🆕 New version available: Now with a more precise focus on the classic Adidas aesthetic.

📢 Changes and improvements in this version:

✅ Style optimization: The model has been refined to focus specifically on classic Adidas apparel and shoe designs. It now generates patterns, cuts, and details that are more faithful to the brand.

✅ Improved resolution: The model is now trained at 1024x1024, ensuring greater sharpness and precision in details.

✅ Better prompt interpretation: Thanks to an interpretive approach, the model better understands combinations of Adidas-related clothing, footwear, and styles.

✅ Greater design consistency: The architecture has been optimized to reduce visual artifacts and improve consistency between generated images.

✅ Specific trigger word: You can now use "adidas_style" to generate images with the brand's classic aesthetic. You can also try variations like:

"adidas_classic_wear" → For styles that are more authentic to the references.

"adidas_classic_sneakers" → To generate sneakers with the iconic retro feel.

⚙️ Tweaks and Fixes:

🔹 Overly generic interpretations of sportswear have been removed.

🔹 Improved support for prompts that combine clothing and accessories.

🔹 Reduced inconsistencies in sneaker generation.

💡 Tip: For best results, try combining the trigger word with terms like "retro sportswear," "track jacket," or "three stripes design."

📌 Planned Upcoming Improvements:

🔜 Expanded the dataset with more classic streetwear references.

🔜 Tweaked the generation of materials like leather and suede for sneakers.