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| import pandas as pd | |
| import numpy as np | |
| import streamlit as st | |
| import easyocr | |
| import cv2 | |
| import PIL | |
| from PIL import Image | |
| 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']) | |
| #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 | |
| # create a dataframe which shows the predicted text and prediction confidence | |
| df = pd.DataFrame.from_dict(textdic_easyocr).T | |
| st.table(df) | |
| else: | |
| st.write("Upload your image") | |