File size: 2,579 Bytes
19f9ac5 6dd2ec6 849cfbb 6dd2ec6 849cfbb 4cb29e5 849cfbb 8973c03 849cfbb 6dd2ec6 849cfbb 6dd2ec6 849cfbb 6dd2ec6 849cfbb 6dd2ec6 849cfbb 6dd2ec6 8973c03 849cfbb 6dd2ec6 849cfbb 8973c03 849cfbb 6dd2ec6 849cfbb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
import streamlit as st
import numpy as np
import pandas as pd
import easyocr
from PIL import Image
from streamlit_drawable_canvas import st_canvas
def rectangle(image, result):
"""Draw rectangles on image based on predicted coordinates using PIL."""
from PIL import ImageDraw
draw = ImageDraw.Draw(image)
for res in result:
top_left = tuple(res[0][0])
bottom_right = tuple(res[0][2])
draw.rectangle((top_left, bottom_right), outline="blue", width=2)
return image
def main():
# Set up Streamlit page
st.set_page_config(
page_title="OCR App",
page_icon=":mag:",
layout="centered",
initial_sidebar_state="auto",
)
st.title("Optical Character Recognition (OCR) with EasyOCR")
st.markdown("""
Upload an image or use the canvas to draw, and the app will recognize and extract text from it.
Supported languages for recognition include English and Japanese.
""")
# Upload image or draw
col1, col2 = st.columns(2)
with col1:
file = st.file_uploader("Upload Image", type=['png', 'jpg', 'jpeg'])
with col2:
stroke_width = st.slider("Stroke Width: ", 1, 25, 3)
canvas_result = st_canvas(
fill_color="rgba(255, 165, 0, 0.3)",
stroke_width=stroke_width,
stroke_color="#ffffff",
background_color="#000000",
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).convert('RGB')
elif canvas_result.image_data is not None:
image = Image.fromarray(np.array(canvas_result.image_data).astype('uint8'), 'RGBA').convert('RGB')
else:
st.warning("Please upload an image or use the canvas to draw.")
st.stop()
st.image(image, caption='Uploaded Image', use_column_width=True)
# OCR
reader = easyocr.Reader(['en', 'ja'], gpu=False)
result = reader.readtext(np.array(image))
# Display results
if result:
image = rectangle(image, result)
st.image(image, caption='Processed Image with Detected Text', use_column_width=True)
textdic_easyocr = {idx: {'text': res[1], 'confidence': res[2]} for idx, res in enumerate(result)}
df = pd.DataFrame.from_dict(textdic_easyocr, orient='index')
st.dataframe(df)
else:
st.info("No text detected.")
if __name__ == "__main__":
main()
|