SDS | FILM

Main model training film photography , computational photography There are two major categories, which deeply fine-tune the image of Asians. Add some popular film models while optimizing core data . Rate images for quality

Various low-quality images are introduced to extract negative features and enhance image quality control capabilities.

Based on LEOSAM FilmGirl Ultra All usage rules also follow the plan of the higher-level model, In Israel Spin-Diffusion is more difficult to train on the base model than chill. It has been bombed four or five, but it is easier to get closer to the target effect with less interference. The model is more difficult to use than the chill system

, and requires more thorough hints and descriptions.

The core data has been slightly expanded as XL_V4

. For basic raw image magnification parameters, see FilmGirl Ultra: Clip skip: 1- 2 CFG scale: 6-9 Sampler: restart/DPM++ 2M Karras base resolution:

(640x768)/(512*768)

The following are functional hints to choose from

: Film : Film photography

Some film models: Fuji C100 shooting, Fuji C200 shooting, Kodak 400 shooting, Kodak Gold 200 shooting, Nolan 5219

Shooting

Computational Photography: Computational

Photography Picture Quality Review

Level: Mobile phone image quality, Landline image quality, Pager image quality

(image quality decreasing in sequence: mobile image quality, landline image quality, pager image quality) Negative tips from training:

overexposed background, poor lighting, overexposed areas, reflective lighting, low resolution, potential compression artifact (I tested this part and doesn't interfere too much with the picture) usage suggestions:

When using a film, enter Film photography+any film (or no film name)

Negative tips for using training and worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, optional plus computational

Photography, mobile phone image quality, Landline image quality, and Pager image quality completely embedding negative

computational photography categories may cause the risk of excessive sharpening. At the same time, since the data subject is still film, it is generally a film

effect by default without adding specific reminders.

When using calculated photography (that is, mobile image quality), enter computational photography+any image quality rating

Negative don't include negative tips from training, because these are also characteristics of computational photography.

RC version. After continuing to expand some data, I will retrain the official version. I expect to add RAW format feature prompts to increase playability.

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