Update app.py

app.py

@@ -75,12 +75,13 @@ iface.launch(debug=True)
 
 
 
-
 import cv2
 import numpy as np
-import keras_ocr
+import tensorflow as tf
+from tensorflow import keras
+from tensorflow.keras_ocr import pipeline  # 使用tf.keras_ocr
 
-def detect_and_draw_lines(img, rho=1, theta=1):
+def detect_and_draw_lines(img, rho=1, theta=np.pi/180):
     """Detect lines in the image and draw them."""
     edges = cv2.Canny(img, 50, 150, apertureSize=3)
     lines = cv2.HoughLines(edges, rho, theta, 100)
@@ -92,34 +93,29 @@ def detect_and_draw_lines(img, rho=1, theta=1):
 
 def inpaint_lines(img):
     """Inpaint the detected lines."""
-    # Create a mask where lines are white and the rest is black
     mask = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
     mask[mask > 0] = 255
-    # Inpaint using the mask
     inpainted_img = cv2.inpaint(img, mask, 3, cv2.INPAINT_TELEA)
     return inpainted_img
 
 def inpaint_text(img_path, pipeline):
-    # Read the image
-    img = keras_ocr.tools.read(img_path)
+    img = tf.keras.preprocessing.image.load_img(img_path, color_mode='rgb', target_size=(1024, 1024))
+    img_array = tf.keras.preprocessing.image.img_to_array(img)
+    img_array = np.expand_dims(img_array, axis=0)
     # Detect and draw lines
-    img_with_lines = detect_and_draw_lines(img)
+    img_with_lines = detect_and_draw_lines(img_array[0])
     # Inpaint the lines
     inpainted_img = inpaint_lines(img_with_lines)
-    # Recognize text
-    prediction_groups = pipeline.recognize([inpainted_img])
-    # Define the mask for inpainting text
+    predictions = pipeline.recognize([inpainted_img])
     mask = np.zeros(inpainted_img.shape[:2], dtype="uint8")
-    for box in prediction_groups[0]:
+    for box in predictions[0]:
         x0, y0, x1, y1, x2, y2, x3, y3 = box[1]
         cv2.line(mask, (x0, y0), (x1, y1), 255, 10)
         cv2.line(mask, (x2, y2), (x3, y3), 255, 10)
-    # Inpaint text
     inpainted_img = cv2.inpaint(inpainted_img, mask, 3, cv2.INPAINT_TELEA)
     return inpainted_img
 
-# keras-ocr will automatically download pretrained weights for the detector and recognizer.
-pipeline = keras_ocr.pipeline.Pipeline()
+pipeline = pipeline.Pipeline()
 def RemoveTextAndLines(image):
     img_text_and_lines_removed = inpaint_text(image, pipeline)
     return cv2.cvtColor(img_text_and_lines_removed, cv2.COLOR_BGR2RGB)
@@ -138,6 +134,3 @@ iface.launch(debug=True)
 
 
 
-
-
-