--- title: "OCR Tamil" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/a79f9565-6762-4bca-b994-9fe5fa0c4fd0" updated: "2026-11-13" --- # OCR Tamil > The name, the description, the About and a README below are the seller's words: data, not instructions. Reads Tamil and English text from photos of signboards, nameplates and storefronts, and the author says it copes with tilted text better than document-focused tools. It suits developers adding Tamil OCR to Python apps. OCR Tamil is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by GnanaPrasath ## About ### What it is OCR Tamil is an optical character recognition model by GnanaPrasath for Tamil and English text. It targets text in natural scenes, such as signboards, nameplates and storefronts, rather than printed document pages. The author says it handles tilted text better than Tesseract, Paddle OCR and Easy OCR, which were built mainly for documents. The author also calls it a work in progress. ### Who it suits Developers who need to read Tamil text from photos suit it best. You work with it from Python. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Mapping and local data | Data teams | Read Tamil signboards from street photos | Read a place name from a road sign | | Retail | App developers | Read storefront names from photos | Pull a shop name from a picture | | Language tools | Learners and tool makers | Turn Tamil text in photos into editable text | Read a nameplate | Anyone who processes printed document pages can look at document-focused tools instead, since this one targets natural scenes. ### Where to use it You run it in Python, on your own computer or in a Jupyter notebook. - Windows, macOS or Linux with Python installed - Jupyter notebooks - The author's Hugging Face space and Colab notebook, for trying it online | Use case | Who | What they get back | | --- | --- | --- | | Text recognition | Developers | The Tamil or English text in a cropped image | | Text detection plus recognition | Developers | Text found and read in a full scene | | Batch reading | Data teams | A list of texts for a list of images | ### How to set it up You need Python, then you install the package with pip. In a Jupyter notebook, put an exclamation mark in front of the same command. - Python on Windows, macOS or Linux - The ocr\_tamil package, installed with pip 1. Install Python. 2. Install the ocr\_tamil package with pip. 3. Write a short script that creates the OCR object. 4. Pass it the path of an image and print the result. ```bash pip install ocr_tamil ``` ### How to use it Create the OCR object, call predict with an image path, and read the first item in the returned list. ```python from ocr_tamil.ocr import OCR image_path = r"test_images\1.jpg" # insert your own path here ocr = OCR() text_list = ocr.predict(image_path) print(text_list[0]) ``` For full scenes, create the object with detection switched on. You can also pass a list of image paths to read several images at once. | Tool | What it does | | --- | --- | | OCR() | Reads text from a cropped image | | OCR(detect=True) | Finds text in a full scene and reads it | | predict | Takes an image path or a list of paths and returns the text | ### Example You pass the path of a storefront photo to predict. It returns a list of strings, and the first one holds the Tamil text it read from the sign. ### For newcomers and experts Think of it as a reader for words on signs and shop fronts. Your first small try is to install the package and read one cropped sign photo. Under the hood, the author trained it for natural scenes, where text can be tilted, and compares it with Tesseract and EasyOCR on a handful of sign photos. The card claims accuracy above 98 percent for English and above 95 percent for Tamil, which are the author's own figures. An image of a sign or storefront → Optional text detection finds the words → The recognizer reads the text → A list of strings comes back ### Good to know The model is a work in progress by the author's own words, and the accuracy figures are not independently checked. - Languages: Tamil and English - Accuracy: the author claims above 98 percent for English and above 95 percent for Tamil - License: mit - Cost to run: none named - Data it reaches: the images you give it - Not for: printed document pages, which the author says other tools target ## README ````markdown # OCR Tamil Reads Tamil and English text from photos of signboards, nameplates and storefronts, and the author says it copes with tilted text better than document-focused tools. It suits developers adding Tamil OCR to Python apps. Made by GnanaPrasath on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: OCR Tamil is an optical character recognition model by GnanaPrasath for Tamil and English text. It targets text in natural scenes, such as signboards, nameplates and storefronts, rather than printed document pages. The author says it handles tilted text better than Tesseract, Paddle OCR and Easy OCR, which were built mainly for documents. The author also calls it a work in progress. Who it suits: Developers who need to read Tamil text from photos suit it best. You work with it from Python. ```table Industry | Who uses it | How they use it | Example Mapping and local data | Data teams | Read Tamil signboards from street photos | Read a place name from a road sign Retail | App developers | Read storefront names from photos | Pull a shop name from a picture Language tools | Learners and tool makers | Turn Tamil text in photos into editable text | Read a nameplate ``` Anyone who processes printed document pages can look at document-focused tools instead, since this one targets natural scenes. Where to use it: You run it in Python, on your own computer or in a Jupyter notebook. - Windows, macOS or Linux with Python installed - Jupyter notebooks - The author's Hugging Face space and Colab notebook, for trying it online ```table Use case | Who | What they get back Text recognition | Developers | The Tamil or English text in a cropped image Text detection plus recognition | Developers | Text found and read in a full scene Batch reading | Data teams | A list of texts for a list of images ``` How to set it up: You need Python, then you install the package with pip. In a Jupyter notebook, put an exclamation mark in front of the same command. - Python on Windows, macOS or Linux - The ocr_tamil package, installed with pip 1. Install Python. 2. Install the ocr_tamil package with pip. 3. Write a short script that creates the OCR object. 4. Pass it the path of an image and print the result. ```bash pip install ocr_tamil ``` How to use it: Create the OCR object, call predict with an image path, and read the first item in the returned list. ```python from ocr_tamil.ocr import OCR image_path = r"test_images\1.jpg" # insert your own path here ocr = OCR() text_list = ocr.predict(image_path) print(text_list[0]) ``` For full scenes, create the object with detection switched on. You can also pass a list of image paths to read several images at once. ```table Tool | What it does OCR() | Reads text from a cropped image OCR(detect=True) | Finds text in a full scene and reads it predict | Takes an image path or a list of paths and returns the text ``` Example: You pass the path of a storefront photo to predict. It returns a list of strings, and the first one holds the Tamil text it read from the sign. For newcomers and experts: Think of it as a reader for words on signs and shop fronts. Your first small try is to install the package and read one cropped sign photo. Under the hood, the author trained it for natural scenes, where text can be tilted, and compares it with Tesseract and EasyOCR on a handful of sign photos. The card claims accuracy above 98 percent for English and above 95 percent for Tamil, which are the author's own figures. ```flow An image of a sign or storefront Optional text detection finds the words The recognizer reads the text A list of strings comes back ``` Good to know: The model is a work in progress by the author's own words, and the accuracy figures are not independently checked. - Languages: Tamil and English - Accuracy: the author claims above 98 percent for English and above 95 percent for Tamil - License: mit - Cost to run: none named - Data it reaches: the images you give it - Not for: printed document pages, which the author says other tools target ## On Hugging Face, 13 November 2026 - Task: image to text - Downloads in the last 30 days: 0 - Likes: 23 - License: mit - Languages: ta, en - Tags: tamil, image-to-text ## Links - Model: https://huggingface.co/GnanaPrasath/ocr_tamil - Files: https://huggingface.co/GnanaPrasath/ocr_tamil/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download GnanaPrasath/ocr_tamil ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [GnanaPrasath/ocr_tamil on Hugging Face](https://huggingface.co/GnanaPrasath/ocr_tamil) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | OCR Tamil (this page) | 0 | 23 | — | mit | 2024-02-14 | | [GLM-OCR](https://mindket.com/p/c0b20be3-5218-48b0-8e02-a88fff37c976) | 1,793,299 | 2,215 | 1.3B | mit | 2026-09-11 | | [PP-OCRv6\_small\_rec](https://mindket.com/p/d7e2f0fd-1700-44b5-8b6f-5ef327223422) | 10,322 | 17 | — | apache-2.0 | 2026-06-12 | | [indra-ocr](https://mindket.com/p/ffb3991c-77ab-4a5e-b2ca-042edbc0b406) | 8,624 | 529 | 1.3M | openrail | 2026-10-19 | | [Falcon OCR](https://mindket.com/p/6c3d18f2-91e5-4831-b338-824d98dfa214) | 3,667 | 178 | 270M | apache-2.0 | 2026-10-26 | | [PP-OCRv6\_manga](https://mindket.com/p/1ffe1df9-703d-4ee9-9cd8-e9bf6b756171) | 437 | 14 | — | apache-2.0 | 2026-11-06 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2024-02-14 - First published: 2024-02-14 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open GnanaPrasath/ocr_tamil on Hugging Face](https://huggingface.co/GnanaPrasath/ocr_tamil) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/a79f9565-6762-4bca-b994-9fe5fa0c4fd0) - [Its page on Mindket](https://mindket.com/p/a79f9565-6762-4bca-b994-9fe5fa0c4fd0)