hirensyd/headshots_trainer 🖼️🔢❓📝✓ → 🖼️
About
Example Output
Prompt:
"create a dynamic professional corporate headshot of hp, sharp facial features, confident smile, professional attire with navy blue suit, crisp white shirt, soft rembrandt lighting, shallow depth of field, shot with Canon EOS R5, 85mm F/1.4 lens, studio setting with subtle gray gradient background, professional color grading, high end retouching, high resolution, photorealistic quality, professional photography, sharp focus on eyes, perfect exposure, natural skin texture, cinematic color grading, 8k, hyperrealistic, award winning professional business portrait, centered composition --ar 3:4 --v 5 --s 750"
Output
Performance Metrics
12.44s
Prediction Time
12.54s
Total Time
All Input Parameters
{
"model": "dev",
"prompt": "create a dynamic professional corporate headshot of hp, sharp facial features, confident smile, professional attire with navy blue suit, crisp white shirt, soft rembrandt lighting, shallow depth of field, shot with Canon EOS R5, 85mm F/1.4 lens, studio setting with subtle gray gradient background, professional color grading, high end retouching, high resolution, photorealistic quality, professional photography, sharp focus on eyes, perfect exposure, natural skin texture, cinematic color grading, 8k, hyperrealistic, award winning professional business portrait, centered composition --ar 3:4 --v 5 --s 750",
"lora_scale": 1,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 90,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
Input Parameters
- mask
- Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- seed
- Random seed. Set for reproducible generation
- image
- Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- model
- 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
- 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
- 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)
- 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
- Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
- extra_lora
- 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
- 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
- Approximate number of megapixels for generated image
- num_outputs
- Number of outputs to generate
- aspect_ratio
- Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
- output_format
- Format of the output images
- guidance_scale
- 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
- 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
- Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
- extra_lora_scale
- 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
- 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
- Number of denoising steps. More steps can give more detailed images, but take longer.
- disable_safety_checker
- Disable safety checker for generated images.
Output Schema
Output
Example Execution Logs
Using seed: 47843 Prompt: create a dynamic professional corporate headshot of hp, sharp facial features, confident smile, professional attire with navy blue suit, crisp white shirt, soft rembrandt lighting, shallow depth of field, shot with Canon EOS R5, 85mm F/1.4 lens, studio setting with subtle gray gradient background, professional color grading, high end retouching, high resolution, photorealistic quality, professional photography, sharp focus on eyes, perfect exposure, natural skin texture, cinematic color grading, 8k, hyperrealistic, award winning professional business portrait, centered composition --ar 3:4 --v 5 --s 750 [!] txt2img mode Using dev model free=6523747336192 Downloading weights 2024-11-06T06:44:08Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmppyj0aoho/weights url=https://replicate.delivery/yhqm/XOWKgNsIJxIfXqFiM7F4fg0dtULLAh09GpKJ0VDtltiTxBuTA/trained_model.tar 2024-11-06T06:44:09Z | INFO | [ Complete ] dest=/tmp/tmppyj0aoho/weights size="172 MB" total_elapsed=1.862s url=https://replicate.delivery/yhqm/XOWKgNsIJxIfXqFiM7F4fg0dtULLAh09GpKJ0VDtltiTxBuTA/trained_model.tar Downloaded weights in 1.89s Loaded LoRAs in 2.48s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.88it/s] 7%|▋ | 2/28 [00:00<00:08, 3.21it/s] 11%|█ | 3/28 [00:00<00:08, 3.06it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.99it/s] 18%|█▊ | 5/28 [00:01<00:07, 2.95it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.93it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.91it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.91it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.90it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.90it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.89it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.89it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.89it/s] 50%|█████ | 14/28 [00:04<00:04, 2.89it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.89it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.89it/s] 61%|██████ | 17/28 [00:05<00:03, 2.89it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.89it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.89it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.89it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.89it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.89it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.89it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.89it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.89it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.89it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.89it/s] 100%|██████████| 28/28 [00:09<00:00, 2.89it/s] 100%|██████████| 28/28 [00:09<00:00, 2.91it/s]
Version Details
- Version ID
c8909c287ca9eef8c884c1993ec2b46369f319762b3513a377c7578ba86ed27f- Version Created
- November 5, 2024