![]() You will get an email once the model is trained. code/train-model.py Step 8: Get Model State Once the Images have been uploaded, begin training the Model python. code/upload-training.py Step 7: Train Model Once you have dataset ready in the folder images (image files), start uploading the dataset. Note: This generates a MODEL_ID that you need for the next step Step 5: Add Model Id as Environment Variable export NANONETS_MODEL_ID=YOUR_MODEL_ID Step 6: Upload the Training DataĬollect a dataset of training images from which you would like to recognize & extract text. Get your free API Key from Step 3: Set the API key as an Environment Variable export NANONETS_API_KEY=YOUR_API_KEY_GOES_HERE Step 4: Create a New Model python. Step 1: Clone the Repo git clone cd nanonets-ocr-sample-python sudo pip install requests sudo pip install tqdm Step 2: Get your free API Key If you have an OCR software or application, here’s a detailed guide to train your own OCR models using the Nanonets API. Step 5: Test & verify data How to train your own models for an OCR software or OCR application using Nanonets API Step 3: Annotate text on the files/images Captured data can be presented as tables, line items, or any other format.įind out why Nanonets is better than other OCR APIs. Nanonets is the only text recognition OCR that presents extracted text in neatly structured & organized formats that are entirely customizable. Nanonets ’ free online OCR allows you to extract text from images accurately, at scale, and in multiple languages. ( What is OCR ? - here’s a detailed explainer on OCR. While such tools do a good job, the extracted text/data is often presented in an unstructured manner that results in a lot of post processing effort.Īn AI-driven OCR like Nanonets can extract text from images and present the extracted data in a neat, organized & structured manner. Tools like Snagit & OneNote among others, leverage basic OCR (Optical Character Recognition) capabilities to extract text from images. ( Check out Nanonets ’ free image to text tool) Image to text converters, often in-built as a sub-feature in image/document processing programs, offer a neat way to extract text from images. Most people just retype the text or data from the image but this is both time-consuming and inefficient when you have a lot of images to deal with. Extracting text from an image can be a cumbersome process.
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