OCR with AI (intelligend data processing)

Job Description:

I already have a python software source-code that converts PDF files into structured Json files.

This is done using OCR and YOLOv5.

The PDF files are supplier invoices. These invoices consist of a header, x items and a footer. There are a subset of predfinded variables (like customer_number, invoice_number, ...) to extract from pdf.

I now need the following adjustments:

1.) the tool needs to be improved. Because it does not recognize the data correctly for the positions.

2.) I need a simple graphical user interface to learn (train) more PDF files. I need a generic solution for this. Today's solution is not generic, but trained and coded for 3 different PDF formats.

3.) the learned models should learn from each other. This means that the tool should learn automatically when new PDF files are trained. If a new format comes along, it should also recognize it as best as possible without necessarily having to train it.

Now I am asking for offers to improve the tool and bring in these 3 points.

These are the requirements of the python tool that must be installed for the tool to run:

# YOLOv5 requirements

# Usage: pip install -r [login to view URL]

# bases ----------------------------------------




image slicer








torch>=1.7.0 # see [login to view URL] (recommended)



# protobuf<=3.20.1 # [login to view URL]

# logging -------------------------------------


# wallb

# clearml

# Plot ------------------------------------



# Export -------------------------------------

# coremltools>=6.0 # CoreML export

# onnx>=1.9.0 # ONNX export

# onnx-simplifier>=0.4.1 # ONNX simplifier

# nvidia-pyindex # TensorRT export

# nvidia-tensorrt # TensorRT export

# scikit-learn<=1.1.2 # CoreML quantization

# tensorflow>=2.4.1 # TF exports (-cpu, -aarch64, -macos)

# tensorflowjs>=3.9.0 # [login to view URL] export

# openvino-dev # OpenVINO export

# Deploy --------------------------------------

# tritonclient[all]~=2.24.0

# Tools --------------------------------------

ipython # interactive notebook

psutil # system utilization

thop>=0.1.1 # FLOP's computation

# mss # screenshots

# album entries>=1.0.3

# pycocotools>=2.0 # COCO mAP

# roboflow

Kemahiran: Python, Kecerdasan Buatan, Deep Learning, OCR, Machine Learning (ML)

Tentang Klien:
( 3 ulasan ) Grüt, Switzerland

ID Projek: #35389087

Dianugerahkan kepada:

(23 Ulasan)

38 pekerja bebas membida secara purata $900 untuk pekerjaan ini


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$1000 USD dalam 3 hari
(15 Ulasan)

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$1000 USD dalam 6 hari
(29 Ulasan)

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$1000 USD dalam 12 hari
(36 Ulasan)

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(8 Ulasan)

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(18 Ulasan)

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(15 Ulasan)

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(25 Ulasan)

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$750 USD dalam 7 hari
(2 Ulasan)