreload swinir model from weights/general_swinir_v1.ckpt\nENABLE XFORMERS!\nModel successfully switched to 'FACE' mode.\n{'bg_tile': 400,\n'bg_tile_stride': 400,\n'bg_upsampler': 'DiffBIR',\n'ckpt': 'weights/face_full_v1.ckpt',\n'color_fix_type': 'wavelet',\n'config': 'configs/model/cldm.yaml',\n'detection_model': 'retinaface_resnet50',\n'device': 'cuda',\n'disable_preprocess_model': False,\n'g_repeat': 5,\n'g_scale': 0.0,\n'g_space': 'latent',\n'g_t_start': 1001,\n'g_t_stop': -1,\n'has_aligned': False,\n'image_size': 512,\n'input': '/tmp/tmpwg3l1z7wAudrey_Hepburn.jpg',\n'only_center_face': False,\n'output': '.',\n'reload_swinir': False,\n'repeat_times': 1,\n'seed': 231,\n'show_lq': False,\n'skip_if_exist': False,\n'sr_scale': 2,\n'steps': 50,\n'swinir_ckpt': 'weights/general_swinir_v1.ckpt',\n'tile_size': 512,\n'tile_stride': 256,\n'tiled': False,\n'use_guidance': False}\nGlobal seed set to 231\n/root/.pyenv/versions/3.9.18/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=None`.\nwarnings.warn(msg)\nDownloading: \"https://github.com/xinntao/facexlib/releases/download/v0.1.0/detection_Resnet50_Final.pth\" to /root/.pyenv/versions/3.9.18/lib/python3.9/site-packages/facexlib/weights/detection_Resnet50_Final.pth\n  0%|          | 0.00/104M [00:00<?, ?B/s]\n 37%|███▋      | 38.6M/104M [00:00<00:00, 405MB/s]\n 76%|███████▋  | 79.8M/104M [00:00<00:00, 421MB/s]\n100%|██████████| 104M/104M [00:00<00:00, 423MB/s]\nDownloading: \"https://github.com/xinntao/facexlib/releases/download/v0.2.2/parsing_parsenet.pth\" to /root/.pyenv/versions/3.9.18/lib/python3.9/site-packages/facexlib/weights/parsing_parsenet.pth\n  0%|          | 0.00/81.4M [00:00<?, ?B/s]\n 37%|███▋      | 30.4M/81.4M [00:00<00:00, 319MB/s]\n 87%|████████▋ | 70.5M/81.4M [00:00<00:00, 378MB/s]\n100%|██████████| 81.4M/81.4M [00:00<00:00, 378MB/s]\nControlLDM: Running in eps-prediction mode\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nDiffusionWrapper has 865.91 M params.\nmaking attention of type 'vanilla-xformers' with 512 in_channels\nbuilding MemoryEfficientAttnBlock with 512 in_channels...\nWorking with z of shape (1, 4, 32, 32) = 4096 dimensions.\nmaking attention of type 'vanilla-xformers' with 512 in_channels\nbuilding MemoryEfficientAttnBlock with 512 in_channels...\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\nSetting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\nSetting up [LPIPS] perceptual loss: trunk [alex], v[0.1], spatial [off]\nLoading model from: /root/.pyenv/versions/3.9.18/lib/python3.9/site-packages/lpips/weights/v0.1/alex.pth\nreload swinir model from weights/general_swinir_v1.ckpt\ntimesteps used in spaced sampler:\n[0, 20, 41, 61, 82, 102, 122, 143, 163, 183, 204, 224, 245, 265, 285, 306, 326, 347, 367, 387, 408, 428, 449, 469, 489, 510, 530, 550, 571, 591, 612, 632, 652, 673, 693, 714, 734, 754, 775, 795, 816, 836, 856, 877, 897, 917, 938, 958, 979, 999]\nSpaced Sampler:   0%|          | 0/50 [00:00<?, ?it/s]\nSpaced Sampler:   2%|▏         | 1/50 [00:00<00:10,  4.82it/s]\nSpaced Sampler:   6%|▌         | 3/50 [00:00<00:05,  8.76it/s]\nSpaced Sampler:  10%|█         | 5/50 [00:00<00:04, 10.31it/s]\nSpaced Sampler:  14%|█▍        | 7/50 [00:00<00:03, 11.08it/s]\nSpaced Sampler:  18%|█▊        | 9/50 [00:00<00:03, 11.51it/s]\nSpaced Sampler:  22%|██▏       | 11/50 [00:01<00:03, 11.78it/s]\nSpaced Sampler:  26%|██▌       | 13/50 [00:01<00:03, 11.95it/s]\nSpaced Sampler:  30%|███       | 15/50 [00:01<00:02, 12.06it/s]\nSpaced Sampler:  34%|███▍      | 17/50 [00:01<00:02, 12.11it/s]\nSpaced Sampler:  38%|███▊      | 19/50 [00:01<00:02, 12.16it/s]\nSpaced Sampler:  42%|████▏     | 21/50 [00:01<00:02, 12.20it/s]\nSpaced Sampler:  46%|████▌     | 23/50 [00:01<00:02, 12.23it/s]\nSpaced Sampler:  50%|█████     | 25/50 [00:02<00:02, 12.25it/s]\nSpaced Sampler:  54%|█████▍    | 27/50 [00:02<00:01, 12.27it/s]\nSpaced Sampler:  58%|█████▊    | 29/50 [00:02<00:01, 12.26it/s]\nSpaced Sampler:  62%|██████▏   | 31/50 [00:02<00:01, 12.25it/s]\nSpaced Sampler:  66%|██████▌   | 33/50 [00:02<00:01, 12.25it/s]\nSpaced Sampler:  70%|███████   | 35/50 [00:02<00:01, 12.26it/s]\nSpaced Sampler:  74%|███████▍  | 37/50 [00:03<00:01, 12.27it/s]\nSpaced Sampler:  78%|███████▊  | 39/50 [00:03<00:00, 12.27it/s]\nSpaced Sampler:  82%|████████▏ | 41/50 [00:03<00:00, 12.26it/s]\nSpaced Sampler:  86%|████████▌ | 43/50 [00:03<00:00, 12.24it/s]\nSpaced Sampler:  90%|█████████ | 45/50 [00:03<00:00, 12.24it/s]\nSpaced Sampler:  94%|█████████▍| 47/50 [00:03<00:00, 12.24it/s]\nSpaced Sampler:  98%|█████████▊| 49/50 [00:04<00:00, 12.25it/s]\nSpaced Sampler: 100%|██████████| 50/50 [00:04<00:00, 11.91it/s]\nupsampling the background image using DiffBIR...\ntimesteps used in spaced sampler:\n[0, 20, 41, 61, 82, 102, 122, 143, 163, 183, 204, 224, 245, 265, 285, 306, 326, 347, 367, 387, 408, 428, 449, 469, 489, 510, 530, 550, 571, 591, 612, 632, 652, 673, 693, 714, 734, 754, 775, 795, 816, 836, 856, 877, 897, 917, 938, 958, 979, 999]\nSpaced Sampler:   0%|          | 0/50 [00:00<?, ?it/s]\nSpaced Sampler:   2%|▏         | 1/50 [00:00<00:44,  1.11it/s]\nSpaced Sampler:   4%|▍         | 2/50 [00:01<00:28,  1.67it/s]\nSpaced Sampler:   6%|▌         | 3/50 [00:01<00:23,  1.98it/s]\nSpaced Sampler:   8%|▊         | 4/50 [00:02<00:21,  2.18it/s]\nSpaced Sampler:  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2.56it/s]\nSpaced Sampler:  72%|███████▏  | 36/50 [00:14<00:05,  2.55it/s]\nSpaced Sampler:  74%|███████▍  | 37/50 [00:14<00:05,  2.56it/s]\nSpaced Sampler:  76%|███████▌  | 38/50 [00:15<00:04,  2.55it/s]\nSpaced Sampler:  78%|███████▊  | 39/50 [00:15<00:04,  2.55it/s]\nSpaced Sampler:  80%|████████  | 40/50 [00:16<00:03,  2.55it/s]\nSpaced Sampler:  82%|████████▏ | 41/50 [00:16<00:03,  2.55it/s]\nSpaced Sampler:  84%|████████▍ | 42/50 [00:16<00:03,  2.55it/s]\nSpaced Sampler:  86%|████████▌ | 43/50 [00:17<00:02,  2.55it/s]\nSpaced Sampler:  88%|████████▊ | 44/50 [00:17<00:02,  2.55it/s]\nSpaced Sampler:  90%|█████████ | 45/50 [00:18<00:01,  2.55it/s]\nSpaced Sampler:  92%|█████████▏| 46/50 [00:18<00:01,  2.55it/s]\nSpaced Sampler:  94%|█████████▍| 47/50 [00:18<00:01,  2.55it/s]\nSpaced Sampler:  96%|█████████▌| 48/50 [00:19<00:00,  2.55it/s]\nSpaced Sampler:  98%|█████████▊| 49/50 [00:19<00:00,  2.55it/s]\nSpaced Sampler: 100%|██████████| 50/50 [00:20<00:00,  2.55it/s]\nSpaced Sampler: 100%|██████████| 50/50 [00:20<00:00,  2.49it/s]\nFace image tmpwg3l1z7wAudrey_Hepburn saved to ./..",
  "output": [
    "https://replicate.delivery/pbxt/3hkSakaS9qpMPxMMmfjYdr8ZLRRKiUkGwdNIlS0r5bcM7s2IA/tmpwg3l1z7wAudrey_Hepburn_00.png",
    "https://replicate.delivery/pbxt/boZvG5okpewhK6FY1YUeO2sehoy1FJoXW9IxBPifL42iZn1GB/tmpwg3l1z7wAudrey_Hepburn_00.png",
    "https://replicate.delivery/pbxt/NlSQp8BS4WLxL13eERn20OJzbMYfKpDx4usqAkywlgZY2ZtRA/tmpwg3l1z7wAudrey_Hepburn.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2023-10-12T12:49:17.922019Z",
  "started_at": "2023-10-12T12:49:19.920227Z",
  "completed_at": "2023-10-12T12:50:32.973606Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/bmqkjzlb4dtxi3plebcqg6sffu/cancel",
    "get": "https://api.replicate.com/v1/predictions/bmqkjzlb4dtxi3plebcqg6sffu"
  },
  "metrics": {
    "predict_time": 73.053379,
    "total_time": 75.051587
  }
}