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Jupyter Hub for Face and Object Detection using Python packaged by Data Science Dojo

Data Science Dojo

Jupyter Hub for Face and Object Detection using Python packaged by Data Science Dojo

Data Science Dojo

Our Jupyter Instance provides an easy-to-use environment for Face and Object Detection applications.

Data Science Dojo delivers data science education, consulting, and technical services to harvest the power of data.

Trademarks: This software listing is packaged by Data Science Dojo. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

About the offer:

Jupyter Hub for Face and Object Detection using Python gives you an effortless coding environment in the cloud with pre-installed Object And Face Detection python libraries, reducing the burden of installation and maintenance of tasks. Through this offer, a user can work on different applications of Face Detection including one-shot attendance system, selfie-segmentation, face recognition to capture criminals, and many more. Similarly, object detection can be used to count the number of vehicles running on roads etc. The heavy computations required for these applications are not performed on the user’s local machine. Instead, they are performed in the Azure cloud, which increases responsiveness and processing speed.

Who benefits from this offer:

Following can benefit from our instance:

  • Teams of developers
  • Computer Vision engineers
  • Scientific researcher groups
  • Data Scientist
  • And anyone else interested in data science tools

What is included in this offer:
  • Pre-installed Object And Face Detection libraries for python
  • Ready to go notebooks which consist of example codes through which user can get guidance for working on Object And Face Detection
  • Work with multiple notebooks at the same time
  • Kernel-backed documents enable code in any text file (Markdown, Python, etc.) to be run interactively in Jupyter kernel
  • Code consoles to run code interactively, with full support for rich output
Technical Specifications:
  • Recommended memory: 8GB RAM
  • Recommended vCPU:4 vCPUs
  • Operating System:Ubuntu 20.04

Our offer provides repositories from following sources:

  • Github repository of book Python-Image-Processing-Cookbook by author Sandipan Dey
  • Github repository of book Modern-Computer-Vision-with-PyTorch by authors V Kishore Ayyadevara, Yeshwanth Reddy
  • Github repository of book Hands-On-Image-Processing-with-Python by author Sandipan Dey
  • Github repository of book Image Processing Masterclass with Python by author Sandipan Dey

Following Authoring Tools are supported in this offer:

  • JupyterHub
  • Jupyter Lab
  • Terminal

Our instance supports following python libraries:

  • keras
  • pillow
  • mmdet
  • numpy
  • opencv-python
  • gluoncv
  • mask-rcnn-12rics
  • timm
  • labelImg
  • albumentations
  • tf-centernet
  • kornia
  • yolov5
  • testresources
  • yolo
  • mediapipe
  • face-recognition
  • tensorflow

The default port JupyterHub listens to is 8000. You can access the web interface at http://yourip:8000 using the credentials

  • username:guest
  • password:guest@123
The Jupyter Trademark is registered with the U.S. Patent & Trademark Office.
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