Update app.py

app.py

@@ -9,27 +9,23 @@ def rectangle(image, result):
     """Draw rectangles on the image based on predicted coordinates."""
     draw = ImageDraw.Draw(image)
     for res in result:
-        top_left = tuple(res[0][0])  # top left coordinates as a tuple
-        bottom_right = tuple(res[0][2])  # bottom right coordinates as a tuple
+        top_left = tuple(res[0][0])
+        bottom_right = tuple(res[0][2])
         draw.rectangle((top_left, bottom_right), outline="blue", width=2)
-    # Display the image on Streamlit
     st.image(image)
 
-# Main title
+# Main title and markdowns
 st.title("Get text from an image with EasyOCR")
-
-# Subtitle
 st.markdown("## EasyOCR with Streamlit")
-
-# Upload image file or draw
 st.markdown("## Upload an Image or Draw")
+
+# Column layout for uploader and canvas
 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,
@@ -43,34 +39,29 @@ with col2:
         key="canvas",
     )
 
-image = None  # Initialize image variable
+image = None
 
-# Process uploaded image or drawing
 if file is not None:
-    image = Image.open(file)  # Read image with PIL library
+    image = Image.open(file)
 elif canvas_result.image_data is not None:
-    image = Image.fromarray(np.array(canvas_result.image_data, dtype=np.uint8)).convert('RGB')
+    # Convert canvas RGBA image to RGB
+    canvas_image_data = canvas_result.image_data.astype(np.uint8)
+    image = Image.fromarray(canvas_image_data, 'RGBA').convert('RGB')
 
 if image is not None:
-    st.image(image)  # Display the image
+    st.image(image)
 
-    # Initialize EasyOCR reader; you can add or remove languages based on your preference
     reader = easyocr.Reader(['en', 'ja'], gpu=False)
-    result = reader.readtext(np.array(image))  # Convert image to numpy array and process with EasyOCR
+    result = reader.readtext(np.array(image))
 
-    # 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}
-
-    # 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.")