yotamwolf/minecraft-textures-sdxl 🖼️🔢📝❓✓ → 🖼️
About

Example Output
Prompt:
"In the style of TOK, red white camouflage seamless texture in minecraft style"
Output

Performance Metrics
25.17s
Prediction Time
105.72s
Total Time
All Input Parameters
{ "width": 1024, "height": 1024, "prompt": "In the style of TOK, red white camouflage seamless texture in minecraft style", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }
Input Parameters
- mask
- Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
- seed
- Random seed. Leave blank to randomize the seed
- image
- Input image for img2img or inpaint mode
- width
- Width of output image
- height
- Height of output image
- prompt
- Input prompt
- refine
- Which refine style to use
- scheduler
- scheduler
- lora_scale
- LoRA additive scale. Only applicable on trained models.
- num_outputs
- Number of images to output.
- refine_steps
- For base_image_refiner, the number of steps to refine, defaults to num_inference_steps
- guidance_scale
- Scale for classifier-free guidance
- apply_watermark
- Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.
- high_noise_frac
- For expert_ensemble_refiner, the fraction of noise to use
- negative_prompt
- Input Negative Prompt
- prompt_strength
- Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
- num_inference_steps
- Number of denoising steps
Output Schema
Output
Example Execution Logs
Using seed: 62571 Prompt: In the style of <s0><s1>, red white camouflage seamless texture in minecraft style txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<00:49, 1.02s/it] 4%|▍ | 2/50 [00:01<00:25, 1.86it/s] 6%|▌ | 3/50 [00:01<00:17, 2.61it/s] 8%|▊ | 4/50 [00:01<00:14, 3.22it/s] 10%|█ | 5/50 [00:01<00:12, 3.70it/s] 12%|█▏ | 6/50 [00:02<00:10, 4.05it/s] 14%|█▍ | 7/50 [00:02<00:09, 4.31it/s] 16%|█▌ | 8/50 [00:02<00:09, 4.51it/s] 18%|█▊ | 9/50 [00:02<00:08, 4.65it/s] 20%|██ | 10/50 [00:02<00:08, 4.75it/s] 22%|██▏ | 11/50 [00:03<00:08, 4.82it/s] 24%|██▍ | 12/50 [00:03<00:07, 4.87it/s] 26%|██▌ | 13/50 [00:03<00:07, 4.90it/s] 28%|██▊ | 14/50 [00:03<00:07, 4.94it/s] 30%|███ | 15/50 [00:03<00:07, 4.94it/s] 32%|███▏ | 16/50 [00:04<00:06, 4.96it/s] 34%|███▍ | 17/50 [00:04<00:06, 4.97it/s] 36%|███▌ | 18/50 [00:04<00:06, 4.97it/s] 38%|███▊ | 19/50 [00:04<00:06, 4.98it/s] 40%|████ | 20/50 [00:04<00:06, 4.98it/s] 42%|████▏ | 21/50 [00:05<00:05, 4.98it/s] 44%|████▍ | 22/50 [00:05<00:05, 4.98it/s] 46%|████▌ | 23/50 [00:05<00:05, 4.98it/s] 48%|████▊ | 24/50 [00:05<00:05, 4.99it/s] 50%|█████ | 25/50 [00:05<00:05, 4.99it/s] 52%|█████▏ | 26/50 [00:06<00:04, 4.99it/s] 54%|█████▍ | 27/50 [00:06<00:04, 4.98it/s] 56%|█████▌ | 28/50 [00:06<00:04, 4.98it/s] 58%|█████▊ | 29/50 [00:06<00:04, 4.98it/s] 60%|██████ | 30/50 [00:06<00:04, 4.98it/s] 62%|██████▏ | 31/50 [00:07<00:03, 4.97it/s] 64%|██████▍ | 32/50 [00:07<00:03, 4.97it/s] 66%|██████▌ | 33/50 [00:07<00:03, 4.98it/s] 68%|██████▊ | 34/50 [00:07<00:03, 4.99it/s] 70%|███████ | 35/50 [00:07<00:03, 5.00it/s] 72%|███████▏ | 36/50 [00:08<00:02, 5.00it/s] 74%|███████▍ | 37/50 [00:08<00:02, 5.01it/s] 76%|███████▌ | 38/50 [00:08<00:02, 5.01it/s] 78%|███████▊ | 39/50 [00:08<00:02, 5.01it/s] 80%|████████ | 40/50 [00:08<00:01, 5.01it/s] 82%|████████▏ | 41/50 [00:09<00:01, 5.01it/s] 84%|████████▍ | 42/50 [00:09<00:01, 5.01it/s] 86%|████████▌ | 43/50 [00:09<00:01, 5.01it/s] 88%|████████▊ | 44/50 [00:09<00:01, 5.00it/s] 90%|█████████ | 45/50 [00:09<00:01, 5.00it/s] 92%|█████████▏| 46/50 [00:10<00:00, 4.99it/s] 94%|█████████▍| 47/50 [00:10<00:00, 5.00it/s] 96%|█████████▌| 48/50 [00:10<00:00, 5.01it/s] 98%|█████████▊| 49/50 [00:10<00:00, 5.01it/s] 100%|██████████| 50/50 [00:10<00:00, 5.01it/s] 100%|██████████| 50/50 [00:10<00:00, 4.62it/s]
Version Details
- Version ID
c3154f9e8528f885109b9b74e46e53a931b27a7d38f443810319301cc96283bf
- Version Created
- August 21, 2023