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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
from streamlit_drawable_canvas import st_canvas
def rectangle(image, result):
"""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 or draw
st.markdown("## Upload an Image or Draw")
col1, col2 = st.columns(2)
with col1:
file = st.file_uploader("Upload Here", type=['png', 'jpg', 'jpeg'])
with col2:
# Drawable canvas
canvas_result = st_canvas(
fill_color="rgba(255, 165, 0, 0.3)",
stroke_width=3,
stroke_color="#ffffff",
background_color="#000000",
background_image=None if file else st.session_state.get("background", None),
update_streamlit=True,
width=400,
height=400,
drawing_mode="freedraw",
key="canvas",
)
# Process uploaded image or drawing
if file is not None:
image = Image.open(file) # Read image with PIL library
elif canvas_result.image_data is not None:
image = Image.fromarray(canvas_result.image_data.astype('uint8'), 'RGBA').convert('RGB')
else:
st.write("Please upload an image or use the canvas to draw.")
image = None
if image is not None:
st.image(image) # Display
# Only detect the English and Turkish part of the image as text
reader = easyocr.Reader(['en','my'], gpu=False)
result = reader.readtext(np.array(image)) # Turn image to numpy array
# Print all predicted text:
for idx, res in enumerate(result):
pred_text = res[1]
st.write(pred_text)
# Collect the results in the dictionary:
textdic_easyocr = {res[1]: {'pred_confidence': res[2]} for res in result}
# 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)
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