kjw488/sdxl-demo-ai-interior 🖼️🔢📝❓✓ → 🖼️

▶️ 1.1K runs 📅 Mar 2024 ⚙️ Cog 0.8.6
image-inpainting image-to-image interior-design

About

Example Output

Prompt:

"Create a room in the cozy with the type room and the following furniture: chair, lamp"

Output

Example outputExample outputExample outputExample output

Performance Metrics

17.01s Prediction Time
17.51s Total Time
All Input Parameters 
{
  "image": "https://replicate.delivery/pbxt/KcjLG8lGt7w7cd8t8r0kivnE3i0jjEIr2djxcma2jqcuNodZ/CompressJPEG.online_512x512_image-2.jpg",
  "width": 512,
  "height": 512,
  "prompt": "Create a room in the cozy with the type room and the following furniture: chair, lamp",
  "refine": "base_image_refiner",
  "scheduler": "KarrasDPM",
  "lora_scale": 1,
  "num_outputs": 4,
  "guidance_scale": 7.5,
  "apply_watermark": true,
  "high_noise_frac": 0.8,
  "negative_prompt": "",
  "prompt_strength": 0.85,
  "num_inference_steps": 50
}
Input Parameters
mask Type: string
Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
seed Type: integer
Random seed. Leave blank to randomize the seed
image Type: string
Input image for img2img or inpaint mode
width Type: integerDefault: 1024
Width of output image
height Type: integerDefault: 1024
Height of output image
prompt Type: stringDefault: An astronaut riding a rainbow unicorn
Input prompt
refine Default: no_refiner
Which refine style to use
scheduler Default: K_EULER
scheduler
lora_scale Type: numberDefault: 0.6Range: 0 - 1
LoRA additive scale. Only applicable on trained models.
num_outputs Type: integerDefault: 1Range: 1 - 4
Number of images to output.
refine_steps Type: integer
For base_image_refiner, the number of steps to refine, defaults to num_inference_steps
guidance_scale Type: numberDefault: 7.5Range: 1 - 50
Scale for classifier-free guidance
apply_watermark Type: booleanDefault: true
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 Type: numberDefault: 0.8Range: 0 - 1
For expert_ensemble_refiner, the fraction of noise to use
negative_prompt Type: stringDefault:
Input Negative Prompt
prompt_strength Type: numberDefault: 0.8Range: 0 - 1
Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
replicate_weights Type: string
Replicate LoRA weights to use. Leave blank to use the default weights.
num_inference_steps Type: integerDefault: 50Range: 1 - 500
Number of denoising steps
disable_safety_checker Type: booleanDefault: false
Disable safety checker for generated images. This feature is only available through the API. See https://replicate.com/docs/how-does-replicate-work#safety
Output Schema

Output

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

Example Execution Logs 
Using seed: 35090
Ensuring enough disk space...
Free disk space: 1700165476352
Downloading weights: https://replicate.delivery/pbxt/r8nhsByEHhKyMVCN2qk8u9uPfkuOHAXLDBjraR8RErpf3ciSA/trained_model.tar
2024-03-24T04:58:11Z | INFO  | [ Initiating ] dest=/src/weights-cache/818f78e8d0228613 minimum_chunk_size=150M url=https://replicate.delivery/pbxt/r8nhsByEHhKyMVCN2qk8u9uPfkuOHAXLDBjraR8RErpf3ciSA/trained_model.tar
2024-03-24T04:58:11Z | INFO  | [ Complete ] dest=/src/weights-cache/818f78e8d0228613 size="186 MB" total_elapsed=0.640s url=https://replicate.delivery/pbxt/r8nhsByEHhKyMVCN2qk8u9uPfkuOHAXLDBjraR8RErpf3ciSA/trained_model.tar
b''
Downloaded weights in 0.7716066837310791 seconds
Loading fine-tuned model
Does not have Unet. assume we are using LoRA
Loading Unet LoRA
Prompt: Create a room in the cozy with the type room and the following furniture: chair, lamp
img2img mode
  0%|          | 0/42 [00:00<?, ?it/s]
  2%|▏         | 1/42 [00:00<00:10,  3.98it/s]
  5%|▍         | 2/42 [00:00<00:10,  3.87it/s]
  7%|▋         | 3/42 [00:00<00:09,  3.91it/s]
 10%|▉         | 4/42 [00:01<00:09,  3.92it/s]
 12%|█▏        | 5/42 [00:01<00:09,  3.92it/s]
 14%|█▍        | 6/42 [00:01<00:09,  3.93it/s]
 17%|█▋        | 7/42 [00:01<00:08,  3.93it/s]
 19%|█▉        | 8/42 [00:02<00:08,  3.93it/s]
 21%|██▏       | 9/42 [00:02<00:08,  3.93it/s]
 24%|██▍       | 10/42 [00:02<00:08,  3.93it/s]
 26%|██▌       | 11/42 [00:02<00:07,  3.93it/s]
 29%|██▊       | 12/42 [00:03<00:07,  3.93it/s]
 31%|███       | 13/42 [00:03<00:07,  3.93it/s]
 33%|███▎      | 14/42 [00:03<00:07,  3.94it/s]
 36%|███▌      | 15/42 [00:03<00:06,  3.95it/s]
 38%|███▊      | 16/42 [00:04<00:06,  3.95it/s]
 40%|████      | 17/42 [00:04<00:06,  3.95it/s]
 43%|████▎     | 18/42 [00:04<00:06,  3.95it/s]
 45%|████▌     | 19/42 [00:04<00:05,  3.95it/s]
 48%|████▊     | 20/42 [00:05<00:05,  3.95it/s]
 50%|█████     | 21/42 [00:05<00:05,  3.95it/s]
 52%|█████▏    | 22/42 [00:05<00:05,  3.95it/s]
 55%|█████▍    | 23/42 [00:05<00:04,  3.95it/s]
 57%|█████▋    | 24/42 [00:06<00:04,  3.95it/s]
 60%|█████▉    | 25/42 [00:06<00:04,  3.95it/s]
 62%|██████▏   | 26/42 [00:06<00:04,  3.95it/s]
 64%|██████▍   | 27/42 [00:06<00:03,  3.95it/s]
 67%|██████▋   | 28/42 [00:07<00:03,  3.95it/s]
 69%|██████▉   | 29/42 [00:07<00:03,  3.95it/s]
 71%|███████▏  | 30/42 [00:07<00:03,  3.95it/s]
 74%|███████▍  | 31/42 [00:07<00:02,  3.95it/s]
 76%|███████▌  | 32/42 [00:08<00:02,  3.95it/s]
 79%|███████▊  | 33/42 [00:08<00:02,  3.95it/s]
 81%|████████  | 34/42 [00:08<00:02,  3.95it/s]
 83%|████████▎ | 35/42 [00:08<00:01,  3.94it/s]
 86%|████████▌ | 36/42 [00:09<00:01,  3.94it/s]
 88%|████████▊ | 37/42 [00:09<00:01,  3.94it/s]
 90%|█████████ | 38/42 [00:09<00:01,  3.94it/s]
 93%|█████████▎| 39/42 [00:09<00:00,  3.95it/s]
 95%|█████████▌| 40/42 [00:10<00:00,  3.94it/s]
98%|█████████▊| 41/42 [00:10<00:00,  3.94it/s]
98%|█████████▊| 41/42 [00:10<00:00,  3.94it/s]
  0%|          | 0/15 [00:00<?, ?it/s]
  7%|▋         | 1/15 [00:00<00:03,  4.64it/s]
 13%|█▎        | 2/15 [00:00<00:02,  4.75it/s]
 20%|██        | 3/15 [00:00<00:02,  4.78it/s]
 27%|██▋       | 4/15 [00:00<00:02,  4.80it/s]
 33%|███▎      | 5/15 [00:01<00:02,  4.80it/s]
 40%|████      | 6/15 [00:01<00:01,  4.81it/s]
 47%|████▋     | 7/15 [00:01<00:01,  4.81it/s]
 53%|█████▎    | 8/15 [00:01<00:01,  4.81it/s]
 60%|██████    | 9/15 [00:01<00:01,  4.81it/s]
 67%|██████▋   | 10/15 [00:02<00:01,  4.81it/s]
 73%|███████▎  | 11/15 [00:02<00:00,  4.80it/s]
 80%|████████  | 12/15 [00:02<00:00,  4.81it/s]
 87%|████████▋ | 13/15 [00:02<00:00,  4.81it/s]
 93%|█████████▎| 14/15 [00:02<00:00,  4.82it/s]
100%|██████████| 15/15 [00:03<00:00,  4.82it/s]
100%|██████████| 15/15 [00:03<00:00,  4.80it/s]
Version Details
Version ID
8859e91ed00a9fc819f53b36b917b5a23506173c8a96f9a7c7b604ad514b91fc
Version Created
March 21, 2024
Run on Replicate →