usamaehsan/multi-controlnet-x-ip-adapter-vision-v2 🔢📝❓✓🖼️ → 🖼️
About
Example Output
Prompt:
"jungle"
Output
Performance Metrics
5.24s
Prediction Time
219.07s
Total Time
All Input Parameters
{
"eta": 0,
"prompt": "jungle",
"max_width": 512,
"scheduler": "DDIM",
"guess_mode": false,
"max_height": 512,
"num_outputs": 1,
"guidance_scale": 7,
"ip_adapter_ckpt": "ip-adapter_sd15.bin",
"negative_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
"img2img_strength": 0.5,
"ip_adapter_weight": 1,
"sorted_controlnets": "tile, inpainting, lineart",
"num_inference_steps": 20,
"disable_safety_check": false,
"film_grain_lora_weight": 0,
"tile_conditioning_scale": 1,
"add_more_detail_lora_scale": 0.5,
"detail_tweaker_lora_weight": 0,
"lineart_conditioning_scale": 1,
"scribble_conditioning_scale": 1,
"epi_noise_offset_lora_weight": 0,
"brightness_conditioning_scale": 1,
"inpainting_conditioning_scale": 1,
"color_temprature_slider_lora_weight": 0
}
Input Parameters
- eta
- Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise
- seed
- Seed
- 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
- max_width
- Max width/Resolution of image
- scheduler
- Choose a scheduler.
- guess_mode
- In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts. The `guidance_scale` between 3.0 and 5.0 is recommended.
- mask_image
- mask image for inpainting controlnet
- max_height
- Max height/Resolution of image
- tile_image
- Control image for tile controlnet
- num_outputs
- Number of images to generate
- img2img_image
- Image2image image
- lineart_image
- Control image for canny controlnet
- guidance_scale
- Scale for classifier-free guidance
- scribble_image
- Control image for scribble controlnet
- ip_adapter_ckpt
- IP Adapter checkpoint
- 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
- brightness_image
- Control image for brightness controlnet
- img2img_strength
- img2img strength, does not work when inpainting image is given, 0.1-same image, 0.99-complete destruction of image
- inpainting_image
- Control image for inpainting controlnet
- ip_adapter_image
- IP Adapter image
- ip_adapter_weight
- IP Adapter weight
- sorted_controlnets
- Comma seperated string of controlnet names, list of names: tile, inpainting, lineart,depth ,scribble , brightness /// example value: tile, inpainting, lineart
- num_inference_steps
- Steps to run denoising
- disable_safety_check
- Disable safety check. Use at your own risk!
- film_grain_lora_weight
- disabled on 0
- negative_auto_mask_text
- comma seperated list of objects you dont want to mask, AI will auto delete these objects from mask, only works if positive_auto_mask_text is given
- positive_auto_mask_text
- comma seperated list of objects for mask, AI will auto create mask of these objects, if mask text is given, mask image will not work
- tile_conditioning_scale
- Conditioning scale for tile controlnet
- add_more_detail_lora_scale
- Scale/ weight of more_details lora, more scale = more details, disabled on 0
- detail_tweaker_lora_weight
- disabled on 0
- lineart_conditioning_scale
- Conditioning scale for canny controlnet
- scribble_conditioning_scale
- Conditioning scale for scribble controlnet
- epi_noise_offset_lora_weight
- disabled on 0
- brightness_conditioning_scale
- Conditioning scale for brightness controlnet
- inpainting_conditioning_scale
- Conditioning scale for brightness controlnet
- color_temprature_slider_lora_weight
- disabled on 0
Output Schema
Output
Example Execution Logs
Time taken until build pipe: 0.00 seconds
using ip adapter:: example/cat.png
loading ip adapter
Time taken to load IP adapter model: 0.01 seconds
Time taken to load image encoder model: 0.00 seconds
Time taken to build pipe: 0.24 seconds
Time taken to apply scheduler-- : 0.00 seconds
Time taken to cuda-- : 0.00 seconds
Using seed: 25977
Time taken until ip -- : 0.00 seconds
Time taken to load ip-- : 2.16 seconds
0%| | 0/20 [00:00<?, ?it/s]
5%|▌ | 1/20 [00:00<00:04, 4.72it/s]
15%|█▌ | 3/20 [00:00<00:01, 9.93it/s]
25%|██▌ | 5/20 [00:00<00:01, 12.53it/s]
35%|███▌ | 7/20 [00:00<00:00, 14.09it/s]
45%|████▌ | 9/20 [00:00<00:00, 15.05it/s]
55%|█████▌ | 11/20 [00:00<00:00, 15.58it/s]
65%|██████▌ | 13/20 [00:00<00:00, 15.88it/s]
75%|███████▌ | 15/20 [00:01<00:00, 16.19it/s]
85%|████████▌ | 17/20 [00:01<00:00, 16.38it/s]
95%|█████████▌| 19/20 [00:01<00:00, 16.14it/s]
100%|██████████| 20/20 [00:01<00:00, 14.73it/s]
Time taken to generate image-- : 1.47 seconds
/root/.pyenv/versions/3.9.18/lib/python3.9/site-packages/peft/tuners/lora/layer.py:595: UserWarning: Already unmerged. Nothing to do.
warnings.warn("Already unmerged. Nothing to do.")
/root/.pyenv/versions/3.9.18/lib/python3.9/site-packages/peft/tuners/lora/layer.py:256: UserWarning: Already unmerged. Nothing to do.
warnings.warn("Already unmerged. Nothing to do.")
Version Details
- Version ID
7a904d90b4a018eeb8e47dd850470ef651a6f4563fa20dc8b62deb0f344cb13a- Version Created
- February 23, 2024