Extracting Text from Images and PDFs Using Python

In this article, we will explore how you can extract text from images and even PDF files just by using a simple prompt in Python. This technique utilizes Optical Character Recognition (OCR), which allows the computer to recognize and extract text from images. By following the step-by-step instructions outlined below, you will be able to implement this feature in your own projects.

Required Libraries and Setup

Before we delve into the process, let's make sure we have all the necessary libraries installed. One library that we will be using is X AI, which provides OCR capabilities. You can find the installation requirements in the requirements.txt file, which I have provided for your convenience. Make sure you have these libraries installed before proceeding.

Steps to Extract Text from Images

Now let's dive into the steps to extract text from images using Python:

1. Prepare the Images: To begin, we need some sample images to work with. You can use any image or even a PDF file. In this demonstration, I will be using a few images sourced from TechCrunch as examples.

2. Upload the Images: Once we have our images ready, we can upload them to a specified folder. This can be done manually or using the windzip library, which allows us to upload multiple files simultaneously. By uploading the images, we save valuable time during the extraction process.

3. Setting up the Code Interpreter: Open the code interpreter and initialize the system prompts. These prompts define the context, occupation, and experience level. Feel free to customize these prompts to suit your needs.

4. Prompt the Extraction of Text: Set up the prompt that requests the extraction of text from the uploaded images. The prompt should instruct the computer to use OCR to extract text from the images and write a summary of the extracted text to a file named summary.txt. The prompt can be written as follows:

   I will be uploading images in a zip file. Your task is to extract text from the images using OCR. Write a summary of the extracted text and save it to a file named summary.txt.
   

5. Extract Text Using OCR: With the prompt in place, we can now execute the code. The code will utilize OCR to extract the text from the uploaded images. You can find the code implementation here. This code will loop through each image, extract the text, and display the extracted text for validation.

6. Save the Summary: Once the text has been extracted, a summary will be generated. However, in this particular example, the library utilized for summarization may not be optimal. Nonetheless, the extracted text can be saved to a file named summary.txt.

Results and Conclusion

After following the aforementioned steps, you should have successfully extracted text from the uploaded images. While this process serves as a basic demonstration, it showcases the powerful capabilities of OCR and its potential applications. By playing around with this technique, you can discover various use cases and harness its potential in your own projects.

If you would like to try this out yourself, you can find all the necessary prompts and resources on my website. The link is provided in the description below. Make sure to bookmark the page, as I will be uploading more cool prompts and resources in the future.

In conclusion, extracting text from images and PDFs using Python and OCR is a fascinating tool to explore. It opens up possibilities for automating data extraction, enhancing data analysis, and improving productivity in various domains. I hope you found this article helpful, and I look forward to sharing more exciting techniques with you in the future.