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import logging
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s [%(levelname)s] %(name)s: %(message)s"
)
import streamlit as st
import streamlit.components.v1 as components
from myocr.pipelines import CommonOCRPipeline
from PIL import Image, ImageDraw, ImageFont
import tempfile
import pandas as pd
import os
logger = logging.getLogger(__name__)
st.set_page_config(layout="wide")
st.title("MyOCR Demo")
# init pipeline
@st.cache_resource
def load_pipeline():
pipeline = CommonOCRPipeline("cpu")
return pipeline
pipeline = load_pipeline()
font = ImageFont.truetype("src/NotoSans.ttf", 12)
def google_analytics():
# Google Analytics
GA_MEASUREMENT_ID = os.getenv("GOOGLE_ANALYTICS") or "NO_ID"
google_analytics_code = f"""
<!-- Google tag (gtag.js) -->
<script async src="https://www.googletagmanager.com/gtag/js?id={GA_MEASUREMENT_ID}"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){{dataLayer.push(arguments);}}
gtag('js', new Date());
gtag('config', '{GA_MEASUREMENT_ID}');
</script>
"""
components.html(google_analytics_code, height=0, width=0)
def main():
google_analytics()
left_col, right_col = st.columns([2, 1.5])
with left_col:
uploaded_file = st.file_uploader("", type=["png", "jpg", "jpeg"])
spinner_container = st.empty()
image_slot = st.empty()
if uploaded_file:
image = Image.open(uploaded_file)
image_slot.image(image, use_container_width=True)
else:
return
with tempfile.NamedTemporaryFile(delete=True, suffix=uploaded_file.name) as temp_file:
temp_file.write(uploaded_file.getbuffer())
temp_file_path = temp_file.name
with spinner_container:
with st.spinner("Recognizing text..."):
results = pipeline(temp_file_path)
image = Image.open(uploaded_file).convert("RGB")
image_with_boxes = image.copy()
draw = ImageDraw.Draw(image_with_boxes)
table_data = []
for item in results.text_items:
text = item.text
bbox = item.bounding_box
top_left = (bbox.left,bbox.top)
bottom_right = (bbox.right, bbox.bottom )
draw.rectangle([top_left, bottom_right], outline="red", width=2)
draw.text((bbox.left, 0 if bbox.top - 18<0 else bbox.top - 18), text, font=font, fill="green")
table_data.append((text, item.confidence))
image_slot.image(image_with_boxes, use_container_width=True)
with right_col:
tabs = st.tabs(["Recognized"])
with tabs[0]:
df = pd.DataFrame(table_data, columns=["Text", "Confidence"])
st.table(df)
if __name__ == "__main__":
try:
main()
except Exception as e:
logger.error("Error: ", e)
st.error(f"Internal Error!") |