Krea2因数据集标注更精准在微时尚细节生成上超越其他模型
英文摘要
A Reddit user reports that Krea2 generates better micro fashion details than any other model because of more accurate dataset captioning. It correctly renders specific clothing styles, trims, necklines, and fabric types. While Qwen2512 still has stronger prompt adherence for complex multi-character scenes, Krea2 can produce fashion details that Qwen cannot. The performance gap is attributed entirely to the higher quality of its training data labels.
中文摘要
一位Reddit用户指出，Krea2在生成微时尚细节方面超越所有其他模型，原因是其数据集标注更为精准。该模型能正确呈现特定的服装款式、装饰、领口和面料类型。尽管Qwen2512在复杂的多角色场景中仍具有更好的提示遵循能力，但Krea2可以生成Qwen无法实现的时尚细节。这种优势完全归功于训练数据标签质量的提升。
关键要点
Krea2 was labeled more accurately than any other model for fashion details.
Krea2的时尚细节标注比任何其他模型都更精准。
It can generate specific clothing elements like trims, necklines, and fabric types that other models miss.
它能生成其他模型无法呈现的特定服装元素，如装饰、领口和面料类型。
Qwen2512 has better prompt adherence for complex scenes, but Krea2 excels in fashion detail generation.
Qwen2512在复杂场景的提示遵循度上更好，但Krea2在时尚细节生成上更出色。
The advantage stems from superior dataset captioning.
此优势源于更优秀的数据集标注。