EZOCR / app.py
Mattral's picture
Update app.py
20e3359 verified
raw
history blame
1.57 kB
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)