1. Text Detection and Extraction using OpenCV and OCR.
OpenCV (Open source computer vision) is a library mainly aimed at real-time computer vision, in python it helps to process an image and apply various functions e.g. pixel manipulations, object detection, etc. For this project using contours to detect the text in an image and save it to a text file.
Requirements
conda install -c conda-forge opencv
conda install -c conda-forge pytesseract
Coding
I will use the following sample image:
import cv2
import numpy as np
import pytesseract as pyt
image = cv2.imread('The_Zen_of_Python.jpeg')
# image convertion to grey scale
image_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
image_gray, binary_image = cv2.threshold(image_gray, 128,255, cv2.THRESH_BINARY)
image_gray =cv2.bitwise_not(binary_image)
kernel = np.ones((2,1), np.uint8)
image = cv2.erode(image_gray, kernel,iterations = 1)
image = cv2.dilate(image_gray, kernel,iterations = 1)
The next code will convert the image into a string and print the string as text.
# image conversion into string
image_text = pyt.image_to_string(image)
print(image_text)
Check out the video of the project above -Project video
2. Stock Price Visualisation using Yahoo's yfinance .
yfinance is an open source library developed by Ran Aroussi as a means to access the financial data available on Yahoo Finance.
Yahoo Finance offers a wide range of market data on stocks, bonds, currencies and cryptocurrencies. In addition it offers market news, reports and analysis and fundamentals data- setting it apart from some of it’s competitors.
Requirements
pip install yfinance
conda install -c conda-forge pandas
pip install plotly-express
Coding
import yfinance as yf
import pandas as pd
import datetime
from datetime import date, timedelta
today = date.today()
date1 = today.strftime("%Y-%m-%d")
end_date = date1
date2 = date.today() -timedelta(days = 365)
date2 = date2.strftime("%Y-%m-%d")
start_date = date2
data = yf.download ( 'AAPL',
start = start_date,
end = end_date,
progress = False)
print(data[:10])
Visualise your Stock price data using Plotly Express. This visualisation will prompt a new window to open in your browser with up todate data.
import plotly.express as px
fig = px.line(data, x = data.index,
y = "Close",
title = "Stock Price data")
fig.show()
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