lucataco/ip-adapter-faceid 🔢📝🖼️✓ → 🖼️

▶️ 31.4K runs 📅 Dec 2023 ⚙️ Cog 0.8.6 🔗 GitHub 📄 Paper
image-consistent-character-generation image-to-image

About

(Research only) IP-Adapter-FaceID can generate various style images conditioned on a face with only text prompts

Example Output

Prompt:

"photo of a woman in red dress in a garden"

Output

Example output

Performance Metrics

19.32s Prediction Time
19.36s Total Time
All Input Parameters
{
  "seed": 2212213399,
  "width": 1024,
  "height": 1024,
  "prompt": "photo of a woman in red dress in a garden",
  "face_image": "https://replicate.delivery/pbxt/K5DSwf3aUzIpS4srbRhNQkESybPovfXwEfjIuDMj3Dz86tDV/demo.png",
  "num_outputs": 1,
  "negative_prompt": "monochrome, lowres, bad anatomy, worst quality, low quality, blurry, multiple people",
  "num_inference_steps": 30,
  "agree_to_research_only": true
}
Input Parameters
seed Type: integer
Random seed. Leave blank to randomize the seed
width Type: integerDefault: 1024
Width of output image
height Type: integerDefault: 1024
Height of output image
prompt Type: stringDefault: photo of a woman in red dress in a garden
Input prompt
face_image (required) Type: string
Input face image
num_outputs Type: integerDefault: 1Range: 1 - 4
Number of images to output
negative_prompt Type: stringDefault: monochrome, lowres, bad anatomy, worst quality, low quality, blurry
Input Negative Prompt
num_inference_steps Type: integerDefault: 30Range: 1 - 200
Number of denoising steps
agree_to_research_only Type: booleanDefault: false
You must agree to use this model only for research. It is not for commercial use.
Output Schema

Output

Type: arrayItems Type: stringItems Format: uri

Example Execution Logs
Using seed: 2212213399
set det-size: (640, 640)
warning: det_size is already set in detection model, ignore
  0%|          | 0/30 [00:00<?, ?it/s]
  3%|▎         | 1/30 [00:00<00:16,  1.73it/s]
  7%|▋         | 2/30 [00:01<00:16,  1.73it/s]
 10%|█         | 3/30 [00:01<00:15,  1.73it/s]
 13%|█▎        | 4/30 [00:02<00:15,  1.73it/s]
 17%|█▋        | 5/30 [00:02<00:14,  1.73it/s]
 20%|██        | 6/30 [00:03<00:13,  1.72it/s]
 23%|██▎       | 7/30 [00:04<00:13,  1.72it/s]
 27%|██▋       | 8/30 [00:04<00:12,  1.72it/s]
 30%|███       | 9/30 [00:05<00:12,  1.72it/s]
 33%|███▎      | 10/30 [00:05<00:11,  1.72it/s]
 37%|███▋      | 11/30 [00:06<00:11,  1.72it/s]
 40%|████      | 12/30 [00:06<00:10,  1.72it/s]
 43%|████▎     | 13/30 [00:07<00:09,  1.72it/s]
 47%|████▋     | 14/30 [00:08<00:09,  1.72it/s]
 50%|█████     | 15/30 [00:08<00:08,  1.72it/s]
 53%|█████▎    | 16/30 [00:09<00:08,  1.72it/s]
 57%|█████▋    | 17/30 [00:09<00:07,  1.72it/s]
 60%|██████    | 18/30 [00:10<00:06,  1.72it/s]
 63%|██████▎   | 19/30 [00:11<00:06,  1.72it/s]
 67%|██████▋   | 20/30 [00:11<00:05,  1.72it/s]
 70%|███████   | 21/30 [00:12<00:05,  1.72it/s]
 73%|███████▎  | 22/30 [00:12<00:04,  1.72it/s]
 77%|███████▋  | 23/30 [00:13<00:04,  1.72it/s]
 80%|████████  | 24/30 [00:13<00:03,  1.72it/s]
 83%|████████▎ | 25/30 [00:14<00:02,  1.72it/s]
 87%|████████▋ | 26/30 [00:15<00:02,  1.72it/s]
 90%|█████████ | 27/30 [00:15<00:01,  1.72it/s]
 93%|█████████▎| 28/30 [00:16<00:01,  1.72it/s]
 97%|█████████▋| 29/30 [00:16<00:00,  1.72it/s]
100%|██████████| 30/30 [00:17<00:00,  1.72it/s]
100%|██████████| 30/30 [00:17<00:00,  1.72it/s]
Version Details
Version ID
fb81ef963e74776af72e6f380949013533d46dd5c6228a9e586c57db6303d7cd
Version Created
December 20, 2023
Run on Replicate →