Huertas97 commited on
Commit
a771624
1 Parent(s): 6b70ec8

Add v1 app

Browse files
Examples/meme_1.jpg ADDED
Examples/meme_2.jpg ADDED
Examples/meme_3.jpg ADDED
aida_logo.png ADDED
app_inpaint.py ADDED
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+ import streamlit as st
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+ import spacy
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+ from streamlit_echarts import st_echarts
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+ from annotated_text import annotated_text
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+ import time
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+ import easyocr
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+ import math
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+ from pathlib import Path
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+ from PIL import Image, ImageDraw
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+ import PIL
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+ import io
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+ import os
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+ import random
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+ import matplotlib.pyplot as plt
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+ import cv2
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+ # from google.colab.patches import cv2_imshow
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+ import numpy as np
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+ from tqdm.auto import tqdm
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+ import shutil
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+ import base64
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+ import logging
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+ logging.basicConfig(format='%(asctime)s - %(message)s',
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+ datefmt='%Y-%m-%d %H:%M:%S',
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+ level=logging.INFO,
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+ )
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+
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+
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+ @st.cache(show_spinner=False, allow_output_mutation=True, suppress_st_warning=True)
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+ def load_models():
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+ #specify shortform of language you want to extract,
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+ # I am using Spanish(es) and English(en) here by list of language ids
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+ reader = easyocr.Reader(['en'],)
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+ return reader
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+
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+ reader = load_models()
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+
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+ def midpoint(x1, y1, x2, y2):
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+ x_mid = int((x1 + x2)/2)
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+ y_mid = int((y1 + y2)/2)
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+ return (x_mid, y_mid)
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+
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+ def inpaint_text(img, text_coordinates):
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+ # read image
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+
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+ # img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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+ # generate (word, box) tuples
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+ mask = np.zeros(img.shape[:2], dtype="uint8")
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+ for box in text_coordinates:
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+ x0, y0 = box[0]
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+ x1, y1 = box[1]
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+ x2, y2 = box[2]
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+ x3, y3 = box[3]
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+
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+ x_mid0, y_mid0 = midpoint(x1, y1, x2, y2)
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+ x_mid1, y_mi1 = midpoint(x0, y0, x3, y3)
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+
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+ thickness = int(math.sqrt( (x2 - x1)**2 + (y2 - y1)**2 ))
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+
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+ cv2.line(mask, (x_mid0, y_mid0), (x_mid1, y_mi1), 255,
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+ thickness)
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+ img = cv2.inpaint(img, mask, 7, cv2.INPAINT_NS)
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+
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+ return(img)
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+
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+
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+ def file_selector(folder_path='.'):
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+ filenames = os.listdir(folder_path)
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+ selected_filename = st.selectbox('Select a file', filenames)
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+ return os.path.join(folder_path, selected_filename)
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+
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+
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+
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+
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+
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+
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+
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+
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+ st.set_page_config(
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+ page_title="Inpaint Me",
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+ page_icon=":art:",
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+ layout="wide",
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+ initial_sidebar_state="expanded",
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+ menu_items={
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+ 'Get Help': 'https://www.extremelycoolapp.com/help',
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+ 'Report a bug': "https://www.extremelycoolapp.com/bug",
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+ 'About': "# This is a header. This is an *extremely* cool app!"
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+ }
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+ )
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+
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+
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+ st.markdown(
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+ """
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+ <style>
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+ .logo-img {
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+
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+
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+ margin-top: auto;
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+ margin-left: 30%;
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+ width: 50%;
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+
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+ }
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+ .logo-img-2 {
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+ margin-top: auto;
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+ margin-left: 20%;
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+ width: 35%;
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+
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+ }
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+ </style>
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+ """,
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+ unsafe_allow_html=True
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+ )
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+
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+ LOGO_IMAGE = "inpaint_me_logo.png"
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+
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+ col1, col2= st.columns([2, 2])
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+ with col1:
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+ # st.image('./aida_logo.png')
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+ st.markdown(
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+ f"""
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+ <img class="logo-img" src="data:image/png;base64,{base64.b64encode(open(LOGO_IMAGE, "rb").read()).decode()}">
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+ """,
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+ unsafe_allow_html=True
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+ )
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+
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+ with col2:
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+ # st.image('./aida_logo.png')
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+ st.markdown(
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+ f"""
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+ <img class="logo-img-2" src="data:image/png;base64,{base64.b64encode(open("aida_logo.png", "rb").read()).decode()}">
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+ """,
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+ unsafe_allow_html=True
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+ )
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+
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+
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+ st.header("")
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+ with st.expander("Project Description", expanded=False):
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+ st.write("""
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+ Developed in Applied Intelligence and Data Analysis ([AI+DA](http://aida.etsisi.upm.es/)) group at Polytech University of Madrid (UPM).
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+
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+ To rule out the possibility of text misleading image Deep Learning models (e.g., CNNs) it is useful to remove text from images. Hence,
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+ this tool uses [EasyOCR](https://github.com/JaidedAI/EasyOCR) and [OpenCV](https://pypi.org/project/opencv-python/) for detecting texts and inpainting them. Currently, only `JPG` files are supported. This tools has been tested on memes, feel free to try some examples or upload your own images.
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+ """)
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+
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+
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+
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+ filename_example = None
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+ if st.checkbox('Select a example'):
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+ folder_path = './Examples/'
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+ # if st.checkbox('Change directory'):
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+ # folder_path = st.text_input('Enter folder path', '.')
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+ filename_example = file_selector(folder_path=folder_path)
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+ st.write('You selected `%s`' % filename_example)
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+
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+ uploaded_file = st.file_uploader(label="Upload image",
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+ type="jpg",
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+ accept_multiple_files=False,
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+ key=None,
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+ help=None,
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+ on_change=None,
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+ args=None,
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+ kwargs=None,
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+ )
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+
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+
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+
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+ col1, col2, col3 = st.columns([2, 0.5, 2])
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+
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+
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+
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+ if filename_example:
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+ with col1:
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+ st.header("Original")
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+ img = Image.open( filename_example )
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+ st.image(img, caption=None, width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto")
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+
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+ with col3:
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+ st.header("Inpainted")
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+ with st.spinner('Wait for it...'):
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+ img_array = np.array(Image.open( filename_example ))
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+ # detect text
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+ bounds = reader.readtext(img_array, detail=1) #detail=1 # [(coordinates, detected text, confidence threshold)]
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+ text_coordinates = [ bound[0] for bound in bounds]
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+ # inpaint text coordinates
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+ inpaint_image = inpaint_text(img_array, text_coordinates)
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+ st.image(inpaint_image, caption=None, width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto")
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+
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+ if uploaded_file:
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+ with col1:
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+ st.header("Original")
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+ st.image(uploaded_file, caption=None, width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto")
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+
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+ with col3:
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+ st.header("Inpainted")
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+ with st.spinner('Wait for it...'):
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+ # Transform loaded file to bytes
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+ bytes_data = uploaded_file.getvalue()
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+ # bytes to numpy array
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+ img_array = np.array(Image.open(io.BytesIO(bytes_data)))
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+ # detect text
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+ bounds = reader.readtext(img_array, detail=1) #detail=1 # [(coordinates, detected text, confidence threshold)]
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+ text_coordinates = [ bound[0] for bound in bounds]
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+ # inpaint text coordinates
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+ inpaint_image = inpaint_text(img_array, text_coordinates)
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+ st.image(inpaint_image, caption=None, width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto")
inpaint_me_logo.png ADDED