Update app.py

app.py

@@ -1,38 +1,74 @@
-from PIL import Image, ImageDraw
-import numpy as np
 import streamlit as st
 from streamlit_drawable_canvas import st_canvas
+import numpy as np
+from PIL import Image
 import easyocr
 import pandas as pd
 
-def rectangle(image, result):
-    """Draw rectangles on the image based on predicted coordinates and display the image."""
-    draw_image = image.copy()  # Work on a copy of the image
+def process_image_for_ocr(image):
+    """Converts the image for EasyOCR and draws rectangles around detected text."""
+    # Convert PIL image to numpy array
+    image_np = np.array(image)
+    
+    # Initialize EasyOCR reader
+    reader = easyocr.Reader(['en'], gpu=False)  # Add more languages or adjust as needed
+    result = reader.readtext(image_np)
+    
+    # Draw rectangles on a copy of the image
+    draw_image = image.copy()
     draw = ImageDraw.Draw(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)
-    st.image(draw_image, caption="Processed Image with Detected Text Highlighted")
+        draw.rectangle([top_left, bottom_right], outline="red", width=2)
+    
+    return draw_image, result
+
+def display_text_results(result):
+    """Displays text results in Streamlit."""
+    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.table(df)
 
-# Rest of your script remains unchanged until the final processing:
+st.title("OCR with EasyOCR and Streamlit")
+st.markdown("Upload an Image or Draw Below")
 
-if image is not None:
-    st.image(image, caption="Uploaded/Drawn Image")
+# Column layout for uploader and canvas
+col1, col2 = st.columns(2)
 
-    # Optional: Indicate that processing is happening
-    with st.spinner('Processing...'):
-        reader = easyocr.Reader(['en'], gpu=False)  # Consider moving this outside the loop if performance is a concern
-        result = reader.readtext(np.array(image))
+with col1:
+    uploaded_file = st.file_uploader("Upload Here", type=['png', 'jpg', 'jpeg'])
 
-    for idx, res in enumerate(result):
-        pred_text = res[1]
-        st.write(pred_text)
+with col2:
+    # Use the background_image parameter if you want to draw on an uploaded image.
+    canvas_result = st_canvas(
+        fill_color="rgba(255, 165, 0, 0.3)",  # Use a transparent fill color
+        stroke_width=3,
+        stroke_color="#FFFFFF",
+        background_color="#000000",
+        width=400,
+        height=400,
+        drawing_mode="freedraw",
+        key="canvas",
+    )
+
+image = None
+
+if uploaded_file is not None:
+    image = Image.open(uploaded_file).convert('RGB')
+
+elif canvas_result.image_data is not None:
+    # Convert the canvas data to an Image
+    canvas_image = Image.fromarray((canvas_result.image_data).astype('uint8'), mode='RGBA')
+    image = canvas_image.convert('RGB')
+
+if image:
+    st.image(image, caption="Uploaded/Drawn Image")
+
+    processed_image, ocr_result = process_image_for_ocr(image)
     
-    textdic_easyocr = {res[1]: {'pred_confidence': res[2]} for res in result}
-    df = pd.DataFrame.from_dict(textdic_easyocr, orient='index', columns=['pred_confidence'])
-    st.table(df)
+    st.image(processed_image, caption="Processed Image with Detected Text")
+    display_text_results(ocr_result)
 
-    rectangle(image, result)
 else:
     st.write("Please upload an image or use the canvas to draw.")