This module aims to validate if the pilot made his flights online on the IVAO and VATSIM networks

Overview

SMPirepValidator

This module aims to validate if the pilot made his flights online on the IVAO and VATSIM networks

SMPirepValidator v.1.0 for phpVMS (tested under PHP 7.4 and phpVMS v5.5.2.72 by ProAvia https://github.com/ProAviaAZ/phpvms_5.5.2.72)

SmartModules addon module for phpVMS virtual airline system https://smartmodules.com.br

SmartModules addon modules are licenced under the following license: Creative Commons Attribution Non-commercial Share Alike (by-nc-sa) To view full license text visit http://creativecommons.org/licenses/by-nc-sa/3.0/

@author Ton Nascoli (SmartModules) @copyright (c) 2021, Ton Nascoli @license http://creativecommons.org/licenses/by-nc-sa/3.0/

Install:

  1. Download the ZIP file in your computer
  2. Extract the zip file into a folder of your choice
  3. Go to the folder where you extracted the files and access the phpvms_content folder
  4. Upload the ADMIN and CORE folders to your website by placing them in the phpvms root folder
  5. If asked to replace files, click YES

Install sm_onlinelog.sql

Just import the sm_onlinelog.sql file using your PhpMyAdmin

Create Custom Fields

For SMPirepValidator to work correctly, you´ll have to create custom fields to receive the VID and CID. These fields are not available by default in phpVMS. After creating them, your pilots will be able to access them in their profile.

  1. Access the phpVMS administrative panel

  2. On the side menu, click on Site & Settings

  3. Click on Profile Fields

  4. At the top of the side menu, click Add a Custom Field

  5. In pop-up window, enter the following values:

    Title: Ivao ID

    Field Type: Text

    Default value: leave blank

    Show in User Profile: YES

    Show During Registration: YES

    Required: {if you answer YES, it will be a required field when pilot registering}

Repeat the procedure in item 5 to include the field that will receive the CID. Just enter in the Title field: Vatsim ID.

Important: Inform Title exactly as described, considering the uppercases and spaces.

CRON JOB

This is the commonly used command line. If in doubt, consult your host provider

/usr/bin/GET https://{your_website}/{your_phpvms_folder}/action.php/SMPirepValidator/run_check

How does work?

After you enable CRON JOB, the module will add all the pilot's flight logs to the sm_onlinelog table. When validating the PIREP, the system will show if the LOG was found and will enable the administrator to see the LOG of the flight performed at IVAO/VATSIM.

ENJOY!!!!

NOTE

  1. Tested under PHP 7.4 and phpVMS v5.5.2.72

  2. We made a litle bit change to the original code of the pirep_list.php file to allow the IVAO / VATSIM flight log to be presented when validating PIREP. Therefore, it is important that you back up your file. This file is in the admin/templates folder. We have provided a backup of the original file in the bkp_original_file folder.

  3. This module is designed to take IVAO and VATSIM logs every 15 minutes and add them to the sm_onlinelog table.

Comments
  • Fine-Tuning with Pretrained Model in Docker Image

    Fine-Tuning with Pretrained Model in Docker Image

    Hi @zhang0jhon

    Thanks for the great work! The pretrained model you put in the docker image worked pretty well! However I want to fine-tune the parameters for my specific application. Is it possible to fine-tune the pretrained model? Since the model is different between the docker image and here, do you have the traning code for the docker version and/or do you have a fine-tuning code already?

    Thanks in advance!

    opened by JianYang93 15
  • 'label', does not exist in the graph

    'label', does not exist in the graph

    @zhang0jhon When running test.py with the model, i get error:

     Traceback (most recent call last):
      File "test.py", line 121, in <module>
        test(args)
      File "test.py", line 91, in test
        model = TextRecognition(args.pb_path, cfg.seq_len+1)
      File "test.py", line 23, in __init__
        self.init_model()
      File "test.py", line 37, in init_model
        self.label_ph = self.sess.graph.get_tensor_by_name('label:0')
      File "/home/home/anaconda3/envs/p3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3972, in get_tensor_by_name
        return self.as_graph_element(name, allow_tensor=True, allow_operation=False)
      File "/home/home/anaconda3/envs/p3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3796, in as_graph_element
        return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
      File "/home/home/anaconda3/envs/p3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3838, in _as_graph_element_locked
        "graph." % (repr(name), repr(op_name)))
    KeyError: "The name 'label:0' refers to a Tensor which does not exist. The operation, 'label', does not exist in the graph."
    
    opened by ghost 9
  • Default MaxPoolingOp only supports NHWC on device type CPU

    Default MaxPoolingOp only supports NHWC on device type CPU

    你好: 请问我再运行完python flaskapp.py,上传图片之后,进行预测的时候,会显示下面的错误,请问这是什么原因导致的? tensorflow.python.framework.errors_impl.InvalidArgumentError: Default MaxPoolingOp only supports NHWC on device type CPU [[node pool0/MaxPool (defined at /tensor_flow/OCRSpace/ocr/ocr/text_detection.py:29) ]]

    Original stack trace for 'pool0/MaxPool':

    请问应该怎么修改呢?多谢。。。

    opened by Springzcf 6
  • 可识别字符长度改为16

    可识别字符长度改为16

    seq_len是单个文本行最多可识别的字符数,是这个意思吧。 我现在想训一个短文本行的模型,最长seq_len设置为16,请问还需要修改哪些地方? 直接改为16报错,报ValueRrror,维度不匹配, 具体错误为cannot feed value of shape(16,33) for Tensor 'label:0', which has shape(?,17) 麻烦您指点一下,多谢

    opened by Bachelorwangwei 2
  • 关于识别的问题

    关于识别的问题

    假设已经定位到文字部分(暂不考虑定位方法),若采用AttentionOCR去识别,识别结果是针对图片中文字整体识别还是针对图片中的文字一个一个进行识别,因为之前采用crnn-ctc的模型是对图片中的文字一起识别,但是我看到您的images文件夹中图片有标识每一个汉字的识别概率,不知道我表达清楚没有^~^

    opened by FortuneStar 2
  • Network does not predict EOS token

    Network does not predict EOS token

    Hello, I have trained this network for about 80k steps but even though it started to detect a lot of the text parts it never predicted the EOS token. How much did you train it? Do I need some special post-processing?

    Thank you for the awesome network 👍

    opened by ionutscorta 1
  • Unable to pull from the docker hub repository you have mentioned

    Unable to pull from the docker hub repository you have mentioned

    I am unable to pull from the docker hub repository that you have mentioned. When I executed

    docker pull zhang0jhon/demo:ocr

    I got an error saying:

    Error response from daemon: pull access denied for zhang0jhon/demo:ocr, repository does not exist or may require docker login

    Is the repository still existing or have you given pull access to all?

    opened by varshaneya 1
  • docker运行demo时内存不够怎么配置

    docker运行demo时内存不够怎么配置

    W tensorflow/core/common_runtime/bfc_allocator.cc:211] Allocator (GPU_0_bfc) ran out of memory trying to allocate 358.89MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.

    普通显卡 tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties: name: GeForce GT 1030 major: 6 minor: 1 memoryClockRate(GHz): 1.5185 pciBusID: 0000:01:00.0 totalMemory: 1.95GiB freeMemory: 1.63GiB

    opened by bigkun 1
  • abcnet accuracy

    abcnet accuracy

    I have to questions. First what e2e accuracy mean? its accuracy for detection and recognition? And det-hmean is only for detection? And second on wich datasets was this model trained?

    opened by jdavidd 0
  • Problems on how to calculate the probs in text recongnition

    Problems on how to calculate the probs in text recongnition

    Thanks for your wonderful work! I observe that the text recongnition network outputs the text and probabilities. I wonder how the probilities calculate and what's the range of them? I can't find the funtion associated. Are the probilities just produced by the network? And they range in [0,1]? Thanks!

    opened by rainfall1998 0
  • I have some questions about training and testing

    I have some questions about training and testing

       First and foremost, thanks to you opensource the awesome STR algorithm,I have some questions about training and testing.
    

    I cope the checkpoint from the docker image, And I find detecting and recognition separted two model, one is ICDAR_0.7.pb, another is text_recognition_5435.pb. this mode is not apropriate this repo code. Hence I train my model through dataset.py genderating icdar_datasets.npy , with a lot of reading code, I find that the test.py can not work.it appear the error: 2021-06-16 15:01:59.018589: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7 2021-06-16 15:01:59.233909: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR 2021-06-16 15:01:59.261653: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR Traceback (most recent call last): File "/home/alan/anaconda3/envs/AttentionOCR/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1356, in _do_call return fn(*args) File "/home/alan/anaconda3/envs/AttentionOCR/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1341, in _run_fn options, feed_dict, fetch_list, target_list, run_metadata) File "/home/alan/anaconda3/envs/AttentionOCR/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1429, in _call_tf_sessionrun run_metadata) tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found. (0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above. [[{{node InceptionV4/InceptionV4/Conv2d_1a_3x3/Conv2D}}]] (1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above. [[{{node InceptionV4/InceptionV4/Conv2d_1a_3x3/Conv2D}}]] [[sequence_preds/_17]]

    opened by alan-img 0
  • train.py error    ModelDescBase?

    train.py error ModelDescBase?

    Traceback (most recent call last): File "train.py", line 81, in train() File "train.py", line 64, in train starting_epoch=cfg.starting_epoch File "/usr/local/lib/python3.6/dist-packages/tensorpack/train/config.py", line 119, in init assert_type(model, ModelDescBase, 'model') File "/usr/local/lib/python3.6/dist-packages/tensorpack/train/config.py", line 107, in assert_type name, tp.name, v.class.name) AssertionError: model has to be type 'ModelDescBase', but an object of type 'AttentionOCR' found.

    opened by xianzhe-741 0
  • Formulae miscalculation

    Formulae miscalculation

    ZhangOjhon your pre-trained model is gr8 !! for recognising characters generically. gr8 work it would be nice if you share the config file which includes the values used for the hyper parameters.
    I went through your code I just found out this formula discrepancy with the one in Bahadanus attention paper. 1.) the hidden state derived from the lstm decoder layer should only be given to the softmax. But in the code the attention_feature, prev_wemb, hidden_layer is concatenated and then given to the softmax. It would be helpful if you provide the explanation of why the formula is altered so and so. Thanks in advance.

    opened by deepakacl 0
  • What's is the license information of this project?

    What's is the license information of this project?

    Hi, I would love to use this amazing project for my project. Does it has MIT license? If yes, can you add the license to the repo? It will encourage people to use your amazing ocr model in their projects as well.

    opened by JC1DA 0
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