qr2ai/3d_qr_code_ai_art_generator 🔢📝 → 🖼️

▶️ 450 runs 📅 Oct 2023 ⚙️ Cog 0.8.6

About

3D QR CODE AI ART GENERATOR

Example Output

Prompt:

"3D fairy-tale town, quaint village, charming, picturesque, idyllic, cobblestone streets, storybook, fable, folklore, enchanting"

Output

Performance Metrics

21.42s Prediction Time

21.40s Total Time

All Input Parameters

{
  "seed": 7649977186,
  "prompt": "3D fairy-tale town, quaint village, charming, picturesque, idyllic, cobblestone streets, storybook, fable, folklore, enchanting",
  "strength": 0.9,
  "batch_size": 1,
  "guidance_scale": 9.5,
  "negative_prompt": "ugly, disfigured, low quality, blurry, nsfw",
  "qr_code_content": "https://qr2ai.com",
  "num_inference_steps": 40,
  "controlnet_conditioning_scale": 1.3
}

Input Parameters

seed Type: integerDefault: -1: Seed
prompt (required) Type: string: The prompt to guide QR Code generation.
strength Type: numberDefault: 0.9Range: 0 - 1: Indicates how much to transform the masked portion of the reference `image`. Must be between 0 and 1.
batch_size Type: integerDefault: 1Range: 1 - 4: Batch size for this prediction
guidance_scale Type: numberDefault: 7.5Range: 0.1 - 30: Scale for classifier-free guidance
negative_prompt Type: stringDefault: ugly, disfigured, low quality, blurry, nsfw: The negative prompt to guide image generation.
qr_code_content (required) Type: string: The website/content your QR Code will point to.
num_inference_steps Type: integerDefault: 40Range: 20 - 100: Number of diffusion steps
controlnet_conditioning_scale Type: numberDefault: 1.5Range: 1 - 2: The outputs of the controlnet are multiplied by `controlnet_conditioning_scale` before they are added to the residual in the original unet.

Output Schema

Output

Type: array • Items Type: string • Items Format: uri

Example Execution Logs

Generating QR Code from content
  0%|          | 0/36 [00:00<?, ?it/s]
  3%|▎         | 1/36 [00:01<00:36,  1.03s/it]
  6%|▌         | 2/36 [00:01<00:24,  1.38it/s]
  8%|▊         | 3/36 [00:02<00:20,  1.58it/s]
 11%|█         | 4/36 [00:02<00:18,  1.71it/s]
 14%|█▍        | 5/36 [00:03<00:17,  1.78it/s]
 17%|█▋        | 6/36 [00:03<00:16,  1.83it/s]
 19%|█▉        | 7/36 [00:04<00:15,  1.86it/s]
 22%|██▏       | 8/36 [00:04<00:14,  1.89it/s]
 25%|██▌       | 9/36 [00:05<00:14,  1.89it/s]
 28%|██▊       | 10/36 [00:05<00:13,  1.91it/s]
 31%|███       | 11/36 [00:06<00:13,  1.91it/s]
 33%|███▎      | 12/36 [00:06<00:12,  1.91it/s]
 36%|███▌      | 13/36 [00:07<00:12,  1.91it/s]
 39%|███▉      | 14/36 [00:07<00:11,  1.92it/s]
 42%|████▏     | 15/36 [00:08<00:10,  1.92it/s]
 44%|████▍     | 16/36 [00:08<00:10,  1.92it/s]
 47%|████▋     | 17/36 [00:09<00:09,  1.91it/s]
 50%|█████     | 18/36 [00:09<00:09,  1.91it/s]
 53%|█████▎    | 19/36 [00:10<00:08,  1.91it/s]
 56%|█████▌    | 20/36 [00:10<00:08,  1.92it/s]
 58%|█████▊    | 21/36 [00:11<00:07,  1.91it/s]
 61%|██████    | 22/36 [00:11<00:07,  1.91it/s]
 64%|██████▍   | 23/36 [00:12<00:06,  1.91it/s]
 67%|██████▋   | 24/36 [00:13<00:06,  1.91it/s]
 69%|██████▉   | 25/36 [00:13<00:05,  1.91it/s]
 72%|███████▏  | 26/36 [00:14<00:05,  1.90it/s]
 75%|███████▌  | 27/36 [00:14<00:04,  1.90it/s]
 78%|███████▊  | 28/36 [00:15<00:04,  1.90it/s]
 81%|████████  | 29/36 [00:15<00:03,  1.90it/s]
 83%|████████▎ | 30/36 [00:16<00:03,  1.90it/s]
 86%|████████▌ | 31/36 [00:16<00:02,  1.90it/s]
 89%|████████▉ | 32/36 [00:17<00:02,  1.89it/s]
 92%|█████████▏| 33/36 [00:17<00:01,  1.89it/s]
 94%|█████████▍| 34/36 [00:18<00:01,  1.90it/s]
 97%|█████████▋| 35/36 [00:18<00:00,  1.89it/s]
100%|██████████| 36/36 [00:19<00:00,  1.89it/s]
100%|██████████| 36/36 [00:19<00:00,  1.86it/s]

Version Details

Version ID: dbd6e68583b30030f872f6aecb091b60979bc80ccfc8d2f03d575383ebbab13f
Version Created: October 3, 2023

Run on Replicate →