Thresholding in OpenCV | Codebasics

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Contents

1.1: Problem Statement, OLTP vs OLAP, ETL, Data Warehouse
1.2: Data Understanding: CSV Files
1.3: Data Understanding: Fact vs Dim table, Star vs Snowflake Schema
1.4: Data Exploration
1.5: Data Cleaning
1.6: Data Transformation
1.7: Insights Generation

2.1: Problem Statement & Tech Architecture
2.2: Database CRUD Operations
2.3: Automated Tests Setup for CRUD
2.4: Expense Management: Backend (FastAPI)
2.5: Expense Management: Logging
2.6: Streamlit Introduction
2.7: Expense Management: Frontend (Streamlit)
2.8: Analytics: Backend (FastAPI)
2.9: Analytics: Frontend (Streamlit)
2.10: README and Requirements.txt
2.11: Exercise

3.1: Technical Architecture of the Project
3.2: Installation of Necessary Libraries
3.3: Extract text from a pdf document
3.4: Thresholding in OpenCV
3.5: Regular Expressions or Regex
3.6: Regex Exercise
3.7: Python class for prescription
3.8: Code Refactoring
3.9: Unit Tests using PyTest

4.1: Write patient details class yourself
4.2: Extract name from a document
4.3: Extract remaining fields from a document
4.4: Write patient details class
4.5: Integrate doc parser classes into an extractor

5.1: FastAPI Basics
5.2: Write FastAPI server for our project
5.3: Integration With Frontend And Deployment

Instructor

Dhaval Patel

Dhaval Patel

Data Entrepreneur | YouTuber | Ex - Bloomberg, Nvidia

I have 17 years of experience in Programming and Data Science working for big tech companies like NVIDIA and Bloomberg. I also run a famous YouTube channel called Codebasics where I pursue my passion for teaching. Codebasics is one of the top channels on YouTube when it comes to data science, machine learning, data structures, etc. I firmly believe that “Anyone can code” and I use analogies, simple explanations, and step-by-step storytelling to explain difficult concepts in such a way that even a high school student can understand them easily.

Thresholding in OpenCV

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