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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 | |
| 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) | |
| # main title | |
| st.title("Get text from image with EasyOCR") | |
| # subtitle | |
| st.markdown("## EasyOCR with Streamlit") | |
| # upload image file | |
| file = st.file_uploader(label = "Upload Here", 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(['en','ja'], gpu=False) | |
| result = reader.readtext(np.array(image)) # turn image to numpy array | |
| # Add a placeholder | |
| # latest_iteration = st.empty() | |
| # bar = st.progress(0) | |
| # for i in range(100): | |
| # Update the progress bar with each iteration. | |
| # latest_iteration.text(f'Iteration {i+1}') | |
| # bar.progress(i + 1) | |
| # time.sleep(0.1) | |
| # print all predicted text: | |
| for idx in range(len(result)): | |
| pred_text = result[idx][1] | |
| st.write(pred_text) | |
| # collect the results in the 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 data frame which shows the predicted text and prediction confidence | |
| df = pd.DataFrame.from_dict(textdic_easyocr).T | |
| st.table(df) | |
| # get boxes on the image | |
| rectangle(image, result) | |
| st.spinner(text="In progress...") | |
| else: | |
| st.write("Upload your image") | |