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/* | |
* camera.ino - Simple camera example sketch | |
* Copyright 2018, 2022 Sony Semiconductor Solutions Corporation | |
* | |
* This library is free software; you can redistribute it and/or | |
* modify it under the terms of the GNU Lesser General Public | |
* License as published by the Free Software Foundation; either | |
* version 2.1 of the License, or (at your option) any later version. | |
* | |
* This library is distributed in the hope that it will be useful, |
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images = np.zeros((1, 3, 360, 640), dtype=np.float32) | |
masks = np.ones((1, 1, 360, 640), dtype=np.float32) | |
torch.onnx.export(nnet.model, | |
(images, masks), | |
"model_float32.onnx", | |
export_params=True, | |
opset_version=11, | |
do_constant_folding=True, | |
input_names = ['input_rgb','input_mask'], |
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ARG PYTORCH="1.5" | |
ARG CUDA="10.1" | |
ARG CUDNN="7" | |
FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel | |
ENV TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0+PTX" | |
ENV TORCH_NVCC_FLAGS="-Xfatbin -compress-all" | |
ENV CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" |
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- エヌビディアの手島でございます
- この記事はOpenCVの画像処理をGPU(CUDA)で高速化する - Qiita(以降「元記事」)を読んで、最後に書かれているリクエストを検証したものです。
OpenCVでの処理(リサイズなど)を、簡単にマルチコア化する方法をどなたかご存知でしたら教えて頂けないでしょうか? TBBを使ってスレッドを作る方法は色々見つかったのですが、単にcv::resize()をマルチコア動作で高速化させたいです。
- Python バインディングが遅い
- OpenCV の
resize
はずっと昔からマルチコア対応している
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import tensorflow as tf | |
import numpy as np | |
import mrcnn.model as modellib # https://github.com/matterport/Mask_RCNN/ | |
from mrcnn.config import Config | |
import keras.backend as keras | |
PATH_TO_SAVE_FROZEN_PB ="./" | |
FROZEN_NAME ="saved_model.pb" | |
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you need to get below files first.
- model: https://github.com/google/mediapipe/blob/master/mediapipe/models/face_detection_front.tflite
- flatc: https://github.com/tensorflow/tensorflow/blob/v1.14.0/tensorflow/lite/tools/visualize.py#L38
- shema: https://github.com/tensorflow/tensorflow/blob/v1.14.0/tensorflow/lite/tools/visualize.py#L37
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