ngor21/txt

1import pandas as pd2import numpy as np3import streamlit as st4import easyocr5import PIL6from PIL import Image, ImageDraw7 8def rectangle(image, result):9    # https://www.blog.pythonlibrary.org/2021/02/23/drawing-shapes-on-images-with-python-and-pillow/10    """ draw rectangles on image based on predicted coordinates"""11    draw = ImageDraw.Draw(image)12    for res in result:13        top_left = tuple(res[0][0]) # top left coordinates as tuple14        bottom_right = tuple(res[0][2]) # bottom right coordinates as tuple15        draw.rectangle((top_left, bottom_right), outline="blue", width=2)16    #display image on streamlit17    st.image(image)18 19 20# main title21st.title("Text recognition on engineering drawings")22 23# subtitle24st.markdown("## Neural network model for text recognition")25 26# upload image file27file = st.file_uploader(label = "Upload Here", type=['png', 'jpg', 'jpeg'])28 29#read the csv file and display the dataframe30if file is not None:31    image = Image.open(file) # read image with PIL library32    st.image(image) #display33 34    # it will only detect the English and Turkish part of the image as text35    reader = easyocr.Reader(['en'], gpu=False) 36    result = reader.readtext(np.array(image))  # turn image to numpy array37 38    # Add a placeholder39    # latest_iteration = st.empty()40    # bar = st.progress(0)41    42    # for i in range(100):43      # Update the progress bar with each iteration.44      # latest_iteration.text(f'Iteration {i+1}')45      # bar.progress(i + 1)46      # time.sleep(0.1)47   48    # collect the results in the dictionary:49    textdic_easyocr = {}50    for idx in range(len(result)):51        pred_coor = result[idx][0]52        pred_text = result[idx][1]53        pred_confidence = result[idx][2]54        textdic_easyocr[pred_text] = {}55        textdic_easyocr[pred_text]['pred_confidence'] = pred_confidence56 57    # create a data frame which shows the predicted text and prediction confidence58    df = pd.DataFrame.from_dict(textdic_easyocr).T59    st.table(df)60 61    # get boxes on the image 62    rectangle(image, result)63 64    st.spinner(text="In progress...")65    66else:67    st.write("Upload your image")