• Projects 15
  • Rating 5.0
  • Rating 7 744

Budget: 20000 UAH Deadline: 20 days

I will develop a postal envelope recognition system: OCR for index/numeric fields, processing handwritten text if possible, searching for stamps in the image and counting their quantity and denomination.

Do you already have a set of real photos or scans of envelopes with correct answers for the index, number of stamps, and denominations to immediately check accuracy on shadows, tilts, handwritten text, and different types of stamps?

Budget and deadlines will be discussed in personal correspondence after reviewing examples of envelopes, image quality, and the required level of accuracy.

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  • Projects 5
  • Rating 4.9
  • Rating 756

Budget: 2000 UAH Deadline: 7 days

Hello, I worked on a license plate recognition system for parking - recognized numbers and letters with 94% accuracy, processing over 1000 images per minute.

I am curious if it is necessary to recognize indexes in all formats (5-digit, international) and which specific brands need to be identified?

I suggest we get in touch; I will provide you with free technical consultation and we can create a development plan + I will tell you about my team! ✨

  • Projects 3
  • Rating 5.0
  • Rating 543

Budget: 6000 UAH Deadline: 6 days

Hello, Dmytro!

The task of automating the recognition of postal envelopes is very interesting and fully implementable in Python using computer vision and OCR tools.

How I will implement this project:

Recognition of indices and text: For printed text, I will set up work with EasyOCR / Tesseract, and for handwritten digits (indices in special boxes or on the margins), I will implement character detection and segmentation for maximum recognition accuracy.

Detection and counting of stamps: I will use a lightweight and fast object detection model (for example, YOLO) so that the system clearly identifies the contours of the stamps on the envelope, counts their number, and classifies them by denomination based on visual features.

  • Projects 5
  • Rating 4.8
  • Rating 764

Budget: 3500 UAH Deadline: 5 days

Good day, Dmytro!

I understood the task. I will implement it in Python + EasyOCR (for handwritten text) + OpenCV:
— extracting the index from the envelope (digital and handwritten format)
— detection and classification of stamps (quantity + denomination) using YOLOv8 or CNN classifier

Please clarify: are there test photos of the envelopes? What denominations of stamps — only Ukrainian?

  • Projects -
  • Rating -
  • Rating 418

Budget: 22000 UAH Deadline: 12 days

Good day!

I can write a similar OCR system in 12 days (during this time I guarantee the full functionality of the system itself as well as all its features).
I have worked on similar projects in Python multiple times (always open to suggestions and ideas).
My portfolio already includes projects related to computer vision, image recognition, data processing, and automation using Python.
I can also offer a convenient system for recognizing indices on envelopes, counting stamps, and determining their denomination.

  • Projects 7
  • Rating 5.0
  • Rating 1 562

Budget: 1000 UAH Deadline: 10 days

Hello! I will perform OCR for envelopes: recognition of the index (including handwritten — specialized models), detection of stamps with counting quantity and denomination (computer vision + LLM verification). Python, a neat pipeline with manual verification of questionable cases. The price in the bid is conditional — negotiable.

  • Projects 20
  • Rating -
  • Rating 2 116

Budget: 5000 UAH Deadline: 3 days

Good day. I understand the task: a system that recognizes the postal code from a photo of an envelope (only numbers, sometimes handwritten) and separately counts the stamps, their quantity, and denomination.

Recognition of printed digits of the postal code is reliably solved. Handwritten digits are more complex; here, a training or fine-tuning stage of the model on your actual envelopes is needed, as the quality heavily depends on the handwriting and background. For the stamps, the logic is different: first, detection of the stamps on the envelope as objects, then classification of each by denomination and counting the quantity. For this, a labeled set of stamp samples will also be required.

I roughly see it like this: a separate module for the postal code digits, a separate one for detection and classification of stamps, with a structured result in JSON containing the postal code, a list of stamps, and the total denominations.

To assess more accurately: what volume of envelopes is planned to be processed, and are there already collected examples of photos with handwritten postal codes and various stamps for training? This largely determines how much time will be needed to achieve stable quality.

  • Projects 9
  • Rating 5.0
  • Rating 656

Budget: 700 UAH Deadline: 1 day

Good day, Dima!
Overall, the task is clear, but to provide an accurate response regarding the deadlines and price, I would like to clarify some questions that arose after analyzing your task.
Please write in private messages – we will discuss the details and your wishes.

  • Projects -
  • Rating -
  • Rating 496

Budget: 10000 UAH Deadline: 1 day

Hello!

We can create an OCR system for this task.

1. What is the volume of letters and envelopes that need to be processed?
2. Do you need the results exported to a separate system or file?


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  • Projects -
  • Rating -
  • Rating 121

Budget: 5000 UAH Deadline: 1 day

Good day. I am ready to complete this project as I have extensive experience in app development.

  • Projects 14
  • Rating 5.0
  • Rating 1 512

Budget: 9997 UAH Deadline: 5 days

Hello! I will implement it using Google Vision API or Tesseract + a custom model for handwriting: recognition of indexes and addresses on envelopes + stamp detection through YOLO with counting the quantity and denomination, all wrapped in a REST API or Telegram bot depending on how you plan to submit the photos as input. 5 days, 10,000 UAH, start after receiving a test sample of envelopes and stamps for model calibration.
I hope for cooperation!

  • Projects 4
  • Rating 5.0
  • Rating 2 025

Budget: 4500 UAH Deadline: 7 days

Hello!

I have extensive experience in Python development.
I am ready to complete the assigned task.

I suggest we discuss the details in private messages.

  • Projects 77
  • Rating 4.8
  • Rating 2 886

Budget: 2000 UAH Deadline: 2 days

Good day! I am ready to implement such a system!! Question: what file format will the index and brand be read from??

  • Projects -
  • Rating -
  • Rating 116

Budget: 700 UAH Deadline: 3 days

I will develop an OCR system in Python. For text recognition, I will use EasyOCR or Pytesseract, and for labels, I will use OpenCV for area detection + OCR for counting quantity and denomination. Handwritten text is also supported through EasyOCR.

  • Projects 55
  • Rating 5.0
  • Rating 6 585

Budget: 5000 UAH Deadline: 7 days

Good day, I would be happy to do it. Please write to me privately to discuss the details further.

  • Projects 18
  • Rating 4.4
  • Rating 2 119

Budget: 20000 UAH Deadline: 12 days

Hello. I specialize in Python development and have practical experience in computer vision projects, automation, and OCR data reading. I will implement a reliable envelope recognition system for you.

Optimal stack for the task:

- OpenCV: frame alignment, contrast, and image preprocessing.
- YOLOv8 / YOLOv11: accurate detection of the index area and finding all stamps on the envelope.
- EasyOCR / PyTorch: recognition of index numbers (even handwritten).
- Template-based classification: to determine the value of stamps (this will bypass the issue of postal stamps that usually interfere with direct text reading).

To accurately assess the scope of work (cost and development time), I need to familiarize myself with the quality of the input data. Please send 10-15 examples of real photos or scans of envelopes that the algorithm will work with in private messages.

  • Projects -
  • Rating -
  • Rating 702

Budget: 4000 UAH Deadline: 3 days

Hello! Ready to collaborate! I offer quality and fast work. Write to me.

  • Projects -
  • Rating -
  • Rating 196

Budget: 27000 UAH Deadline: 21 days

We have a practically ready similar solution for text and object recognition, we can quickly adapt it for envelopes and launch the first working phase, I am available here (:
The estimated cost for the first phase is 65,000 UAH and 21 days for a prototype with index recognition, recipient, number of stamps, and denomination.
There is a nuance - for handwritten text, it is important to see 20-50 real photos or scans, as quality and angle significantly affect accuracy.
Are there examples with the correct answers for the index, recipient, number of stamps, and denomination?
Do we only need to output the result in a table, or is an admin panel or integration with your system required?
A similar class of task example - https://business.ingello.com/vorfahr - automation with applied logic and artificial intelligence.
Another close example - https://business.ingello.com/fractal - complex process automation with artificial intelligence.
About us and the work format on the marketplace - https://systems-fl.ingello.com/ua

  • Projects 4
  • Rating 4.3
  • Rating 738

Budget: 5000 UAH Deadline: 2 days

Hello. I can do it using free libraries or with paid ones. Write to discuss.

  • Projects 10
  • Rating 5.0
  • Rating 1 756

Budget: 1000 UAH Deadline: 1 day

Hello. For the development of a text and stamp recognition system on postal envelopes, I plan to use a combination of advanced deep neural network architectures. The recognition of postal codes, including handwritten text, will be implemented using adapted models based on Convolutional Recurrent Neural Networks (CRNN) or Transformer-based models, which will ensure high accuracy and robustness to writing variability. Detection and classification of stamps by denomination will be performed using object detectors optimized for speed and reliability. I have successful experience in developing and implementing similar computer vision systems, as well as ready modules to accelerate the implementation of key components. I suggest discussing all implementation details, final budget, and timelines in private messages.

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