EasyOCR Detection System for Raspberry Pi/Embedded
₹1500-12500 INR
In Progress
Posted 4 months ago
₹1500-12500 INR
Paid on delivery
Objective:
Develop an OCR-based system to extract numerical/text data from various digital screens (e.g., industrial displays, dashboards) every 30 seconds, ensuring adaptability to different layouts, fonts, and formats.
Ideally we will want to run it on a RPI 2W to a RPI 4 1GB variant.
Key Requirements:
Screen Layout Adaptability
Scrape & analyze various screen layouts from different brands to improve system flexibility.
Implement AI-based text detection (YOLO/EAST) to handle layout variations.
OCR Processing Pipeline
Frame capture every 30 seconds, ensuring clear, stable images.
Use EasyOCR/Tesseract with pre-processing (contrast enhancement, thresholding, de-noising).
Apply post-processing corrections (regex filtering, validation rules) for improved accuracy.
Optimization for Edge Devices
Ensure efficient processing on Raspberry Pi, Jetson Nano, or low-power devices.
Convert models to TensorFlow Lite/ONNX for lightweight execution.
Data Output & Integration
Structure extracted data in JSON format.
Support local storage & cloud sync options.
Challenges & Mitigations:
Challenge Solution
Varied Layouts YOU HAVE TO Scrape data FROM INTERNET on screen types + use AI-based text detection
Glare & Noise Apply pre-processing (adaptive thresholding, contrast adjustment)
OCR Errors Use post-processing corrections (regex, validation rules)
Hardware Constraints Optimize models (TensorFlow Lite/ONNX) for edge devices
Tech Stack:
Languages: Python (OpenCV, TensorFlow, PyTorch), C++ (optional)
Libraries: OpenCV, EasyOCR/Tesseract, YOLO/EAST for text detection
Deployment: Raspberry Pi 4/2W
Deliverables:
✅ Adaptive OCR Pipeline (Capture → Pre-process → Extract → Validate)
✅ AI Model for Dynamic Text Detection (if required)
✅ Optimized Deployment Package for Edge Devices
✅ Documentation & Installation Guide
Example Use Cases (We will share exact use case after NDA) :
? Industrial Equipment Screens: Read meters & control panels.
? Stock Market Displays: Extract live ticker data.
? IoT Display Panels: Capture sensor values for automation.
Hi there, I checked your requirements and guarantee you that i have relevant experience in Python,AI and data science it's gonna be done within the highest quality .
Let's contact via chat so that I can start work immediately
i have 13 years Experience in same required Skills, We already did kind of project many times, We provide support for over 150 technologies worldwide, ensuring comprehensive solutions for our clients. Our global reach allows us to connect with diverse industries and address various technological needs. We pride ourselves on delivering reliable and efficient support services. Our dedicated team is available 24/7 to assist with any technical issues. Partner with us to experience seamless and innovative technology support
With 8 years of experience in the field, I am confident that I am the best fit to complete this OCR-based system project. I have the relevant skills and have worked on similar solutions in the past.
How I will be completing this project:
- Scrape & analyze various screen layouts to improve system flexibility.
- Implement AI-based text detection (YOLO/EAST) for handling layout variations.
- Capture frames every 30 seconds and ensure clear, stable images.
- Use EasyOCR/Tesseract with pre-processing for accurate data extraction.
- Apply post-processing corrections for improved accuracy.
- Optimize for Edge Devices such as Raspberry Pi, Jetson Nano.
- Structure extracted data in JSON format and support local storage & cloud sync options.
What tech stack I will be following:
- Languages: Python (OpenCV, TensorFlow, PyTorch), C++ (optional).
- Libraries: OpenCV, EasyOCR/Tesseract, YOLO/EAST for text detection.
- Deployment: Raspberry Pi 4/2W.
I have worked with similar tech stack in the past and have successfully delivered adaptive OCR pipelines, AI models for dynamic text detection, and optimized deployment packages for edge devices.
Roadmap to complete the project:
1. Understand and analyze the screen layouts for adaptability.
2. Implement AI-based text detection for handling variations.
3. Develop OCR processing pipeline with pre/post-processing.
4. Optimize for edge devices and convert models to TensorFlow Lite/ONNX.
5. Stru
With 8 years of experience in OCR systems, I am the perfect fit to develop an OCR-based system for extracting numerical/text data from various digital screens every 30 seconds. I have the relevant skills and have worked on similar solutions in the past.
How I will be completing this project:
- Scrape & analyze different screen layouts to enhance system flexibility
- Implement AI-based text detection using YOLO/EAST
- Capture frames every 30 seconds with clear, stable images
- Utilize EasyOCR/Tesseract with pre-processing techniques
- Apply post-processing corrections for improved accuracy
- Optimize for Raspberry Pi, Jetson Nano, or low-power devices
- Structure extracted data in JSON format with local storage & cloud sync options
What tech stack I will be following:
- Languages: Python (OpenCV, TensorFlow, PyTorch), C++ (optional)
- Libraries: OpenCV, EasyOCR/Tesseract, YOLO/EAST for text detection
- Deployment: Raspberry Pi 4/2W
I have worked on similar solutions in the past and have the expertise to deliver the following:
- Adaptive OCR Pipeline
- AI Model for Dynamic Text Detection
- Optimized Deployment Package for Edge Devices
- Documentation & Installation Guide
I am confident in my ability to meet the requirements and provide a robust solution for extracting data from digital screens. Let's collaborate to bring this project to life.
With over 8 years of experience in developing robust, scalable software systems, I am confident that I can deliver a highly effective OCR detection system tailored to your requirements. My expertise lies in leveraging Python, OpenCV, TensorFlow and PyTorch among other languages and libraries - the core stack you'll require for this project. Previously, I have worked with Raspberry Pi devices and understand the hardware constraints you're facing.
My vast experience empowers me to uniquely tackle each technical challenge mentioned in the project description. For instance, my familiarity with YOLO/EAST for text detection culminates in my ability to adapt the AI-based detection to cater to various layout variations which then enables EasyOCR/Tesseract for accurate data extraction. Additionally, I excel at optimizing models for low-power devices which will be necessary for running your system on RPi's 4 1GB variant with ease.
I am particularly excited about the example use cases listed since they closely align with my domain knowledge; industrial equipment screens, stock market displays and IoT display panels are all familiar territories for me. My dedication to client satisfaction was not just a facetious statement ; )
since the other listing deals with 2w, and this being a crossplatform project, as i mentioned earlier -- we have out own versions of EasyOCR scripts that we use for digitalization of handwritten docs,
I would like to Pitch in for the script that runs on top of core linux that will be able to achieve most out of the board. We have few demo ready if you would like to have a look.
++ we are Noida based and can help in person with the project.
Professionally we are embedded system developers who dead in end to end commercial product development.
for this project we will also provide
free documentations
free 6 month of support
free installer script to replicate setup on any linux based SBC device
With a decade of experience in freelancing, I have honed my Python skills to perfection, guaranteeing quality work with the adaptability and precision required for your EasyOCR Detection System project. My familiarity with OpenCV, TensorFlow, PyTorch, EasyOCR/Tesseract, YOLO/EAST and the likes will facilitate the implementation of AI-based text detection algorithms, ensuring your system can handle the diverse screen layouts from different brands that you may encounter.
Additionally, my skill set includes pre-processing (contrast enhancement, thresholding, de-noising) and post-processing (regex filtering, validation rules) techniques which are crucial for optimizing OCR accuracy on a variety of digital screens in various lighting conditions. Since your project requires running on Raspberry Pi or low-power devices, I assure you that my experience in deploying models using TensorFlow Lite/ONNX for resource-constrained environments would be advantageous.
Lastly, I take great pride in delivering timely and budget-friendly work without compromising on quality. My 24/7 availability ensures effective communication throughout the duration of this project so that we can solve any challenge together. Let's team up to not only meet but exceed all expectations!
? **Over 80% of industrial data is locked in digital screens—are you missing out on critical insights?** Extracting real-time data efficiently can drive automation and decision-making.
? **The Challenge:** Different screen layouts, glare, and OCR errors make text extraction unreliable. **Solution?** A robust, AI-powered OCR pipeline optimized for Raspberry Pi.
? **Here’s how I’ll deliver:**
✅ **AI-powered text detection (YOLO/EAST)** for adaptive screen recognition
✅ **OCR pipeline (EasyOCR/Tesseract)** with pre/post-processing for accuracy
✅ **Optimized deployment (TensorFlow Lite/ONNX)** for Raspberry Pi efficiency
✅ **Structured JSON output** with local/cloud sync
? **Past Work:** Built OCR solutions reducing **data extraction errors by 40%**, deployed on low-power devices for **real-time monitoring**.
? Let’s unlock your screen data **accurately & efficiently**—when can we start?
Drawing on my master's degree in electrical engineering and over eight years of experience in crafting embedded systems, I believe I have the ideal skill set to tackle your OCR Detection System project for Raspberry Pi/Embedded devices. With my expertise in FPGA, VHDL, Verilog, and C programming, I'm well-versed in optimizing performance for hardware constrained environments.
My proficiency in OpenCV, TensorFlow, PyTorch and EasyOCR/Tesseract align perfectly with your tech stack. Furthermore, my prior exposure to differential processing on a vast scale - the real time data acquisition and control system for the European XFEL - will enable me to scrape, analyze and process different screen layouts innovatively.
Additionally, I noticed you need not just an engineer but a Data Scientist too. Machine Learning is not just my strength; it’s what I breathe on everyday basis! My artificial intelligence experience coupled with machine learning skills make me proficient enough to implement YOLO/EAST known for it's effectiveness in layout variability challenge. I can also bring additional value by leveraging advanced statistical techniques to validate and clean the extracted data for higher accuracy rates. Let’s collaborate on this cutting-edge project; together we can fully optimize every parameter of Python to create a mind-blowing OCR solution that suits varied client requirements!
