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# Image Classification with Gemini Pro

**[PyImageSearch](https://daily.dev/sources/pyimagesearch)** · 19 min read · 2 upvotes · 0 comments

## Summary

This post explores image classification using Gemini Pro and compares it with ChatGPT-3.5. It covers the setup of Gemini Pro, its limitations in code generation, and the need for adjustments to achieve an accuracy rate of 57%. In contrast, the code generated by ChatGPT-3.5 requires no modifications and achieves an accuracy rate of 77.29%.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://pyimagesearch.com/2024/02/19/image-classification-with-gemini-pro/>

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Tags: [#ai](https://daily.dev/tags/ai), [#bard](https://daily.dev/tags/bard), [#chatgpt](https://daily.dev/tags/chatgpt), [#computer-vision](https://daily.dev/tags/computer-vision), [#deep-learning](https://daily.dev/tags/deep-learning), [#gcp](https://daily.dev/tags/gcp), [#genai](https://daily.dev/tags/genai), [#google-gemini](https://daily.dev/tags/google-gemini), [#machine-learning](https://daily.dev/tags/machine-learning), [#mnist](https://daily.dev/tags/mnist), [#nlp](https://daily.dev/tags/nlp), [#palm](https://daily.dev/tags/palm), [#python](https://daily.dev/tags/python), [#pytorch](https://daily.dev/tags/pytorch), [#transformers](https://daily.dev/tags/transformers), [#vertex-ai](https://daily.dev/tags/vertex-ai)

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