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--- |
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title: All In One Translation |
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emoji: 📚 |
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colorFrom: gray |
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colorTo: green |
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sdk: gradio |
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sdk_version: 5.12.0 |
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app_file: app.py |
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pinned: false |
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short_description: Convert text/image/audio/video from src language to English |
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--- |
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**************************** |
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<p align="center"> |
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Liked the setup? Put a like on top left, it takes only 2 seconds. |
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</p> |
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# Logs |
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- 27/05/2025 - This app receieved bulk usage, in terms of data size. 63 requests with input text of size 3.3MB. The `https://detectlanguage.com/` API can only support 1MB/day. My personal API key was suspeded, making this app dysfunctional. |
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- 28/05/2025 - I have removed the need for an external API. Using `langdetect` library for the same purpose now. No limitations of usage (Theoretically). |
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**************************** |
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Replication |
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- Requirements |
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- Free API Key from https://detectlanguage.com/ for automatic language detection from text. |
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- GPU for `Whisper` model inference. It's slower in CPU. |
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- Notes |
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- `pytesseract` library (For image-to-text) is easier to install in linux machines. |
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- If you have GPU, you can go for more sophisticated image-to-text models. |
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- The image-to-text setup works best for non-decorative and normal sized fonts. |
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******* |
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The space consists of 3-4 parts: - |
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- Text translator - Input (Input Text, Target language), Output (Translated text in target language, Source language name) |
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- Image translator - Input (Image with any text, Source language, Target language), Output (Image text in source language, Image text translated to target language) |
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- Audio translator - Input (Audio in any language, Model size, Target language), Output (Transcribed original text, Transcribed text translated to target language, Original language name) |
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- Video translator - Input (Video, Model size, Target language), Output (Translated text version of the audio) [Not yet implemented] |
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******************************************************** |
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Demo |
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**Text translator** |
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- Simple `deep-translator` library usage. |
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*********** |
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**Image translator** |
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- Best works with simple fonts. Performance detoriates with decorative fonts. |
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- For now, you have to choose the language, choosing "English" can work for almost all Latin-script languages like (Spanish, Romanian etc.) |
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- Using `pytesseract` model for image-to-text conversion. It's installation is a bit complicated. [Follow this link for installation](https://stackoverflow.com/a/52231794/17820006) |
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************* |
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**Audio translator** |
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- Since I am on a free-tier space, the inference takes a lot of time (1000 seconds for 10 seconds of audio) |
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- If one has HuggingFace pro, he/she can get a GPU and get reasonable inference time. But for now, this is just a demo. |
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- If you have an OpenAPI key, you can use whisper speech-to-text model via API call. But since I don't have it, I used the whisper library method, where you have to take care of the inference hardware yourself. |
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- Here is a 10 seconds translation of the famous Russian song [Kukushka](https://youtu.be/fuPX8mjeb-E?si=RSlOLLfVnt52UUGG) |
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
