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Edge TPU compiler comment #6196

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Jan 5, 2022
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6 changes: 3 additions & 3 deletions export.py
Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand Down Expand Up @@ -179,7 +179,7 @@ def export_engine(model, im, file, train, half, simplify, workspace=4, verbose=F
export_onnx(model, im, file, 12, train, False, simplify) # opset 12
model.model[-1].anchor_grid = grid
else: # TensorRT >= 8
check_version(trt.__version__, '7.0.0', hard=True) # require tensorrt>=8.0.0
check_version(trt.__version__, '8.0.0', hard=True) # require tensorrt>=8.0.0
export_onnx(model, im, file, 13, train, False, simplify) # opset 13
onnx = file.with_suffix('.onnx')
assert onnx.exists(), f'failed to export ONNX file: {onnx}'
Expand Down Expand Up @@ -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}...')
Expand Down
4 changes: 2 additions & 2 deletions models/common.py
Original file line number Diff line number Diff line change
Expand Up @@ -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)])
Expand Down