Update app.py

app.py

@@ -1,79 +1,76 @@
-import streamlit as st
-import numpy as np
 import pandas as pd
+import numpy as np
+import streamlit as st
 import easyocr
-from PIL import Image
+import PIL
+from PIL import Image, ImageDraw
 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 rectangles on 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 tuple
+        bottom_right = tuple(res[0][2])  # bottom right coordinates as tuple
         draw.rectangle((top_left, bottom_right), outline="blue", width=2)
-    return image
+    # Display image on streamlit
+    st.image(image)
+
+# Main title
+st.title("Get text from image with EasyOCR")
+
+# Subtitle
+st.markdown("## EasyOCR with Streamlit")
+
+# Upload image file or draw
+st.markdown("## Upload an Image or Draw")
+col1, col2 = st.columns(2)
 
-def main():
-    # Set up Streamlit page
-    st.set_page_config(
-        page_title="OCR App",
-        page_icon=":mag:",
-        layout="centered",
-        initial_sidebar_state="auto",
+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,
+        stroke_color="#ffffff",
+        background_color="#000000",
+        background_image=None if file else st.session_state.get("background", None),
+        update_streamlit=True,
+        width=400,
+        height=400,
+        drawing_mode="freedraw",
+        key="canvas",
     )
 
-    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)  # Read image with PIL library
+elif canvas_result.image_data is not None:
+    image = Image.fromarray(canvas_result.image_data.astype('uint8'), 'RGBA').convert('RGB')
+else:
+    st.write("Please upload an image or use the canvas to draw.")
+    image = None
 
-    # 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()
+if image is not None:
+    st.image(image)  # Display
 
-    st.image(image, caption='Uploaded Image', use_column_width=True)
-    
-    # OCR
-    reader = easyocr.Reader(['en', 'ja'], gpu=False)
-    result = reader.readtext(np.array(image))
+    # Only detect the English and Turkish part of the image as text
+    reader = easyocr.Reader(['en'], gpu=False) 
+    result = reader.readtext(np.array(image))  # Turn image to numpy array
+
+    # Print all predicted text:
+    for idx, res in enumerate(result):
+        pred_text = res[1]
+        st.write(pred_text)
     
-    # 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.")
+    # Collect the results in the dictionary:
+    textdic_easyocr = {res[1]: {'pred_confidence': res[2]} for res in result}
+
+    # Create a data frame which shows the predicted text and prediction confidence
+    df = pd.DataFrame.from_dict(textdic_easyocr).T
+    st.table(df)
 
-if __name__ == "__main__":
-    main()
+    # Get boxes on the image 
+    rectangle(image, result)