Yu-Kai Huang joyhuang9473
joyhuang9473
/ trace_detection_train.txt
Last active
February 25, 2019 15:26
https://github.com/TuSimple/simpledet/blob/master/detection_train.py
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| - [detection_train.py](https://github.com/TuSimple/simpledet/blob/master/detection_train.py) | |
| - | |
| ``` | |
| pGen, pKv, pRpn, pRoi, pBbox, pDataset, pModel, pOpt, pTest, \ | |
| transform, data_name, label_name, metric_list = config.get_config(is_train=True | |
| ``` | |
| [link](https://github.com/TuSimple/simpledet/blob/master/detection_train.py#L20) | |
| - [config/tridentnet_r101v2c4_c5_1x.py](https://github.com/TuSimple/simpledet/blob/master/config/tridentnet_r101v2c4_c5_1x.py#L11) | |
| - from models.tridentnet.builder import TridentFasterRcnn as Detector [link](https://github.com/TuSimple/simpledet/blob/master/config/tridentnet_r50v2c4_c5_1x.py#L1) | |
| - |
joyhuang9473
/ trace_export_inference_graph_stripped.txt
Created
January 31, 2019 09:32
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| - [export_inference_graph.py](https://github.com/tensorflow/models/blob/master/research/object_detection/export_inference_graph.py#L143) | |
| - exporter.export_inference_graph | |
| - [exporter.py](https://github.com/tensorflow/models/blob/master/research/object_detection/exporter.py#L414) | |
| - export_inference_graph() | |
| - detection_model = model_builder.build [link](https://github.com/tensorflow/models/blob/master/research/object_detection/exporter.py#L438) | |
| - [builders/model_builder.py](https://github.com/tensorflow/models/blob/master/research/object_detection/builders/model_builder.py#L101) | |
| - build(model_config, is_training, add_summaries=True) | |
| - _build_ssd_model(model_config.ssd, is_training, add_summaries) [link](https://github.com/tensorflow/models/blob/master/research/object_detection/builders/model_builder.py#L119) | |
| - feature_extractor = _build_ssd_feature_extractor( [link](https://github.com/tensorflow/models/blob/master/research/object_detection/builders/model_builder.py#L233) |
joyhuang9473
/ trace_export_inference_graph.txt
Last active
February 14, 2019 07:22
Trace code in export_inference_graph.py https://github.com/tensorflow/models/tree/master/research/object_detection
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| - [export_inference_graph.py](https://github.com/tensorflow/models/blob/master/research/object_detection/export_inference_graph.py#L143) | |
| - exporter.export_inference_graph | |
| - [exporter.py](https://github.com/tensorflow/models/blob/master/research/object_detection/exporter.py#L414) | |
| - export_inference_graph() | |
| - detection_model = model_builder.build [link](https://github.com/tensorflow/models/blob/master/research/object_detection/exporter.py#L438) | |
| - [builders/model_builder.py](https://github.com/tensorflow/models/blob/master/research/object_detection/builders/model_builder.py#L101) | |
| - build(model_config, is_training, add_summaries=True) | |
| - _build_ssd_model(model_config.ssd, is_training, add_summaries) [link](https://github.com/tensorflow/models/blob/master/research/object_detection/builders/model_builder.py#L119) | |
| - feature_extractor = _build_ssd_feature_extractor( [link](https://github.com/tensorflow/models/blob/master/research/object_detection/builders/model_builder.py#L233) |
joyhuang9473
/ bar.c
Last active
September 18, 2018 06:50
Owen Hsu: Introduction to gdb https://www.slideshare.net/owenhsu/introduction-to-gdb-3790833
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| #include <stdlib.h> | |
| void bar(int *val) { | |
| *val = 11; | |
| val = NULL; | |
| *val = 17; | |
| } |
joyhuang9473
/ gdb_hello.log
Last active
September 18, 2018 03:43
Owen Hsu: Introduction to gdb https://www.slideshare.net/owenhsu/introduction-to-gdb-3790833
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| user@pc:~$ gcc -Wall -g hello.c -o hello | |
| user@pc:~$ gdb hello | |
| GNU gdb (Ubuntu 7.11.1-0ubuntu1~16.5) 7.11.1 | |
| Copyright (C) 2016 Free Software Foundation, Inc. | |
| License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html> | |
| This is free software: you are free to change and redistribute it. | |
| There is NO WARRANTY, to the extent permitted by law. Type "show copying" | |
| and "show warranty" for details. | |
| This GDB was configured as "x86_64-linux-gnu". |
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| config = { | |
| 'network': [ | |
| ('input', {}), | |
| ('conv1', {'W_size': 8, 'stride': 4, 'in': 4, 'out': 16}), | |
| ('conv2', {'W_size': 4, 'stride': 2, 'in': 16, 'out': 32}), | |
| ('fc1', {'num_relus': 256}), | |
| ('output', {}), | |
| ], | |
| 'input_size': [84, 84], # height, width | |
| 'num_actions': 4, |
joyhuang9473
/ create_n_read_tfrecord_with_opencv.py
Created
January 17, 2018 06:51
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| import tensorflow as tf | |
| import cv2 | |
| def int64_feature(value): | |
| return tf.train.Feature(int64_list=tf.train.Int64List(value=[value])) | |
| def int64_list_feature(value): | |
| return tf.train.Feature(int64_list=tf.train.Int64List(value=value)) | |
| def bytes_feature(value): |
joyhuang9473
/ gcc 5 on ubuntu 14.04
Created
March 21, 2017 10:16
— forked from beci/gcc 5 on ubuntu 14.04
use gcc 5.x on ubuntu 14.04
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| sudo add-apt-repository ppa:ubuntu-toolchain-r/test | |
| sudo apt-get update | |
| sudo apt-get install gcc-5 g++-5 | |
| sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 60 --slave /usr/bin/g++ g++ /usr/bin/g++-5 |
joyhuang9473
/ reader.py
Created
March 5, 2017 07:51
reader template: https://github.com/chiphuyen/tf-stanford-tutorials/blob/master/examples/05_csv_reader.py
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| """ | |
| """ | |
| import tensorflow as tf | |
| def batch_generator(filenames, BATCH_SIZE): | |
| """ filenames is the list of files you want to read from. | |
| In this case, it contains only heart.csv | |
| """ | |
| filename_queue = tf.train.string_input_producer(filenames) |
joyhuang9473
/ model.py
Created
March 5, 2017 07:43
TF model template: https://github.com/chiphuyen/tf-stanford-tutorials/blob/master/examples/04_word2vec_visualize.py
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| """ | |
| """ | |
| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function | |
| class Model: | |
| """ Build the graph for model """ | |
| def __init__(self, vocab_size, embed_size, batch_size, num_sampled, learning_rate): |
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