Update app.py

app.py

@@ -12,6 +12,49 @@ def ctc_lambda_func(args):
 # Load the model, providing the custom loss function in the custom_objects dictionary
 loaded_model = load_model('Text_recognizer_Using_CRNN_model.keras', custom_objects={'ctc': ctc_lambda_func},safe_mode=False)
 
+def process_image(img):
+    """
+    Converts image to shape (32, 128, 1) & normalize
+    """
+    w, h = img.shape
+
+#     _, img = cv2.threshold(img,
+#                            128,
+#                            255,
+#                            cv2.THRESH_BINARY | cv2.THRESH_OTSU)
+
+    # Aspect Ratio Calculation
+    new_w = 32
+    new_h = int(h * (new_w / w))
+    img = cv2.resize(img, (new_h, new_w))
+    w, h = img.shape
+
+    img = img.astype('float32')
+
+    # Converts each to (32, 128, 1)
+    if w < 32:
+        add_zeros = np.full((32-w, h), 255)
+        img = np.concatenate((img, add_zeros))
+        w, h = img.shape
+
+    if h < 128:
+        add_zeros = np.full((w, 128-h), 255)
+        img = np.concatenate((img, add_zeros), axis=1)
+        w, h = img.shape
+
+    if h > 128 or w > 32:
+        dim = (128,32)
+        img = cv2.resize(img, dim)
+
+    img = cv2.subtract(255, img)
+
+    img = np.expand_dims(img, axis=2)
+
+    # Normalize
+    img = img / 255
+
+    return img
+
 filepath="test_img.png"
 img = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)
 img = process_image(img)