Update app.py

app.py

@@ -1,32 +1,35 @@
-from PIL import Image, ImageDraw
+import pandas as pd
 import numpy as np
 import streamlit as st
-from streamlit_drawable_canvas import st_canvas
 import easyocr
-import pandas as pd
+from PIL import Image, ImageDraw
+from streamlit_drawable_canvas import st_canvas
 
 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
-    draw = ImageDraw.Draw(draw_image)
+    """Draw rectangles on the image based on predicted coordinates."""
+    draw = ImageDraw.Draw(image)
     for res in result:
-        top_left = tuple(res[0][0])
-        bottom_right = tuple(res[0][2])
+        top_left = tuple(res[0][0])  # top left coordinates as a tuple
+        bottom_right = tuple(res[0][2])  # bottom right coordinates as a tuple
         draw.rectangle((top_left, bottom_right), outline="blue", width=2)
-    st.image(draw_image, caption="Processed Image with Detected Text Highlighted")
+    # Display the image on Streamlit
+    st.image(image)
 
-# Main title and markdowns
+# Main title
 st.title("Get text from an image with EasyOCR")
+
+# Subtitle
 st.markdown("## EasyOCR with Streamlit")
-st.markdown("## Upload an Image or Draw")
 
-# Column layout for uploader and canvas
+# 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,
@@ -40,24 +43,34 @@ with col2:
         key="canvas",
     )
 
-image = None
+image = None  # Initialize image variable
+
+# 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(np.array(canvas_result.image_data, dtype=np.uint8)).convert('RGB')
 
 if image is not None:
-    st.image(image, caption="Uploaded/Drawn Image")
+    st.image(image)  # Display the image
 
-    # Optional: Indicate that processing is happening
-    with st.spinner('Processing...'):
-        reader = easyocr.Reader(['en', 'ja'], gpu=False)  # Consider moving this outside the loop if performance is a concern
-        result = reader.readtext(np.array(image))
+    # Initialize EasyOCR reader; you can add or remove languages based on your preference
+    reader = easyocr.Reader(['en'], gpu=False)
+    result = reader.readtext(np.array(image))  # Convert image to numpy array and process with EasyOCR
 
+    # Print all predicted text
     for idx, res in enumerate(result):
         pred_text = res[1]
         st.write(pred_text)
     
+    # Collect the results in a dictionary
     textdic_easyocr = {res[1]: {'pred_confidence': res[2]} for res in result}
-    df = pd.DataFrame.from_dict(textdic_easyocr, orient='index', columns=['pred_confidence'])
+
+    # Create a DataFrame to show the predicted text and prediction confidence
+    df = pd.DataFrame.from_dict(textdic_easyocr).T
     st.table(df)
 
+    # Draw rectangles around the detected text in the image
     rectangle(image, result)
 else:
     st.write("Please upload an image or use the canvas to draw.")