文章探讨了使用Google Gemini-3-pro-image-preview模型时的技术问题。用户发现,在调用模型时传递AI生成的图片,模型无法正确识别,导致响应与实际图片严重不符。例如,模型错误描述了不存在的壁炉和书架,而实际图片是两只狗在公园。用户寻求帮助实现多轮对话和连续修改图片,避免超限。这揭示了AI模型在图像生成和识别中的局限性,为开发者和AI研究者提供了实际应用中的故障排除思路,强调了模型优化的必要性。
原文链接:Linux.do
文章探讨了使用Google Gemini-3-pro-image-preview模型时的技术问题。用户发现,在调用模型时传递AI生成的图片,模型无法正确识别,导致响应与实际图片严重不符。例如,模型错误描述了不存在的壁炉和书架,而实际图片是两只狗在公园。用户寻求帮助实现多轮对话和连续修改图片,避免超限。这揭示了AI模型在图像生成和识别中的局限性,为开发者和AI研究者提供了实际应用中的故障排除思路,强调了模型优化的必要性。
原文链接:Linux.do
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