Edge TPU compiler comment

export.py

@@ -17,7 +17,7 @@
 TensorFlow.js               | `tfjs`                        | yolov5s_web_model/
 
 Usage:
-    $ python path/to/export.py --weights yolov5s.pt --include torchscript onnx coreml openvino saved_model tflite tfjs
+    $ python path/to/export.py --weights yolov5s.pt --include torchscript onnx openvino engine coreml tflite ...
 
 Inference:
     $ python path/to/detect.py --weights yolov5s.pt                 # PyTorch
@@ -308,7 +308,7 @@ def export_tflite(keras_model, im, file, int8, data, ncalib, prefix=colorstr('Te
 def export_edgetpu(keras_model, im, file, prefix=colorstr('Edge TPU:')):
     # YOLOv5 Edge TPU export https://coral.ai/docs/edgetpu/models-intro/
     try:
-        cmd = 'edgetpu_compiler --version'
+        cmd = 'edgetpu_compiler --version'  # install https://coral.ai/docs/edgetpu/compiler/
         out = subprocess.run(cmd, shell=True, capture_output=True, check=True)
         ver = out.stdout.decode().split()[-1]
         LOGGER.info(f'\n{prefix} starting export with Edge TPU compiler {ver}...')

models/common.py

@@ -376,8 +376,8 @@ def wrap_frozen_graph(gd, inputs, outputs):
             elif tflite:  # https://www.tensorflow.org/lite/guide/python#install_tensorflow_lite_for_python
                 if 'edgetpu' in w.lower():  # Edge TPU
                     LOGGER.info(f'Loading {w} for TensorFlow Lite Edge TPU inference...')
-                    import tflite_runtime.interpreter as tfli
-                    delegate = {'Linux': 'libedgetpu.so.1',  # install https://coral.ai/software/#edgetpu-runtime
+                    import tflite_runtime.interpreter as tfli  # install https://coral.ai/software/#edgetpu-runtime
+                    delegate = {'Linux': 'libedgetpu.so.1',
                                 'Darwin': 'libedgetpu.1.dylib',
                                 'Windows': 'edgetpu.dll'}[platform.system()]
                     interpreter = tfli.Interpreter(model_path=w, experimental_delegates=[tfli.load_delegate(delegate)])