usamaehsan/swap-sd 🖼️🔢📝✓ → 🖼️
About
Experimental & for non-commercial use only
Example Output
Prompt:
"This is Eric Draven The Crow Movie 1994 version, Brandon Lee, realistic, 8k, the crow bird, portrait"
Output
Performance Metrics
14.58s
Prediction Time
153.10s
Total Time
All Input Parameters
{
"image": "https://replicate.delivery/pbxt/KOVEvXzae3nKcjxgRTsHrfdWN88WaLuPquXrognA336KLDuL/53894527%20%281%29.jpg",
"prompt": "This is Eric Draven The Crow Movie 1994 version, Brandon Lee, realistic, 8k, the crow bird, portrait",
"max_width": 512,
"max_height": 512,
"guidance_scale": 0.1,
"negative_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
"ip_adapter_scale": 0.8,
"num_inference_steps": 4,
"disable_safety_check": false
}
Input Parameters
- image
- Input image
- width
- Max width/Resolution of image
- height
- Max height/Resolution of image
- prompt (required)
- Prompt - using compel, use +++ to increase words weight:: doc: https://github.com/damian0815/compel/tree/main/doc || https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#attention-weighting
- swap_face
- pose_image
- pose image
- pose_scale
- Scale for open pose controlnet
- use_gfpgan
- gfpgan to enhance face
- guidance_scale
- Scale for classifier-free guidance
- negative_prompt
- Negative prompt - using compel, use +++ to increase words weight//// negative-embeddings available ///// FastNegativeV2 , boring_e621_v4 , verybadimagenegative_v1 || to use them, write their keyword in negative prompt
- ip_adapter_scale
- Scale for IP adapter
- num_inference_steps
- Steps to run denoising
- disable_safety_check
- Disable safety check. Use at your own risk!
- use_pose_image_resolution
- image will be generated in pose' width and height
Output Schema
Output
Example Execution Logs
0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:00, 4.75it/s] 100%|██████████| 4/4 [00:00<00:00, 14.18it/s] 100%|██████████| 4/4 [00:00<00:00, 12.34it/s] /root/.pyenv/versions/3.11.8/lib/python3.11/site-packages/insightface/utils/transform.py:68: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions. To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`. P = np.linalg.lstsq(X_homo, Y)[0].T # Affine matrix. 3 x 4
Version Details
- Version ID
ce62b1e250fd5be8614cb3437e6f61e4f7dd56be2cb7c959d890239b9f7b1294- Version Created
- March 3, 2024