update copy features

app.py

@@ -4,6 +4,9 @@ import cv2
 import numpy as np
 from PIL import Image
 import time
+import pyperclip  # Import pyperclip for clipboard operations
+
+from streamlit_drawable_canvas import st_canvas
 
 # Initialize the OCR engines
 box_engine = BoxEngine()
@@ -38,8 +41,16 @@ def transform_image(image, box):
 
     return dst_img
 
+def is_point_in_box(point, box):
+    """
+    Check if a point is inside a bounding box.
+    """
+    x, y = point
+    contour = box.reshape((-1, 1, 2)).astype(np.int32)
+    return cv2.pointPolygonTest(contour, (x, y), False) >= 0
+
 def main():
-    st.title("OCR Application with akaOCR")
+    st.title("Quick Copy")
 
     uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
 
@@ -55,19 +66,49 @@ def main():
         processing_time = time.perf_counter() - start
         st.write(f"Box detection took {processing_time:.2f} seconds.")
 
+        # Extracted text for each box
+        extracted_texts = []
+
         for box in boxes[::-1]:
             org_image = cv2.polylines(org_image, [box.astype(np.int32)], isClosed=True, color=(0, 255, 0), thickness=2)
             image = transform_image(org_image, box)
             images.append(image)
 
+        # Get the texts from the boxes
+        texts = text_engine(images)
+
+        # Store extracted texts with corresponding boxes
+        for text, box in zip(texts, boxes[::-1]):
+            extracted_texts.append((text, box))
+
         # Convert back to PIL Image for displaying
         output_image = Image.fromarray(cv2.cvtColor(org_image, cv2.COLOR_BGR2RGB))
-        st.image(output_image, caption='Detected Text Boxes', use_column_width=True)
+        # st.image(output_image, caption='Detected Text Boxes', use_column_width=True)
 
-        texts = text_engine(images)
-        
-        st.write("Extracted Texts:")
-        st.write(texts)
+        # Create a drawable canvas
+        canvas_result = st_canvas(
+            background_image=output_image,
+            stroke_width=0,
+            update_streamlit=True,
+            height=output_image.height,
+            width=output_image.width,
+            drawing_mode="freedraw",  # Disable drawing to make it click only
+            key="canvas",
+        )
+
+        # Check if any clicks are detected
+        if canvas_result.json_data is not None:
+            for annotation in canvas_result.json_data["objects"]:
+                x = annotation["left"]
+                y = annotation["top"]
+                clicked_point = (x, y)
+
+                # Check which bounding box the user clicked on
+                for text, box in extracted_texts:
+                    if is_point_in_box(clicked_point, box):
+                        pyperclip.copy(text[0])  # Copy text to clipboard
+                        st.toast(f"Text copied to clipboard: {text}")  # Show popup message
+                        break  # Exit after finding the first match
 
 if __name__ == '__main__':
     main()

requirements.txt

@@ -2,3 +2,5 @@ streamlit
 akaocr
 opencv-python-headless
 numpy
+pyperclip
+streamlit_drawable_canvas