update

test_script/nvjpeg_infer.py

@@ -0,0 +1,31 @@
+import time
+import tkinter
+
+# import cv2
+from nvjpeg_decoder import decode
+from os import listdir, getcwd
+from os.path import join
+from numpy import array
+# from matplotlib import pyplot, figure
+# from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
+# import matplotlib_fontja
+from onnxruntime import InferenceSession
+
+onnx_path = r"C:\Users\tomokazu\RustroverProjects\ameba_blog_downloader\src\retinaface\resnet_retinaface.onnx"
+datadir = r"D:\helloproject-ai-data\blog_images"
+
+session = InferenceSession(
+    path_or_bytes=onnx_path,
+    # providers=[
+    #     # 'TensorrtExecutionProvider',
+    #     # 'CUDAExecutionProvider',
+    #     'CPUExecutionProvider'
+    # ]
+)
+for member in listdir(datadir):
+    for file in listdir(join(datadir, member)):
+        with open(join(datadir, member, file), mode="rb") as f:
+            (data, (width, height)) = decode((f.read()), "imagenet")
+            print(width, height)
+            image_arr = array(data).reshape((1, 3, height, width))  # .transpose([1, 2, 0])
+            session.run(input_feed={'input': image_arr}, output_names=['bbox', 'confidence', 'landmark'])

test_script/onnx_cacher.py

@@ -9,7 +9,7 @@ print(get_available_providers())
 
 onnx_session = InferenceSession(
     path_or_bytes=r"retinaface.onnx",
-    providers=[
+    providers=(
         'CUDAExecutionProvider',
         ('TensorrtExecutionProvider', {
             'trt_engine_cache_enable': True,
@@ -18,7 +18,7 @@ onnx_session = InferenceSession(
         }),
         'DmlExecutionProvider',
         'CPUExecutionProvider'
-    ]
+    )
 )
 print(__version__)
 image_arr = numpy.expand_dims(numpy.array(