📄 中文摘要
在 Vets Who Code,我们使用 Imagen 4 自动生成博客文章的复古英雄图像,然而,尽管有明确的指示,AI 有时仍会在图像中添加文本。为了解决这一问题,我们构建了一个自动化评估的测试框架。生成图像的要求非常严格,包括仅使用大胆的海军蓝、红色和白色调、禁止任何文本或排版以及保持复古海报的美学。尽管 Imagen 4 功能强大,但其非确定性导致我们在生成的图像中偶尔出现随机文本,人工质量检查无法满足规模需求。通过自动化评估,我们能够有效地解决这一问题,确保生成的图像符合预期标准。
📄 English Summary
How I Built an Evaluation Pipeline for AI Image Generation
At Vets Who Code, we automated the generation of retro hero images for blog posts using Imagen 4. However, despite clear instructions, the AI occasionally inserted text into the images. To address this issue, we developed an automated evaluation test harness. The requirements for the generated images were strict, including a bold navy/red/white color palette, no text or typography, and a retro poster aesthetic. While Imagen 4 is powerful, its non-deterministic nature led to random text appearing in some images, making manual quality assurance unscalable. By implementing automated evaluation, we effectively resolved this issue and ensured that the generated images met the expected standards.
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数据源: OpenAI, Google AI, DeepMind, AWS ML Blog, HuggingFace 等