DAC_Fluxed_Style版本v1.0 (ID: 762901)

Now my photographic style in FLUX

Flux.1 Dev + DAC Style Lora https://civitai.com/models/657131/dac-style-flux-realistic-portrait-generator

Create characters more real than ever before

Key Features:

1. Distinctive and Realistic Visual Output:
   One of the standout features of DAC Fluxed Style is its ability to generate images with a distinctive and more realistic appearance compared to other Flux models. The advanced algorithms and training techniques employed result in visuals that not only captivate with their uniqueness but also exhibit a heightened sense of realism, making them ideal for both artistic and commercial applications.

2. Detail Enrichment Algorithm:
   The model incorporates a detail enrichment module that accurately captures intricate elements and fine textures. This algorithm combines super-resolution techniques with fine-tuning adjustments, allowing the generation of images with exceptional detail, particularly in traditionally challenging areas such as hair, reflective surfaces, and complex patterns.

3. Multidimensional Stylistic Adaptability:
   Unlike conventional models limited to a specific stylistic range, DAC Fluxed Style introduces multidimensional stylistic adaptability. By utilizing specially trained latent vectors, the model can emulate a wide array of artistic styles, from hyperrealism to photorealism, offering granular control over style parameters.

4. Optimized Computational Efficiency:
   The model’s design has been meticulously optimized to maximize computational efficiency without compromising output quality. It employs a neural pruning scheme and weight quantization, significantly reducing computational load, enabling deployment on mid/high-range hardware without sacrificing inference speed or image resolution.

5. Enhanced Semantic Control:
   A key innovation in DAC Fluxed Style is its enhanced semantic control system, allowing users to influence the composition and narrative of the image at a deeper level. This system integrates contextual analysis of textual inputs, enabling greater precision in translating complex descriptions into visual representations.

6. Training on Curated Dataset:
   The model has been trained on a high-quality curated dataset, my own photos, composed of thousands of labeled images to ensure diverse stylistic and thematic coverage. This enables better generalization across a wide range of creative scenarios and adaptation to different types of artistic projects.

7. Support for Conditional Generation:
   DAC Fluxed Style supports advanced conditional generation, allowing users to dictate both specific features and the contextual environment of the generated images. This conditional approach includes support for multimodal inputs, such as text and base images, which the model uses to enrich and guide the generation process.

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