Add edgetpu_compiler checks (#6218)

* Add `edgetpu_compiler` checks

* Update export.py

* Update export.py

* Update export.py

* Update export.py

* Update export.py

* Update export.py

export.py

@@ -41,6 +41,7 @@
 import argparse
 import json
 import os
+import platform
 import subprocess
 import sys
 import time
@@ -307,11 +308,15 @@ 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'  # install https://coral.ai/docs/edgetpu/compiler/
+        cmd = 'edgetpu_compiler --version'
+        help = 'See https://coral.ai/docs/edgetpu/compiler/'
+        assert platform.system() == 'Linux', f'export only supported on Linux. {help}'
+        assert subprocess.run(cmd, shell=True).returncode == 0, f'export requires edgetpu-compiler. {help}'
         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}...')
-        f = str(file).replace('.pt', '-int8_edgetpu.tflite')
+        f = str(file).replace('.pt', '-int8_edgetpu.tflite')  # Edge TPU model
         f_tfl = str(file).replace('.pt', '-int8.tflite')  # TFLite model
 
         cmd = f"edgetpu_compiler -s {f_tfl}"
@@ -434,7 +439,7 @@ def run(data=ROOT / 'data/coco128.yaml',  # 'dataset.yaml path'
     # TensorFlow Exports
     if any(tf_exports):
         pb, tflite, edgetpu, tfjs = tf_exports[1:]
-        if (tflite or edgetpu) and int8:  # TFLite --int8 bug https://github.com/ultralytics/yolov5/issues/5707
+        if int8 or edgetpu:  # TFLite --int8 bug https://github.com/ultralytics/yolov5/issues/5707
             check_requirements(('flatbuffers==1.12',))  # required before `import tensorflow`
         assert not (tflite and tfjs), 'TFLite and TF.js models must be exported separately, please pass only one type.'
         model = export_saved_model(model, im, file, dynamic, tf_nms=nms or agnostic_nms or tfjs,