我无法运行您的某篇文章的代码，请帮我运行代码 [英] I am not able to run code of one of your article please help me to run the code

问题描述

https://www.codeproject.com/Articles / 3993967 /应用 - 长短期内存 - 视频 - 分类

为视频分类问题应用长短期内存

github代码给出了，我无法运行代码请帮助我解决这些问题。

代码链接

https://github.com/SBoyNumber1/LSTM-video-classification





Apriorit Inc，Semyon Boyko请回复我的询问



我尝试了什么：



我已经在网站上给出了适当结构的代码数据集。请帮我运行代码。当我运行下面的代码时，会显示错误。我无法理解sys.argv在代码中做了什么。请

 runfile（'C：/Users/Dell/Desktop/LSTM-video-classification-master/data/extract_files.py'， wdir ='C：/ Users / Dell / Desktop / LSTM-video-classification-master / data'）
为Commercial_train_0生成91帧
为Commercial_train_1生成91帧
为Commercial_train_10生成91帧
为Commercial_train_11生成91帧
为Commercial_train_12生成91帧
为Commercial_train_13生成91帧
为Commercial_train_2生成91帧
为Commercial_train_3生成91帧
生成89帧for Commercial_train_4 
为Commercial_train_5生成91帧
为Commercial_train_6生成91帧
为Commercial_train_7生成91帧
为Commercial_train_8生成89帧
为Commercial_train_9 $生成89帧b $ b为News_train_1_0生成90帧
为News_train_1_12生成91帧
为News_t生成91帧rain_1_15 
为News_train_1_18生成91帧
为News_train_1_21生成89帧
为News_train_1_24生成89帧
为News_train_1_27生成91帧
为News_train_1_3 
生成91帧为News_train_1_30 
生成了89帧为News_train_1_33生成了91帧
为News_train_1_36生成了90帧
为News_train_1_39生成了91帧
为News_train_1_42生成了91帧
为News_train_1_45生成了90帧
为News_train_1_48生成91帧
为News_train_1_51生成89帧
为News_train_1_54生成90帧
为News_train_1_57生成91帧
为News_train_1_6生成90帧
生成91为News_train_1_9 
为News_train_2_0生成91帧
为News_train_2_12生成91帧
为News_train_2_15生成91帧
为News_train_2_18生成91帧
为News_train_2_21生成91帧b $ b为News_train_2_24 
生成91帧为News_train_2_27生成91帧
为News_train_2_3生成91帧
为News_train_2_30生成89帧
为News_train_2_33生成89帧
为News_train_2_36生成91帧
为News_train_2_39生成90帧
为News_train_2_42生成91帧
为News_train_2_45生成91帧
为News_train_2_48生成89帧
为News_train_2_51生成91帧
生成News_train_2_54 
生成91帧News_train_2_57生成91帧
为News_train_2_6生成91帧
为News_train_2_9生成89帧
为News_train_3_0生成91帧
为News_train_3_12生成91帧b $ b为News_train_3_15生成91帧
为News_train_3_18生成90帧
为News_train_3_21生成91帧
为News_train_3_24生成91帧
为News_train_3_27生成91帧
生成91News_train_3_3 
的帧为News_train_3_30生成89帧
为News_train_3_33生成91帧
为News_train_3_36生成91帧
为News_train_3_39生成91帧
为News_train_3_42 $ b生成91帧$ b为News_train_3_45生成91帧
为News_train_3_6生成91帧
为News_train_3_9生成91帧
为Commercial_test_0生成91帧
为Commercial_test_1生成91帧
生成91帧for Commercial_test_2 
为Commercial_test_3生成91帧
为Commercial_test_4生成91帧
为Commercial_test_5生成89帧
为News_train_3_48生成90帧
为News_train_3_51生成91帧
为News_train_3_54生成89帧
为News_train_3_57生成89帧
为News_train_4_0生成91帧
为News_train_4_12生成91帧
为News_train_4_15生成91帧
生成91 fr a_for News_train_4_18 
为News_train_4_21生成91帧
为News_train_4_24生成91帧
为News_train_4_27生成91帧
为News_train_4_3生成91帧
为News_train_4_30 $ b生成91帧$ b为News_train_4_33生成91帧
为News_train_4_36生成91帧
为News_train_4_39生成91帧
为News_train_4_42生成89帧
为News_train_4_45生成91帧
生成91帧for News_train_4_48 
为News_train_4_51生成89帧
为News_train_4_54生成89帧
为News_train_4_57生成89帧
为News_train_4_6生成91帧
为News_train_4_9生成91帧
提取并写入100个视频文件。 
用法：python extract_filese.py [videos extession] 
示例：python extract_files.py mp4 
 
 runfile（'C：/ Users / Dell / Desktop / LSTM- video-classification -master / data.py'，wdir ='C：/ Users / Dell / Desktop / LSTM-video-classification-master'）
 
 
 
 runfile（'C： /Users/Dell/Desktop/LSTM-video-classification-master/train.py',wdir ='C：/ Users / Dell / Desktop / LSTM-video-classification-master'）
重装上阵的模块：processor 
用法：python train.py sequence_length class_limit image_height image_width 
示例：python train.py 75 2 720 1280 
回溯（最近一次调用最后一次）：
 
文件< ; ipython-input-19-091ab9c812f8>，第1行，< module> 
 runfile（'C：/Users/Dell/Desktop/LSTM-video-classification-master/train.py',wdir ='C：/ Users / Dell / Desktop / LSTM-video-classification-master'） 
 
文件D：\ Users \Dell\Anaconda3 \lib \site-packages \ spyder_kernels \customize\spydercustomize.py，第704行，在runfile中
 execfile（filename，namespace）
 
文件D：\ Users \Dell\Anaconda3 \lib \site-packages \ spyder_kernels \customize\spydercustomize.py，line 108，在execfile中
 exec（compile（f.read（），filename，'e​​xec'），命名空间）
 
文件C：/ Users / Dell / Desktop / LSTM-video- classification-master / train.py，第125行，< module> 
 main（）
 
主要
 extract_features中的文件C：/Users/Dell/Desktop/LSTM-video-classification-master/train.py，第119行（ seq_length = seq_length，class_limit = class_limit，image_shape = image_shape）
 
文件C：\ Users \Dell\Desktop\LSTM-video-classification-master\extract_features.py，line 20，在extract_features中
 data = DataSet（seq_length = seq_length，class_limit = class_limit，image_shape = image_shape）
 
文件C：\ Users \Dell \Desktop \ LSTM-video -classification-master\data.py，第50行，在__init__ 
 self.classes = self.get_classes（）
 
文件C：\ Users \Dell\Desktop \ LSTM-video-classification-master\data.py，第82行，在get_classes 
中如果item [1]不在类中：
 
 IndexError：list index超出范围
 
 
 
 
 
 runfile（'C：/Users/Dell/Desktop/LSTM-video-classification-master/train.py',wdir = C：/用户/戴尔/桌面/ LS TM-video-classification-master'）
重装上阵模块：模型，数据，处理器，extract_features，提取器
 Traceback（最近一次调用最后一次）：
 
文件< ipython -input-22-091ab9c812f8>，第1行，< module> 
 runfile（'C：/Users/Dell/Desktop/LSTM-video-classification-master/train.py',wdir ='C：/ Users / Dell / Desktop / LSTM-video-classification-master'） 
 
文件D：\ Users \Dell\Anaconda3 \lib \site-packages \ spyder_kernels \customize\spydercustomize.py，第704行，在runfile中
 execfile（filename，namespace）
 
文件D：\ Users \Dell\Anaconda3 \lib \site-packages \ spyder_kernels \customize\spydercustomize.py，line 108，在execfile中
 exec（compile（f.read（），filename，'e​​xec'），命名空间）
 
文件C：/ Users / Dell / Desktop / LSTM-video- classification-master / train.py，第129行，< module> 
 main（）
 
主
 extract_features中的文件C：/Users/Dell/Desktop/LSTM-video-classification-master/train.py，第123行（ seq_length = seq_length，class_limit = class_limit，image_shape = image_shape）
 
文件C：\ Users \Dell\Desktop\LSTM-video-classification-master\extract_features.py，line 20，在extract_features中
 data = DataSet（seq_length = seq_length，class_limit = class_limit，image_shape = image_shape）
 
文件C：\ Users \Dell \Desktop \ LSTM-video -classification-master\data.py，第50行，在__init__ 
 self.classes = self.get_classes（）
 
文件C：\ Users \Dell\Desktop \ LSTM-video-classification-master\data.py，第82行，在get_classes 
中如果item [1]不在类中：
 
 IndexError：列表索引超出范围

解决方案

联系作者的最佳方式是使用文章底部的论坛：

为视频分类问题应用长短期内存 [ ^ ]

https://www.codeproject.com/Articles/3993967/Applying-Long-Short-Term-Memory-for-Video-Classifi
Applying Long Short-Term Memory for Video Classification Issues
github code is given, and I am not able to run the code Please help me out in these matter.
Link of code
https://github.com/SBoyNumber1/LSTM-video-classification


Apriorit Inc, Semyon Boyko Please reply for my query

What I have tried:

I have made the data set of code in proper structure given on website. Please help me to run the code. When I run the code below errors were shown. I am not able to understand what sys.argv is doing in the code. Please

runfile('C:/Users/Dell/Desktop/LSTM-video-classification-master/data/extract_files.py', wdir='C:/Users/Dell/Desktop/LSTM-video-classification-master/data')
Generated 91 frames for Commercial_train_0
Generated 91 frames for Commercial_train_1
Generated 91 frames for Commercial_train_10
Generated 91 frames for Commercial_train_11
Generated 91 frames for Commercial_train_12
Generated 91 frames for Commercial_train_13
Generated 91 frames for Commercial_train_2
Generated 91 frames for Commercial_train_3
Generated 89 frames for Commercial_train_4
Generated 91 frames for Commercial_train_5
Generated 91 frames for Commercial_train_6
Generated 91 frames for Commercial_train_7
Generated 89 frames for Commercial_train_8
Generated 89 frames for Commercial_train_9
Generated 90 frames for News_train_1_0
Generated 91 frames for News_train_1_12
Generated 91 frames for News_train_1_15
Generated 91 frames for News_train_1_18
Generated 89 frames for News_train_1_21
Generated 89 frames for News_train_1_24
Generated 91 frames for News_train_1_27
Generated 91 frames for News_train_1_3
Generated 89 frames for News_train_1_30
Generated 91 frames for News_train_1_33
Generated 90 frames for News_train_1_36
Generated 91 frames for News_train_1_39
Generated 91 frames for News_train_1_42
Generated 90 frames for News_train_1_45
Generated 91 frames for News_train_1_48
Generated 89 frames for News_train_1_51
Generated 90 frames for News_train_1_54
Generated 91 frames for News_train_1_57
Generated 90 frames for News_train_1_6
Generated 91 frames for News_train_1_9
Generated 91 frames for News_train_2_0
Generated 91 frames for News_train_2_12
Generated 91 frames for News_train_2_15
Generated 91 frames for News_train_2_18
Generated 91 frames for News_train_2_21
Generated 91 frames for News_train_2_24
Generated 91 frames for News_train_2_27
Generated 91 frames for News_train_2_3
Generated 89 frames for News_train_2_30
Generated 89 frames for News_train_2_33
Generated 91 frames for News_train_2_36
Generated 90 frames for News_train_2_39
Generated 91 frames for News_train_2_42
Generated 91 frames for News_train_2_45
Generated 89 frames for News_train_2_48
Generated 91 frames for News_train_2_51
Generated 90 frames for News_train_2_54
Generated 91 frames for News_train_2_57
Generated 91 frames for News_train_2_6
Generated 89 frames for News_train_2_9
Generated 91 frames for News_train_3_0
Generated 91 frames for News_train_3_12
Generated 91 frames for News_train_3_15
Generated 90 frames for News_train_3_18
Generated 91 frames for News_train_3_21
Generated 91 frames for News_train_3_24
Generated 91 frames for News_train_3_27
Generated 91 frames for News_train_3_3
Generated 89 frames for News_train_3_30
Generated 91 frames for News_train_3_33
Generated 91 frames for News_train_3_36
Generated 91 frames for News_train_3_39
Generated 91 frames for News_train_3_42
Generated 91 frames for News_train_3_45
Generated 91 frames for News_train_3_6
Generated 91 frames for News_train_3_9
Generated 91 frames for Commercial_test_0
Generated 91 frames for Commercial_test_1
Generated 91 frames for Commercial_test_2
Generated 91 frames for Commercial_test_3
Generated 91 frames for Commercial_test_4
Generated 89 frames for Commercial_test_5
Generated 90 frames for News_train_3_48
Generated 91 frames for News_train_3_51
Generated 89 frames for News_train_3_54
Generated 89 frames for News_train_3_57
Generated 91 frames for News_train_4_0
Generated 91 frames for News_train_4_12
Generated 91 frames for News_train_4_15
Generated 91 frames for News_train_4_18
Generated 91 frames for News_train_4_21
Generated 91 frames for News_train_4_24
Generated 91 frames for News_train_4_27
Generated 91 frames for News_train_4_3
Generated 91 frames for News_train_4_30
Generated 91 frames for News_train_4_33
Generated 91 frames for News_train_4_36
Generated 91 frames for News_train_4_39
Generated 89 frames for News_train_4_42
Generated 91 frames for News_train_4_45
Generated 91 frames for News_train_4_48
Generated 89 frames for News_train_4_51
Generated 89 frames for News_train_4_54
Generated 89 frames for News_train_4_57
Generated 91 frames for News_train_4_6
Generated 91 frames for News_train_4_9
Extracted and wrote 100 video files.
Usage: python extract_filese.py [videos extession]
Example: python extract_files.py mp4

runfile('C:/Users/Dell/Desktop/LSTM-video-classification-master/data.py', wdir='C:/Users/Dell/Desktop/LSTM-video-classification-master')



runfile('C:/Users/Dell/Desktop/LSTM-video-classification-master/train.py', wdir='C:/Users/Dell/Desktop/LSTM-video-classification-master')
Reloaded modules: processor
Usage: python train.py sequence_length class_limit image_height image_width
Example: python train.py 75 2 720 1280
Traceback (most recent call last):

  File "<ipython-input-19-091ab9c812f8>", line 1, in <module>
    runfile('C:/Users/Dell/Desktop/LSTM-video-classification-master/train.py', wdir='C:/Users/Dell/Desktop/LSTM-video-classification-master')

  File "D:\Users\Dell\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 704, in runfile
    execfile(filename, namespace)

  File "D:\Users\Dell\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 108, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users/Dell/Desktop/LSTM-video-classification-master/train.py", line 125, in <module>
    main()

  File "C:/Users/Dell/Desktop/LSTM-video-classification-master/train.py", line 119, in main
    extract_features(seq_length=seq_length, class_limit=class_limit, image_shape=image_shape)

  File "C:\Users\Dell\Desktop\LSTM-video-classification-master\extract_features.py", line 20, in extract_features
    data = DataSet(seq_length=seq_length, class_limit=class_limit, image_shape=image_shape)

  File "C:\Users\Dell\Desktop\LSTM-video-classification-master\data.py", line 50, in __init__
    self.classes = self.get_classes()

  File "C:\Users\Dell\Desktop\LSTM-video-classification-master\data.py", line 82, in get_classes
    if item[1] not in classes:

IndexError: list index out of range





runfile('C:/Users/Dell/Desktop/LSTM-video-classification-master/train.py', wdir='C:/Users/Dell/Desktop/LSTM-video-classification-master')
Reloaded modules: models, data, processor, extract_features, extractor
Traceback (most recent call last):

  File "<ipython-input-22-091ab9c812f8>", line 1, in <module>
    runfile('C:/Users/Dell/Desktop/LSTM-video-classification-master/train.py', wdir='C:/Users/Dell/Desktop/LSTM-video-classification-master')

  File "D:\Users\Dell\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 704, in runfile
    execfile(filename, namespace)

  File "D:\Users\Dell\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 108, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users/Dell/Desktop/LSTM-video-classification-master/train.py", line 129, in <module>
    main()

  File "C:/Users/Dell/Desktop/LSTM-video-classification-master/train.py", line 123, in main
    extract_features(seq_length=seq_length, class_limit=class_limit, image_shape=image_shape)

  File "C:\Users\Dell\Desktop\LSTM-video-classification-master\extract_features.py", line 20, in extract_features
    data = DataSet(seq_length=seq_length, class_limit=class_limit, image_shape=image_shape)

  File "C:\Users\Dell\Desktop\LSTM-video-classification-master\data.py", line 50, in __init__
    self.classes = self.get_classes()

  File "C:\Users\Dell\Desktop\LSTM-video-classification-master\data.py", line 82, in get_classes
    if item[1] not in classes:

IndexError: list index out of range

解决方案

The best way to contact the author is to use the forum on bottom of article:
Applying Long Short-Term Memory for Video Classification Issues[^]

这篇关于我无法运行您的某篇文章的代码，请帮我运行代码的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！