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helloproject-ai
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continuous-integration/drone/push Build is passing Details

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yayoimizuha 2023-10-24 00:16:37 +09:00
parent 3b7ced3eb7
commit 289879c8dd
2 changed files with 8 additions and 3 deletions
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1
.drone.yml
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@ -16,6 +16,7 @@ steps:
PYTHONPATH: /drone/src/ PYTHONPATH: /drone/src/
DATA_DIR: /drone/src/data/ DATA_DIR: /drone/src/data/
commands: commands:
- git diff --name-only `git merge-base refs/remotes/origin/master HEAD`..HEAD | grep finetune/facenet_transfer_learning.py > /dev/null || exit 78
- python -m pip install -q -U pip - python -m pip install -q -U pip
- pip install -q torchsummary matplotlib pytorch-metric-learning torchinfo torch torchvision tqdm Pillow facenet-pytorch - pip install -q torchsummary matplotlib pytorch-metric-learning torchinfo torch torchvision tqdm Pillow facenet-pytorch
- apt update -qq - apt update -qq

10
test_script/onnx_cacher.py
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@ -1,11 +1,14 @@
from os import getcwd from os import getcwd
from os.path import join from os.path import join
from onnxruntime import InferenceSession, SessionOptions, __version__ from onnxruntime import InferenceSession, SessionOptions, __version__, get_all_providers, get_available_providers
from PIL import Image from PIL import Image
import numpy import numpy
print(get_all_providers())
print(get_available_providers())
onnx_session = InferenceSession( onnx_session = InferenceSession(
path_or_bytes="test_script/retinaface.onnx", path_or_bytes=r"retinaface.onnx",
providers=[ providers=[
'CUDAExecutionProvider', 'CUDAExecutionProvider',
('TensorrtExecutionProvider', { ('TensorrtExecutionProvider', {
@ -13,6 +16,7 @@ onnx_session = InferenceSession(
'trt_engine_cache_path': join(getcwd(), 'onnx_cache'), 'trt_engine_cache_path': join(getcwd(), 'onnx_cache'),
'trt_fp16_enable': True, 'trt_fp16_enable': True,
}), }),
'DmlExecutionProvider',
'CPUExecutionProvider' 'CPUExecutionProvider'
] ]
) )
@ -20,7 +24,7 @@ print(__version__)
image_arr = numpy.expand_dims(numpy.array( image_arr = numpy.expand_dims(numpy.array(
Image.open(r'C:\Users\tomokazu\CLionProjects\ameba_blog_downloader\manaka_test.jpg').convert('RGB')), 0).transpose( Image.open(r'C:\Users\tomokazu\CLionProjects\ameba_blog_downloader\manaka_test.jpg').convert('RGB')), 0).transpose(
0, 3, 1, 2).astype(numpy.float32) 0, 3, 1, 2).astype(numpy.float32)
image_arr /= 255.0 # image_arr /= 255.0
print(image_arr) print(image_arr)
print(image_arr.shape) print(image_arr.shape)
res = onnx_session.run(input_feed={'input': image_arr}, output_names=["bbox", "confidence", "landmark"]) res = onnx_session.run(input_feed={'input': image_arr}, output_names=["bbox", "confidence", "landmark"])