test

app.py

@@ -1,124 +1,6 @@
 import streamlit as st
-from akaocr import TextEngine, BoxEngine
-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
+from st_copy_to_clipboard import st_copy_to_clipboard
 
-
-# Initialize the OCR engines
-box_engine = BoxEngine()
-text_engine = TextEngine()
-
-
-def transform_image(image, box):
-    # Get perspective transform image
-    assert len(box) == 4, "Shape of points must be 4x2"
-    img_crop_width = int(
-        max(
-            np.linalg.norm(box[0] - box[1]),
-            np.linalg.norm(box[2] - box[3])))
-    img_crop_height = int(
-        max(
-            np.linalg.norm(box[0] - box[3]),
-            np.linalg.norm(box[1] - box[2])))
-    pts_std = np.float32([[0, 0],
-                          [img_crop_width, 0],
-                          [img_crop_width, img_crop_height],
-                          [0, img_crop_height]])
-    box = np.array(box, dtype="float32")
-    M = cv2.getPerspectiveTransform(box, pts_std)
-    dst_img = cv2.warpPerspective(
-        image,
-        M, (img_crop_width, img_crop_height),
-        borderMode=cv2.BORDER_REPLICATE,
-        flags=cv2.INTER_CUBIC)
-
-    img_height, img_width = dst_img.shape[0:2]
-    if img_height/img_width >= 1.25:
-        dst_img = np.rot90(dst_img, k=3)
-
-    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("Quick OCR Copy")
-
-    uploaded_file = st.file_uploader(
-        "Choose an image...", type=["jpg", "jpeg", "png"])
-
-    if uploaded_file is not None:
-        # Convert the uploaded file to an OpenCV image
-        file_bytes = np.asarray(
-            bytearray(uploaded_file.read()), dtype=np.uint8)
-        org_image = cv2.imdecode(file_bytes, 1)
-        # st.image(org_image, channels="BGR", caption='Uploaded Image')
-
-        images = []
-        start = time.perf_counter()
-        boxes = box_engine(org_image)
-        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)
-
-        # 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
-                        # Show popup message
-                        st.toast(f"Text copied to clipboard: {text}")
-                        break  # Exit after finding the first match
-
-
-if __name__ == '__main__':
-    main()
+# Render copy to clipboard button
+st_copy_to_clipboard("Copy this to clipboard")

requirements.txt

@@ -3,4 +3,5 @@ akaocr
 opencv-python-headless
 numpy
 pyperclip
-streamlit_drawable_canvas
+streamlit_drawable_canvas
+st-copy-to-clipboard