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Converting handwritten (digits) information to digital format

Project description

Real-time-handwritten-digits-recognition-using-Convolutional-Neural-Network

Description

Reading handwritten information is still a difficult task for many of us, because each one of us is having a different interpretation style. As the world is moving towards digitization, converting the hand written information to a readable digital format reduces the difficulty. This approach will be beneficial for the readers as it gives a better understanding of the information. This packages deals with converting the real time handwritten digits to digital format with human level accuracy.

Sample Working

Diagram

Sample Programming

  • pip install Upender-recognizer

  • from jarvis.call import recognizer | --------------------------------------------------------------------- | Downloading... From: https://drive.google.com/uc?id=129jCE5-dWVOHIVgcw4L_g1NhGAsyCu8- To: /content/model.h5 100%|██████████| 3.09M/3.09M [00:00<00:00, 90.8MB/s]

Weights retrieved Downloading... From: https://drive.google.com/uc?id=1KAUpIPXI1W5TlZmed1LJwyZNgG1ggStR To: /content/model.json 100%|██████████| 3.53k/3.53k [00:00<00:00, 7.29MB/s]

File (json) retrieved Give image_path : /content/CamScanner 01-28-2022 10.44.26_1.jpg

Note: Image path should be modified in case of jupyter notebook, spyder etc. image_path= "/content/CamScanner 01-28-2022 10.44.26_1.jpg"

updated_path= "//content//CamScanner 01-28-2022 10.44.26_1.jpg"

Sample Output

Capture

Project details


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  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.2

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