Tensorflow Object Detection API
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  • 上傳者: Kuann Hung,
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步驟
1.
安裝 anaconda protobug
conda install -c anaconda protobuf
pip install pillow
pip install lxml
pip install Cython
pip install jupyter
pip install matplotlib
pip install pandas
pip install opencv-python
2.
Compile Protobufs and run setup.py
在 \models\research 目錄下執行 
protoc --python_out=. .\object_detection\protos\anchor_generator.proto .\object_detection\protos\argmax_matcher.proto .\object_detection\protos\bipartite_matcher.proto .\object_detection\protos\box_coder.proto .\object_detection\protos\box_predictor.proto .\object_detection\protos\eval.proto .\object_detection\protos\faster_rcnn.proto .\object_detection\protos\faster_rcnn_box_coder.proto .\object_detection\protos\grid_anchor_generator.proto .\object_detection\protos\hyperparams.proto .\object_detection\protos\image_resizer.proto .\object_detection\protos\input_reader.proto .\object_detection\protos\losses.proto .\object_detection\protos\matcher.proto .\object_detection\protos\mean_stddev_box_coder.proto .\object_detection\protos\model.proto .\object_detection\protos\optimizer.proto .\object_detection\protos\pipeline.proto .\object_detection\protos\post_processing.proto .\object_detection\protos\preprocessor.proto .\object_detection\protos\region_similarity_calculator.proto .\object_detection\protos\square_box_coder.proto .\object_detection\protos\ssd.proto .\object_detection\protos\ssd_anchor_generator.proto .\object_detection\protos\string_int_label_map.proto .\object_detection\protos\train.proto .\object_detection\protos\keypoint_box_coder.proto .\object_detection\protos\multiscale_anchor_generator.proto .\object_detection\protos\graph_rewriter.proto
設定環境變數 PYTHONPATH (要把 C:\tensorflow 更換成你的路徑)
set PYTHONPATH=C:\tensorflow\models;C:\tensorflow\models\research;C:\tensorflow\models\research\slim
 
然後開始 Build & Install
python setup.py build
python setup.py install
3.
檢查是否成功
切換至 models\research\object_detection 執行
jupyter notebook object_detection_tutorial.ipynb
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    資料夾 :
    發表時間 :
    2018-10-14 22:16:38
    觀看數 :
    123
    發表人 :
    Kuann Hung
    部門 :
    老洪的 IT 學習系統
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