Refactor imports for tensorflow (#27617)

* Refactoring imports for tensorflow

* Removing whitespace spaces on blank line 110

* Moving tensorflow to try/except block

* Fixed black formatting

* Refactoring try/except to if/else

homeassistant/components/tensorflow/image_processing.py

@@ -2,8 +2,22 @@
 import logging
 import os
 import sys
-
+import io
 import voluptuous as vol
+from PIL import Image, ImageDraw
+import numpy as np
+
+try:
+    import cv2
+except ImportError:
+    cv2 = None
+
+try:
+    # Verify that the TensorFlow Object Detection API is pre-installed
+    import tensorflow as tf  # noqa
+    from object_detection.utils import label_map_util  # noqa
+except ImportError:
+    label_map_util = None
 
 from homeassistant.components.image_processing import (
     CONF_CONFIDENCE,
@@ -84,14 +98,8 @@ def setup_platform(hass, config, add_entities, discovery_info=None):
     # append custom model path to sys.path
     sys.path.append(model_dir)
 
-    try:
-        # Verify that the TensorFlow Object Detection API is pre-installed
-        # pylint: disable=unused-import,unused-variable
-        os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
-        import tensorflow as tf  # noqa
-        from object_detection.utils import label_map_util  # noqa
-    except ImportError:
-        # pylint: disable=line-too-long
+    os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
+    if label_map_util is None:
         _LOGGER.error(
             "No TensorFlow Object Detection library found! Install or compile "
             "for your system following instructions here: "
@@ -99,11 +107,7 @@ def setup_platform(hass, config, add_entities, discovery_info=None):
         )  # noqa
         return
 
-    try:
-        # Display warning that PIL will be used if no OpenCV is found.
-        # pylint: disable=unused-import,unused-variable
-        import cv2  # noqa
-    except ImportError:
+    if cv2 is None:
         _LOGGER.warning(
             "No OpenCV library found. TensorFlow will process image with "
             "PIL at reduced resolution"
@@ -236,9 +240,6 @@ class TensorFlowImageProcessor(ImageProcessingEntity):
         }
 
     def _save_image(self, image, matches, paths):
-        from PIL import Image, ImageDraw
-        import io
-
         img = Image.open(io.BytesIO(bytearray(image))).convert("RGB")
         img_width, img_height = img.size
         draw = ImageDraw.Draw(img)
@@ -280,18 +281,8 @@ class TensorFlowImageProcessor(ImageProcessingEntity):
 
     def process_image(self, image):
         """Process the image."""
-        import numpy as np
-
-        try:
-            import cv2  # pylint: disable=import-error
-
-            img = cv2.imdecode(np.asarray(bytearray(image)), cv2.IMREAD_UNCHANGED)
-            inp = img[:, :, [2, 1, 0]]  # BGR->RGB
-            inp_expanded = inp.reshape(1, inp.shape[0], inp.shape[1], 3)
-        except ImportError:
-            from PIL import Image
-            import io
 
+        if cv2 is None:
             img = Image.open(io.BytesIO(bytearray(image))).convert("RGB")
             img.thumbnail((460, 460), Image.ANTIALIAS)
             img_width, img_height = img.size
@@ -301,6 +292,10 @@ class TensorFlowImageProcessor(ImageProcessingEntity):
                 .astype(np.uint8)
             )
             inp_expanded = np.expand_dims(inp, axis=0)
+        else:
+            img = cv2.imdecode(np.asarray(bytearray(image)), cv2.IMREAD_UNCHANGED)
+            inp = img[:, :, [2, 1, 0]]  # BGR->RGB
+            inp_expanded = inp.reshape(1, inp.shape[0], inp.shape[1], 3)
 
         image_tensor = self._graph.get_tensor_by_name("image_tensor:0")
         boxes = self._graph.get_tensor_by_name("detection_boxes:0")