Skip to main content

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...

Weights retrieved

Downloading...

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.

Example: 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


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Upender_recognizer-0.0.11.tar.gz (4.1 kB view details)

Uploaded Source

Built Distribution

Upender_recognizer-0.0.11-py3-none-any.whl (4.4 kB view details)

Uploaded Python 3

File details

Details for the file Upender_recognizer-0.0.11.tar.gz.

File metadata

  • Download URL: Upender_recognizer-0.0.11.tar.gz
  • Upload date:
  • Size: 4.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • 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

File hashes

Hashes for Upender_recognizer-0.0.11.tar.gz
Algorithm Hash digest
SHA256 3366f7ef38716937453fb6f92dfa83d777c8fba1152906004ac95a2bee7046d1
MD5 9ea8009d830eb6d641ee24b70e834d44
BLAKE2b-256 2eb7cb6ba5e791e48eb31320c65d0662be9dbfa3c0a780b6305e45710e9fca23

See more details on using hashes here.

File details

Details for the file Upender_recognizer-0.0.11-py3-none-any.whl.

File metadata

  • Download URL: Upender_recognizer-0.0.11-py3-none-any.whl
  • Upload date:
  • Size: 4.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • 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

File hashes

Hashes for Upender_recognizer-0.0.11-py3-none-any.whl
Algorithm Hash digest
SHA256 1eb8deccdad3bca4eb45dcf0d513c4b9cf0246e6978af52cbb5a8f975f3339b1
MD5 f76a2122db22945e57d1be5e93e7427e
BLAKE2b-256 bd29fb409aeb498be6b620c6ae9c56d90efe3de41cd21fafdbe9255149645730

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page