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import pandas as pd
import numpy as np
import streamlit as st
import easyocr
import PIL
from PIL import Image, ImageDraw
from matplotlib import pyplot as plt
# main title
st.title("Get text from image with EasyOCR")
# subtitle
st.markdown("## EasyOCRR with Streamlit")
# upload image file
file = st.file_uploader(label = "Upload your image", type=['png', 'jpg', 'jpeg'])
image = Image.open(file) # read image with PIL library
st.image(image) #display
# it will only detect the English and Turkish part of the image as text
reader = easyocr.Reader(['my','en'], gpu=False)
result = reader.readtext(np.array(image)) # turn image to numpy array
textdic_easyocr = {}
for idx in range(len(result)):
pred_coor = result[idx][0]
pred_text = result[idx][1]
pred_confidence = result[idx][2]
textdic_easyocr[pred_text] = {}
textdic_easyocr[pred_text]['pred_confidence'] = pred_confidence
# create a dataframe which shows the predicted text and prediction confidence
df = pd.DataFrame.from_dict(textdic_easyocr).T
st.table(df)
def rectangle(image, result):
# https://www.blog.pythonlibrary.org/2021/02/23/drawing-shapes-on-images-with-python-and-pillow/
""" draw rectangles on image based on predicted coordinates"""
draw = ImageDraw.Draw(image)
for res in result:
top_left = tuple(res[0][0]) # top left coordinates as tuple
bottom_right = tuple(res[0][2]) # bottom right coordinates as tuple
draw.rectangle((top_left, bottom_right), outline="blue", width=2)
#display image on streamlit
st.image(image)
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