app.py

import pandas as pd
import numpy as np
import PIL
from PIL import Image
import streamlit as st
import torch
import easyocr
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
image = st.file_uploader(label = "Upload your image", type=['png', 'jpg', 'jpeg'])

#read the csv file and display the dataframe
if file is not None:
    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(['tr','en'], gpu=False) 
    result = reader.readtext(np.array(image))  # turn image to numpy array

    # collect the results in dictionary:
    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
    
    df = pd.DataFrame.from_dict(textdic_easyocr).T
    
    st.table(df)

    
    ax1.plot(agg_df.year, agg_df.rating)
    st.pyplot(fig1)
    
    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 on image, 2 is thickness
        cv2.rectangle(image, top_left, bottom_right, (0, 255, 0), 2)
        # write recognized text on image (top_left) minus 10 pixel on y
        cv2.putText(image, res[1], (top_left[0], top_left[1]-10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
    fig1, ax1 = plt.subplots()
    plt.imshow(image)
    plt.show()
    
else:
    st.write("Upload your image")