batchbinary/flux-qfaces 🖼️🔢❓📝✓ → 🖼️

▶️ 3.6K runs 📅 Nov 2024 ⚙️ Cog 0.11.1

About

Flux trained on QFACES of High quality facial textures of diverse people, age, ethnicity. Mainly used for image to image (img2img) enhancement. See Readme for ideas & settings.

Example Output

Prompt:

"photo, high resolution, face, high quality, QFACES, photograph, skin, hair, detailed, maximum definition, 4k, highres,"

Output

Performance Metrics

9.26s Prediction Time

9.47s Total Time

All Input Parameters

{
  "seed": 42,
  "image": "https://replicate.delivery/pbxt/MFoN60GJkZUE5qH6bejQ3yQBG2pXHIIT6nmIF9ObWmCkYEFu/test-A4-CF-thenCR1.png",
  "model": "dev",
  "width": 1440,
  "height": 1440,
  "prompt": "photo, high resolution, face, high quality, QFACES, photograph, skin, hair, detailed, maximum definition, 4k, highres,",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "custom",
  "output_format": "png",
  "guidance_scale": 3,
  "output_quality": 80,
  "prompt_strength": 0.4,
  "extra_lora_scale": 1,
  "num_inference_steps": 50
}

Input Parameters

mask Type: string: Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
seed Type: integer: Random seed. Set for reproducible generation
image Type: string: Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
model Default: dev: Which model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.
width Type: integerRange: 256 - 1440: Width of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
height Type: integerRange: 256 - 1440: Height of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
prompt (required) Type: string: Prompt for generated image. If you include the `trigger_word` used in the training process you are more likely to activate the trained object, style, or concept in the resulting image.
go_fast Type: booleanDefault: false: Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
extra_lora Type: string: Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
lora_scale Type: numberDefault: 1Range: -1 - 3: Determines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
megapixels Default: 1: Approximate number of megapixels for generated image
num_outputs Type: integerDefault: 1Range: 1 - 4: Number of outputs to generate
aspect_ratio Default: 1:1: Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
output_format Default: webp: Format of the output images
guidance_scale Type: numberDefault: 3Range: 0 - 10: Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5
output_quality Type: integerDefault: 80Range: 0 - 100: Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
prompt_strength Type: numberDefault: 0.8Range: 0 - 1: Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
extra_lora_scale Type: numberDefault: 1Range: -1 - 3: Determines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
replicate_weights Type: string: Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
num_inference_steps Type: integerDefault: 28Range: 1 - 50: Number of denoising steps. More steps can give more detailed images, but take longer.
disable_safety_checker Type: booleanDefault: false: Disable safety checker for generated images.

Output Schema

Output

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

Example Execution Logs

2025-01-02 23:27:53.016 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-02 23:27:53.017 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  96%|█████████▌| 292/304 [00:00<00:00, 2913.15it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2834.08it/s]
2025-01-02 23:27:53.124 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-02 23:27:53.125 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  50%|█████     | 153/304 [00:00<00:00, 1520.65it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 1768.12it/s]
2025-01-02 23:27:53.297 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.28s
2025-01-02 23:27:53.298 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/11c8b9548dd3adca
2025-01-02 23:27:53.418 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2025-01-02 23:27:53.418 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-02 23:27:53.418 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  91%|█████████▏| 278/304 [00:00<00:00, 2777.94it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2754.48it/s]
2025-01-02 23:27:53.529 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s
Using seed: 42
Image detected - setting to img2img mode
Input image size: 1536x1800
Scaling image down to 1228x1440
Input image size set to: 1232x1440
0it [00:00, ?it/s]
1it [00:00,  4.64it/s]
2it [00:00,  3.25it/s]
3it [00:00,  2.93it/s]
4it [00:01,  2.81it/s]
5it [00:01,  2.76it/s]
6it [00:02,  2.71it/s]
7it [00:02,  2.70it/s]
8it [00:02,  2.69it/s]
9it [00:03,  2.67it/s]
10it [00:03,  2.67it/s]
11it [00:03,  2.66it/s]
12it [00:04,  2.66it/s]
13it [00:04,  2.66it/s]
14it [00:05,  2.66it/s]
15it [00:05,  2.65it/s]
16it [00:05,  2.65it/s]
17it [00:06,  2.64it/s]
18it [00:06,  2.65it/s]
19it [00:07,  2.65it/s]
20it [00:07,  2.65it/s]
20it [00:07,  2.71it/s]
Total safe images: 1 out of 1

Version Details

Version ID: 4d1d2ea165dffc2d84792d350e9819e3eeb03dc6ceaffcd9c859bbc2d7301f7e
Version Created: January 2, 2025

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