非同期描画におけるノード削除時の不正終了対応。

Author: Kazuhito00

node/analysis_node/node_fps.py

@@ -5,6 +5,8 @@
 
 import dearpygui.dearpygui as dpg
 
+from node_editor.util import dpg_get_value, dpg_set_value
+
 from node.node_abc import DpgNodeABC
 
 
@@ -123,7 +125,7 @@ def update(
                 destination_tag = connection_info[1] + 'Value'
 
                 # 値更新
-                input_value = dpg.get_value(source_tag)
+                input_value = dpg_get_value(source_tag)
 
                 # 数値のみを抽出
                 input_value = re.sub(r'\D', '', input_value)
@@ -159,7 +161,7 @@ def update(
                         4) + 'ms)'
 
                     # テキスト更新
-                    dpg.set_value(destination_tag, text)
+                    dpg_set_value(destination_tag, text)
 
                     # 全スロットの合計時間
                     total_elapsed_time += average_elapsed_time
@@ -175,8 +177,8 @@ def update(
                 text += '{:.2f}'.format(fps).zfill(3)
             # text += ' (' + '{:.0f}'.format(total_elapsed_time).zfill(4) + 'ms)'
 
-            dpg.set_value(output_value01_tag, text)
-            dpg.set_value(
+            dpg_set_value(output_value01_tag, text)
+            dpg_set_value(
                 output_value02_tag,
                 '{:.0f}'.format(total_elapsed_time).zfill(4) + 'ms',
             )

node/analysis_node/node_rgb_histgram.py

@@ -4,6 +4,8 @@
 import numpy as np
 import dearpygui.dearpygui as dpg
 
+from node_editor.util import dpg_get_value, dpg_set_value
+
 from node.node_abc import DpgNodeABC
 
 
@@ -128,15 +130,16 @@ def update(
             r_histgram = cv2.calcHist([frame], [2], None, [256], [0, 256])
 
             # ヒストグラム反映
-            dpg.set_value(tag_node_input01_value_name + 'line_b',
+            dpg_set_value(tag_node_input01_value_name + 'line_b',
                           [self._default_xdata, b_histgram.T[0]])
-            dpg.set_value(tag_node_input01_value_name + 'line_g',
+            dpg_set_value(tag_node_input01_value_name + 'line_g',
                           [self._default_xdata, g_histgram.T[0]])
-            dpg.set_value(tag_node_input01_value_name + 'line_r',
+            dpg_set_value(tag_node_input01_value_name + 'line_r',
                           [self._default_xdata, r_histgram.T[0]])
-            dpg.set_axis_limits(
-                tag_node_input01_value_name + 'yaxis', 0,
-                int(np.sum(b_histgram.T[0]) / self._yaxis_divide_value))
+            if dpg.does_item_exist(tag_node_input01_value_name + 'yaxis'):
+                dpg.set_axis_limits(
+                    tag_node_input01_value_name + 'yaxis', 0,
+                    int(np.sum(b_histgram.T[0]) / self._yaxis_divide_value))
 
             result = {}
             result['r_histgram'] = list(r_histgram.T[0])

node/deep_learning_node/node_classification.py

@@ -6,6 +6,8 @@
 import numpy as np
 import dearpygui.dearpygui as dpg
 
+from node_editor.util import dpg_get_value, dpg_set_value
+
 from node.node_abc import DpgNodeABC
 from node_editor.util import convert_cv_to_dpg
 
@@ -186,10 +188,10 @@ def update(
                 source_tag = connection_info[0] + 'Value'
                 destination_tag = connection_info[1] + 'Value'
                 # 値更新
-                input_value = int(dpg.get_value(source_tag))
+                input_value = int(dpg_get_value(source_tag))
                 input_value = max([self._min_val, input_value])
                 input_value = min([self._max_val, input_value])
-                dpg.set_value(destination_tag, input_value)
+                dpg_set_value(destination_tag, input_value)
             if connection_type == self.TYPE_IMAGE:
                 # 画像取得元のノード名(ID付き)を取得
                 connection_info_src = connection_info[0]
@@ -201,10 +203,10 @@ def update(
         frame = node_image_dict.get(connection_info_src, None)
 
         # CPU/GPU選択状態取得
-        provider = dpg.get_value(tag_provider_select_value_name)
+        provider = dpg_get_value(tag_provider_select_value_name)
 
         # モデル情報取得
-        model_name = dpg.get_value(input_value02_tag)
+        model_name = dpg_get_value(input_value02_tag)
         model_path = self._model_path_setting[model_name]
         model_class = self._model_class[model_name]
 
@@ -287,7 +289,7 @@ def update(
         if frame is not None and use_pref_counter:
             elapsed_time = time.perf_counter() - start_time
             elapsed_time = int(elapsed_time * 1000)
-            dpg.set_value(output_value02_tag,
+            dpg_set_value(output_value02_tag,
                           str(elapsed_time).zfill(4) + 'ms')
 
         # 描画
@@ -318,7 +320,7 @@ def update(
                 small_window_w,
                 small_window_h,
             )
-            dpg.set_value(output_value01_tag, texture)
+            dpg_set_value(output_value01_tag, texture)
 
         return frame, result
 
@@ -330,7 +332,7 @@ def get_setting_dict(self, node_id):
         input_value02_tag = tag_node_name + ':' + self.TYPE_TEXT + ':Input02Value'
 
         # 選択モデル
-        model_name = dpg.get_value(input_value02_tag)
+        model_name = dpg_get_value(input_value02_tag)
 
         pos = dpg.get_item_pos(tag_node_name)
 
@@ -347,4 +349,4 @@ def set_setting_dict(self, node_id, setting_dict):
 
         model_name = setting_dict[input_value02_tag]
 
-        dpg.set_value(input_value02_tag, model_name)
+        dpg_set_value(input_value02_tag, model_name)

node/deep_learning_node/node_face_detection.py

@@ -6,6 +6,8 @@
 import numpy as np
 import dearpygui.dearpygui as dpg
 
+from node_editor.util import dpg_get_value, dpg_set_value
+
 from node.node_abc import DpgNodeABC
 from node_editor.util import convert_cv_to_dpg
 
@@ -203,10 +205,10 @@ def update(
                 source_tag = connection_info[0] + 'Value'
                 destination_tag = connection_info[1] + 'Value'
                 # 値更新
-                input_value = round(float(dpg.get_value(source_tag)), 3)
+                input_value = round(float(dpg_get_value(source_tag)), 3)
                 input_value = max([self._min_val, input_value])
                 input_value = min([self._max_val, input_value])
-                dpg.set_value(destination_tag, input_value)
+                dpg_set_value(destination_tag, input_value)
             if connection_type == self.TYPE_IMAGE:
                 # 画像取得元のノード名(ID付き)を取得
                 connection_info_src = connection_info[0]
@@ -217,13 +219,13 @@ def update(
         frame = node_image_dict.get(connection_info_src, None)
 
         # スコア閾値
-        score_th = round(float(dpg.get_value(input_value03_tag)), 3)
+        score_th = round(float(dpg_get_value(input_value03_tag)), 3)
 
         # CPU/GPU選択状態取得
-        provider = dpg.get_value(tag_provider_select_value_name)
+        provider = dpg_get_value(tag_provider_select_value_name)
 
         # モデル情報取得
-        model_name = dpg.get_value(input_value02_tag)
+        model_name = dpg_get_value(input_value02_tag)
         model_path = self._model_path_setting[model_name]
         model_class = self._model_class[model_name]
 
@@ -259,7 +261,7 @@ def update(
         if frame is not None and use_pref_counter:
             elapsed_time = time.perf_counter() - start_time
             elapsed_time = int(elapsed_time * 1000)
-            dpg.set_value(output_value02_tag,
+            dpg_set_value(output_value02_tag,
                           str(elapsed_time).zfill(4) + 'ms')
 
         # 描画
@@ -276,7 +278,7 @@ def update(
                 small_window_w,
                 small_window_h,
             )
-            dpg.set_value(output_value01_tag, texture)
+            dpg_set_value(output_value01_tag, texture)
 
         return frame, result
 
@@ -289,9 +291,9 @@ def get_setting_dict(self, node_id):
         input_value03_tag = tag_node_name + ':' + self.TYPE_FLOAT + ':Input03Value'
 
         # 選択モデル
-        model_name = dpg.get_value(input_value02_tag)
+        model_name = dpg_get_value(input_value02_tag)
         # スコア閾値
-        score_th = round(float(dpg.get_value(input_value03_tag)), 3)
+        score_th = round(float(dpg_get_value(input_value03_tag)), 3)
 
         pos = dpg.get_item_pos(tag_node_name)
 
@@ -311,5 +313,5 @@ def set_setting_dict(self, node_id, setting_dict):
         model_name = setting_dict[input_value02_tag]
         score_th = setting_dict[input_value03_tag]
 
-        dpg.set_value(input_value02_tag, model_name)
-        dpg.set_value(input_value03_tag, score_th)
+        dpg_set_value(input_value02_tag, model_name)
+        dpg_set_value(input_value03_tag, score_th)

node/deep_learning_node/node_low_light_image_enhancement.py

@@ -5,6 +5,8 @@
 import numpy as np
 import dearpygui.dearpygui as dpg
 
+from node_editor.util import dpg_get_value, dpg_set_value
+
 from node.node_abc import DpgNodeABC
 from node_editor.util import convert_cv_to_dpg
 
@@ -181,10 +183,10 @@ def update(
                 source_tag = connection_info[0] + 'Value'
                 destination_tag = connection_info[1] + 'Value'
                 # 値更新
-                input_value = int(dpg.get_value(source_tag))
+                input_value = int(dpg_get_value(source_tag))
                 input_value = max([self._min_val, input_value])
                 input_value = min([self._max_val, input_value])
-                dpg.set_value(destination_tag, input_value)
+                dpg_set_value(destination_tag, input_value)
             if connection_type == self.TYPE_IMAGE:
                 # 画像取得元のノード名(ID付き)を取得
                 connection_info_src = connection_info[0]
@@ -195,10 +197,10 @@ def update(
         frame = node_image_dict.get(connection_info_src, None)
 
         # CPU/GPU選択状態取得
-        provider = dpg.get_value(tag_provider_select_value_name)
+        provider = dpg_get_value(tag_provider_select_value_name)
 
         # モデル情報取得
-        model_name = dpg.get_value(input_value02_tag)
+        model_name = dpg_get_value(input_value02_tag)
         model_path = self._model_path_setting[model_name]
         model_class = self._model_class[model_name]
 
@@ -229,7 +231,7 @@ def update(
         if frame is not None and use_pref_counter:
             elapsed_time = time.perf_counter() - start_time
             elapsed_time = int(elapsed_time * 1000)
-            dpg.set_value(output_value02_tag,
+            dpg_set_value(output_value02_tag,
                           str(elapsed_time).zfill(4) + 'ms')
 
         # 描画
@@ -239,7 +241,7 @@ def update(
                 small_window_w,
                 small_window_h,
             )
-            dpg.set_value(output_value01_tag, texture)
+            dpg_set_value(output_value01_tag, texture)
 
         return frame, None
 
@@ -251,7 +253,7 @@ def get_setting_dict(self, node_id):
         input_value02_tag = tag_node_name + ':' + self.TYPE_TEXT + ':Input02Value'
 
         # 選択モデル
-        model_name = dpg.get_value(input_value02_tag)
+        model_name = dpg_get_value(input_value02_tag)
 
         pos = dpg.get_item_pos(tag_node_name)
 
@@ -268,4 +270,4 @@ def set_setting_dict(self, node_id, setting_dict):
 
         model_name = setting_dict[input_value02_tag]
 
-        dpg.set_value(input_value02_tag, model_name)
+        dpg_set_value(input_value02_tag, model_name)

node/deep_learning_node/node_monocular_depth_estimation.py

@@ -6,6 +6,8 @@
 import numpy as np
 import dearpygui.dearpygui as dpg
 
+from node_editor.util import dpg_get_value, dpg_set_value
+
 from node.node_abc import DpgNodeABC
 from node_editor.util import convert_cv_to_dpg
 
@@ -179,10 +181,10 @@ def update(
                 source_tag = connection_info[0] + 'Value'
                 destination_tag = connection_info[1] + 'Value'
                 # 値更新
-                input_value = int(dpg.get_value(source_tag))
+                input_value = int(dpg_get_value(source_tag))
                 input_value = max([self._min_val, input_value])
                 input_value = min([self._max_val, input_value])
-                dpg.set_value(destination_tag, input_value)
+                dpg_set_value(destination_tag, input_value)
             if connection_type == self.TYPE_IMAGE:
                 # 画像取得元のノード名(ID付き)を取得
                 connection_info_src = connection_info[0]
@@ -193,10 +195,10 @@ def update(
         frame = node_image_dict.get(connection_info_src, None)
 
         # CPU/GPU選択状態取得
-        provider = dpg.get_value(tag_provider_select_value_name)
+        provider = dpg_get_value(tag_provider_select_value_name)
 
         # モデル情報取得
-        model_name = dpg.get_value(input_value02_tag)
+        model_name = dpg_get_value(input_value02_tag)
         model_path = self._model_path_setting[model_name]
         model_class = self._model_class[model_name]
 
@@ -230,7 +232,7 @@ def update(
         if frame is not None and use_pref_counter:
             elapsed_time = time.perf_counter() - start_time
             elapsed_time = int(elapsed_time * 1000)
-            dpg.set_value(output_value02_tag,
+            dpg_set_value(output_value02_tag,
                           str(elapsed_time).zfill(4) + 'ms')
 
         # 描画
@@ -240,7 +242,7 @@ def update(
                 small_window_w,
                 small_window_h,
             )
-            dpg.set_value(output_value01_tag, texture)
+            dpg_set_value(output_value01_tag, texture)
 
         return frame, result
 
@@ -252,7 +254,7 @@ def get_setting_dict(self, node_id):
         input_value02_tag = tag_node_name + ':' + self.TYPE_TEXT + ':Input02Value'
 
         # 選択モデル
-        model_name = dpg.get_value(input_value02_tag)
+        model_name = dpg_get_value(input_value02_tag)
 
         pos = dpg.get_item_pos(tag_node_name)
 
@@ -269,4 +271,4 @@ def set_setting_dict(self, node_id, setting_dict):
 
         model_name = setting_dict[input_value02_tag]
 
-        dpg.set_value(input_value02_tag, model_name)
+        dpg_set_value(input_value02_tag, model_name)