Pinned Repositories
azure-iot-sdk-python
A Python SDK for connecting devices to Microsoft Azure IoT services
Computer-Vision-Group-Project
To develop a prototype device for visually-impaired individuals so they can navigate their route through a known or unknown environment by providing data and cues of common objects or of a known person, that surrounds such individual in their day-to-day life, by making a stand-alone device requiring minimum and transportable equipment.
DeepFake-Detection
Towards deepfake detection that actually works
EDA_Retail_DashboardinPython
Performing EDA on 'SuperStore' dataset in Jupyter Notebook and enabling the 'Dashboard View' in View Toolbar
K-Means-Clustering
LuxAI_computer_vision
LuxAI_ML_DL
ai_coding_test
Neural-Networks
Evaluating, Testing and Predicting different types of Neural Networks
Object-Detection-and-Distance-Measurement-using-Mobile-Net-SSD
Using OpenCV 4.0.1, Python 3.8 and Tensorflow 2.3, object detection and distance measurement in real-time is obtained.
Optical-Character-Recognition-and-Text-to-Speech-using-Pyttsx3
OCR using Pytesseract (Pyttsx3 and Gtts)
ArunimaB1995's Repositories
ArunimaB1995/Object-Detection-and-Distance-Measurement-using-Mobile-Net-SSD
Using OpenCV 4.0.1, Python 3.8 and Tensorflow 2.3, object detection and distance measurement in real-time is obtained.
ArunimaB1995/Computer-Vision-Group-Project
To develop a prototype device for visually-impaired individuals so they can navigate their route through a known or unknown environment by providing data and cues of common objects or of a known person, that surrounds such individual in their day-to-day life, by making a stand-alone device requiring minimum and transportable equipment.
ArunimaB1995/Neural-Networks
Evaluating, Testing and Predicting different types of Neural Networks
ArunimaB1995/Optical-Character-Recognition-and-Text-to-Speech-using-Pyttsx3
OCR using Pytesseract (Pyttsx3 and Gtts)
ArunimaB1995/Visionify_AI
use a simple object detection model (with your choice of PyTorch or Tensorflow). Implement object tracking for the objects detected from frame-to-frame. Use your choice of algorithm for object tracking (I am okay with a simple centroid based object tracking). If two people are in the frame, then count them as two different people (Person#1 and Person#2). A person going out of frame and coming back can be counted as a new object. Show a box on the object detected, and print person number on each detection.
ArunimaB1995/azure-iot-sdk-python
A Python SDK for connecting devices to Microsoft Azure IoT services
ArunimaB1995/DeepFake-Detection
Towards deepfake detection that actually works
ArunimaB1995/EDA_Retail_DashboardinPython
Performing EDA on 'SuperStore' dataset in Jupyter Notebook and enabling the 'Dashboard View' in View Toolbar
ArunimaB1995/K-Means-Clustering
ArunimaB1995/LuxAI_computer_vision
ArunimaB1995/LuxAI_ML_DL
ai_coding_test
ArunimaB1995/readme-with-video
ArunimaB1995/SimpleLinearRegression
Percentage/score of a student based in the number of study hours
ArunimaB1995/Tableau_EDA_SampleSuperstore
In this video you'll see EDA done again on SampleSuperstore.csv dataset using Tableau. Tableau is an interactive data viz software that aims to help people see and understand data. Using this software, seven visualization charts (Worksheets) have been build along with one Dashboard and one Story.
ArunimaB1995/utils