Prediction

{
  "id": "dsestetcxnrj40cqmfwvaeqg7c",
  "model": "philz1337x/clarity-upscaler",
  "version": "dfad41707589d68ecdccd1dfa600d55a208f9310748e44bfe35b4a6291453d5e",
  "input": {
    "creativity": 0.35,
    "custom_sd_model": "",
    "downscaling": false,
    "downscaling_resolution": 768,
    "dynamic": 6,
    "handfix": "disabled",
    "image": "https://replicate.delivery/pbxt/NFCN3AMb0EBCJDJSnIZsnF6w8GZrnKumiydYrrCQG6Vcwmm2/placeholder_transparent.png",
    "lora_links": "",
    "negative_prompt": "(worst quality, low quality, normal quality:2) JuggernautNegative-neg",
    "num_inference_steps": 18,
    "output_format": "png",
    "pattern": false,
    "prompt": "masterpiece, best quality, highres, <lora:more_details:0.5> <lora:SDXLrender_v2.0:1>",
    "resemblance": 0.6,
    "scale_factor": 4,
    "scheduler": "DPM++ 3M SDE Karras",
    "sd_model": "juggernaut_reborn.safetensors [338b85bc4f]",
    "seed": 1337,
    "sharpen": 0,
    "tiling_height": 144,
    "tiling_width": 112
  },
  "logs": "Running prediction\nUpscale your image 2 times\nUpscaling with scale_factor:  2\n[Tiled Diffusion] upscaling image with 4x-UltraSharp...\n[Tiled Diffusion] ControlNet found, support is enabled.\n2025-06-24 22:05:17,386 - ControlNet - \u001b[0;32mINFO\u001b[0m - unit_separate = False, style_align = False\n2025-06-24 22:05:17,386 - ControlNet - \u001b[0;32mINFO\u001b[0m - Loading model from cache: control_v11f1e_sd15_tile\n2025-06-24 22:05:17,415 - ControlNet - \u001b[0;32mINFO\u001b[0m - Using preprocessor: tile_resample\n2025-06-24 22:05:17,415 - ControlNet - \u001b[0;32mINFO\u001b[0m - preprocessor resolution = 2048\n2025-06-24 22:05:17,511 - ControlNet - \u001b[0;32mINFO\u001b[0m - ControlNet Hooked - Time = 0.13015222549438477\nMultiDiffusion hooked into 'DPM++ 3M SDE Karras' sampler, Tile size: 144x112, Tile count: 6, Batch size: 6, Tile batches: 1 (ext: ContrlNet)\n[Tiled VAE]: the input size is tiny and unnecessary to tile.\nMultiDiffusion Sampling:   0%|          | 0/2 [00:00<?, ?it/s]\u001b[A\n  0%|          | 0/7 [00:00<?, ?it/s]\u001b[A\u001b[A\nTotal progress:   0%|          | 0/7 [00:00<?, ?it/s]\u001b[A\n 14%|█▍        | 1/7 [00:00<00:04,  1.31it/s]\u001b[A\u001b[A\nTotal progress:  29%|██▊       | 2/7 [00:00<00:01,  2.63it/s]\u001b[A\n 29%|██▊       | 2/7 [00:01<00:03,  1.34it/s]\u001b[A\u001b[A\nTotal progress:  43%|████▎     | 3/7 [00:01<00:02,  1.89it/s]\u001b[A\n 43%|████▎     | 3/7 [00:02<00:02,  1.34it/s]\u001b[A\u001b[A\nTotal progress:  57%|█████▋    | 4/7 [00:02<00:01,  1.65it/s]\u001b[A\n 57%|█████▋    | 4/7 [00:02<00:02,  1.35it/s]\u001b[A\u001b[A\nTotal progress:  71%|███████▏  | 5/7 [00:02<00:01,  1.53it/s]\u001b[A\n 71%|███████▏  | 5/7 [00:03<00:01,  1.35it/s]\u001b[A\u001b[A\nTotal progress:  86%|████████▌ | 6/7 [00:03<00:00,  1.47it/s]\u001b[A\n 86%|████████▌ | 6/7 [00:04<00:00,  1.35it/s]\u001b[A\u001b[A\n100%|██████████| 7/7 [00:05<00:00,  1.36it/s]\u001b[A\u001b[A\n100%|██████████| 7/7 [00:05<00:00,  1.35it/s]\nMultiDiffusion Sampling:   0%|          | 0/7 [00:19<?, ?it/s]\nTotal progress: 100%|██████████| 7/7 [00:04<00:00,  1.43it/s]\u001b[A[Tiled VAE]: input_size: torch.Size([1, 4, 256, 256]), tile_size: 128, padding: 11\n[Tiled VAE]: split to 2x2 = 4 tiles. Optimal tile size 128x128, original tile size 128x128\n[Tiled VAE]: Fast mode enabled, estimating group norm parameters on 128 x 128 image\n[Tiled VAE]: Executing Decoder Task Queue:   0%|          | 0/492 [00:00<?, ?it/s]\n[Tiled VAE]: Executing Decoder Task Queue:  25%|██▌       | 124/492 [00:00<00:00, 548.01it/s]\n[Tiled VAE]: Executing Decoder Task Queue:  50%|█████     | 247/492 [00:00<00:00, 601.97it/s]\n[Tiled VAE]: Executing Decoder Task Queue:  75%|███████▌  | 370/492 [00:00<00:00, 621.50it/s]\n[Tiled VAE]: Executing Decoder Task Queue: 100%|██████████| 492/492 [00:00<00:00, 642.19it/s]\n[Tiled VAE]: Done in 1.446s, max VRAM alloc 6209.335 MB\nTotal progress: 100%|██████████| 7/7 [00:06<00:00,  1.43it/s]\u001b[A\nTotal progress: 100%|██████████| 7/7 [00:06<00:00,  1.13it/s]\nUpscaling with scale_factor:  2\n[Tiled Diffusion] upscaling image with 4x-UltraSharp...\n[Tiled Diffusion] ControlNet found, support is enabled.\n2025-06-24 22:05:36,887 - ControlNet - \u001b[0;32mINFO\u001b[0m - unit_separate = False, style_align = False\n2025-06-24 22:05:36,888 - ControlNet - \u001b[0;32mINFO\u001b[0m - Loading model from cache: control_v11f1e_sd15_tile\n2025-06-24 22:05:36,959 - ControlNet - \u001b[0;32mINFO\u001b[0m - Using preprocessor: tile_resample\n2025-06-24 22:05:36,959 - ControlNet - \u001b[0;32mINFO\u001b[0m - preprocessor resolution = 4096\n2025-06-24 22:05:37,276 - ControlNet - \u001b[0;32mINFO\u001b[0m - ControlNet Hooked - Time = 0.39351892471313477\nMultiDiffusion hooked into 'DPM++ 3M SDE Karras' sampler, Tile size: 144x112, Tile count: 20, Batch size: 7, Tile batches: 3 (ext: ContrlNet)\nMultiDiffusion Sampling:   0%|          | 0/21 [00:00<?, ?it/s]\nMultiDiffusion Sampling:   0%|          | 0/2 [00:20<?, ?it/s]\n[Tiled VAE]: input_size: torch.Size([1, 3, 4096, 4096]), tile_size: 2048, padding: 32\n[Tiled VAE]: split to 2x2 = 4 tiles. Optimal tile size 2016x2016, original tile size 2048x2048\n[Tiled VAE]: Fast mode enabled, estimating group norm parameters on 2048 x 2048 image\n[Tiled VAE]: Executing Encoder Task Queue:   0%|          | 0/364 [00:00<?, ?it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:   5%|▌         | 19/364 [00:00<00:08, 40.47it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:   7%|▋         | 24/364 [00:00<00:08, 37.95it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  10%|█         | 38/364 [00:01<00:09, 34.04it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  12%|█▏        | 42/364 [00:01<00:09, 32.53it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  16%|█▌        | 57/364 [00:01<00:09, 32.90it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  17%|█▋        | 61/364 [00:01<00:09, 31.93it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  21%|██        | 76/364 [00:02<00:08, 32.64it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  22%|██▏     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Encoder Task Queue:  38%|███▊      | 138/364 [00:08<00:15, 14.48it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  38%|███▊      | 140/364 [00:08<00:15, 14.19it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  39%|███▉      | 142/364 [00:08<00:14, 15.41it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  40%|███▉      | 144/364 [00:08<00:14, 14.77it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  41%|████      | 148/364 [00:08<00:12, 16.89it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  41%|████▏     | 151/364 [00:08<00:12, 17.04it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  42%|████▏     | 154/364 [00:09<00:12, 17.17it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  44%|████▍     | 161/364 [00:09<00:09, 22.53it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  45%|████▌     | 164/364 [00:09<00:09, 21.10it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  46%|████▌     | 167/364 [00:09<00:13, 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Queue:  86%|████████▌ | 312/364 [00:13<00:01, 43.34it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  87%|████████▋ | 318/364 [00:13<00:01, 32.13it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  89%|████████▊ | 323/364 [00:13<00:01, 21.52it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  91%|█████████ | 331/364 [00:14<00:01, 27.08it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  95%|█████████▍| 344/364 [00:14<00:00, 41.18it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue:  96%|█████████▋| 351/364 [00:14<00:00, 44.80it/s]\u001b[A\n[Tiled VAE]: Executing Encoder Task Queue: 100%|██████████| 364/364 [00:14<00:00, 25.50it/s]\n[Tiled VAE]: Done in 14.970s, max VRAM alloc 8676.574 MB\n  0%|          | 0/6 [00:00<?, ?it/s]\u001b[A\nMultiDiffusion Sampling:   5%|▍         | 1/21 [00:15<05:14, 15.73s/it]\nMultiDiffusion Sampling:  10%|▉         | 2/21 [00:16<02:12,  6.98s/it]\nTotal progress:   0%|          | 0/6 [00:00<?, ?it/s]\u001b[A\n 17%|█▋        | 1/6 [00:02<00:12,  2.45s/it]\u001b[A\n 33%|███▎      | 2/6 [00:04<00:09,  2.45s/it]\u001b[A\nMultiDiffusion Sampling:  14%|█▍        | 3/21 [00:21<01:48,  6.03s/it]\nTotal progress:  33%|███▎      | 2/6 [00:02<00:04,  1.22s/it]\u001b[A\nMultiDiffusion Sampling:  19%|█▉        | 4/21 [00:22<01:07,  3.96s/it]\n 50%|█████     | 3/6 [00:07<00:07,  2.45s/it]\u001b[A\nMultiDiffusion Sampling:  24%|██▍       | 5/21 [00:23<00:50,  3.13s/it]\nTotal progress:  50%|█████     | 3/6 [00:04<00:05,  1.74s/it]\u001b[A\nMultiDiffusion Sampling:  29%|██▊       | 6/21 [00:24<00:35,  2.34s/it]\n 67%|██████▋   | 4/6 [00:09<00:04,  2.45s/it]\u001b[A\nMultiDiffusion Sampling:  33%|███▎      | 7/21 [00:26<00:29,  2.12s/it]\nTotal progress:  67%|██████▋   | 4/6 [00:07<00:04,  2.00s/it]\u001b[A\nMultiDiffusion Sampling:  38%|███▊      | 8/21 [00:27<00:22,  1.69s/it]\n 83%|████████▎ | 5/6 [00:12<00:02,  2.45s/it]\u001b[A\nMultiDiffusion Sampling:  43%|████▎     | 9/21 [00:28<00:20,  1.68s/it]\nTotal progress:  83%|████████▎ | 5/6 [00:09<00:02,  2.16s/it]\u001b[A\nMultiDiffusion Sampling:  48%|████▊     | 10/21 [00:29<00:15,  1.41s/it]\n100%|██████████| 6/6 [00:14<00:00,  2.45s/it]\u001b[A\n100%|██████████| 6/6 [00:14<00:00,  2.45s/it]\nTotal progress: 100%|██████████| 6/6 [00:12<00:00,  2.26s/it]\u001b[A[Tiled VAE]: input_size: torch.Size([1, 4, 512, 512]), tile_size: 128, padding: 11\n[Tiled VAE]: split to 4x4 = 16 tiles. Optimal tile size 128x128, original tile size 128x128\n[Tiled VAE]: Fast mode enabled, estimating group norm parameters on 128 x 128 image\n[Tiled VAE]: Executing Decoder Task Queue:   0%|          | 0/1968 [00:00<?, ?it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:   6%|▋         | 124/1968 [00:00<00:03, 548.74it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  13%|█▎        | 247/1968 [00:00<00:03, 545.40it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  19%|█▉        | 370/1968 [00:00<00:02, 545.05it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  25%|██▌       | 493/1968 [00:00<00:02, 581.54it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  31%|███▏      | 616/1968 [00:01<00:02, 567.47it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  38%|███▊      | 739/1968 [00:01<00:02, 559.06it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  44%|████▍     | 862/1968 [00:01<00:01, 554.22it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  50%|█████     | 985/1968 [00:01<00:01, 580.69it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  56%|█████▋    | 1108/1968 [00:01<00:01, 568.19it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  63%|██████▎   | 1231/1968 [00:02<00:01, 560.62it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  69%|██████▉   | 1354/1968 [00:02<00:01, 554.75it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  75%|███████▌  | 1477/1968 [00:02<00:00, 579.67it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  81%|████████▏ | 1600/1968 [00:02<00:00, 597.85it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  88%|████████▊ | 1723/1968 [00:02<00:00, 611.17it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue:  94%|█████████▍| 1846/1968 [00:03<00:00, 621.45it/s]\u001b[A\u001b[A\n[Tiled VAE]: Executing Decoder Task Queue: 100%|██████████| 1968/1968 [00:03<00:00, 589.53it/s]\n[Tiled VAE]: Done in 3.993s, max VRAM alloc 6730.210 MB\nTotal progress: 100%|██████████| 6/6 [00:16<00:00,  2.26s/it]\u001b[A\nTotal progress: 100%|██████████| 6/6 [00:16<00:00,  2.81s/it]\nPrediction took 65.24 seconds",
  "output": [
    "https://replicate.delivery/yhqm/zphqr5xF5aJhIFg3uLhMmAJP9sfmwuWlxwYNi9P4m5ltmGdKA/1338-72ab9986-5147-11f0-af34-36d41c341aaa.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2025-06-24T22:05:13.837Z",
  "started_at": "2025-06-24T22:05:13.846832Z",
  "completed_at": "2025-06-24T22:06:19.77518Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/dsestetcxnrj40cqmfwvaeqg7c/cancel",
    "get": "https://api.replicate.com/v1/predictions/dsestetcxnrj40cqmfwvaeqg7c",
    "stream": "https://stream.replicate.com/v1/files/qoxq-xuvrdxplopso45tnq6erbh2upaavufvnzy4t6jokqc6b4oqfouma",
    "web": "https://replicate.com/p/dsestetcxnrj40cqmfwvaeqg7c"
  },
  "metrics": {
    "predict_time": 65.928348097,
    "total_time": 65.93818
  }
}