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You have explained a pipeline of AI algorithms for text in images: 1) Text detection, 2) OCR, 3) named entity recognition (NER). There are reams of paper on these topics. Extracting City and Country Name from Text Introducing flashgeotext: extract city and country names from text locationtagger -A Python Package for detecting location A Comparison Between ...


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I think this is a risky project. There is a lot of specialist knowledge in neural networks and NLP. Trying to learn it "on the side" in order to complete your project may be biting off more than you can chew. If you intend to write the neural network and train it yourself, you should be prepared for long sessions of training and testing variations ...


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Huggingface has a Helsinki-NLP/opus-mt-ka-en repository with a Georgian (Ka) to English (en) model. A tokenizer_config.json is available


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Having a sound understanding on language processing will help you understand all its concepts. This summarise must reads for NLP.


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I propose you try this. It's about modern Natural Language Processing, Computational Linguistics and Speech Recognition, including Embeddings methods.


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