<div dir="ltr">Don't forget to also research some things (or maybe other developers who know will comment on this thread right away), that:<br><ol><li>Even when users want to train a model themselves, the environment in Python Plugin wouldn't make it easy e.g. for running on GPU</li><li>Designing a network is an art in itself. The goal of the plugin should be clear, to facilitate users who are familiar with DL or for general QGIS users? to create really good models or to apply the models? (I feel that if it is the first, QGIS is not the best framework to do it)</li><li>Transfer learning is not out of the box (I wrote my thesis about this). It depends on many things from the architecture itself to the data that it was originally trained on. Things like this would not interest general QGIS users in my opinion.</li></ol><div>It would also help if you make more detailed use cases so people would understand about what this plugin will do.</div><div><br></div><div>Good luck!<br><br>Cheers</div></div><div class="gmail_extra"><br><div class="gmail_quote">On Fri, Mar 23, 2018 at 3:35 PM, Evandro Carrijo <span dir="ltr"><<a href="mailto:evandro.taquary@gmail.com" target="_blank">evandro.taquary@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Hello Akbar,<br><br>This is an important remark. The Plugin could provide three scenarios at all:<div><ol><li>Train the model from scratch (when there's sufficient computational resources);<br></li><li>Use Transfer Learning, that is, use models with pre-trained weights;</li><li>Like you suggest, fetch the desired <span style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">model from a </span><span style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline"><i>zoo platform</i> suitable to his data.</span></li></ol><div><span style="font-size:12.8px">An important caveat, although, is that the models can be very region-specific, that is when the scenarios 1 and 2 are applicable. Also, user can fetch well consolidated models from the <i>model zoo platform</i> as basis and tune their models as of them. <br class="m_-2061592213586581222gmail-Apple-interchange-newline"></span></div></div><div><br>I'm going to write my proposal right away, so that ideas are going to take place. As soon as I have the first version of it I will share with you guys.<br><br>Thank your for you precious advices!<br><br>Cheers</div><div><div class="h5"><div class="gmail_extra"><br><div class="gmail_quote">2018-03-23 11:12 GMT-03:00 Akbar Gumbira <span dir="ltr"><<a href="mailto:akbargumbira@gmail.com" target="_blank">akbargumbira@gmail.com</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div>Hi (again),</div><span><div> </div><blockquote style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex" class="gmail_quote">The RNN model can then be shipped into a QGIS Plugin with a convenient interface such that one could accomplish the following tasks:<ul style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><li style="margin-left:15px">Select the input data;</li></ul><ul style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><li style="margin-left:15px">Adjust some model hyperparameters (if desirable);</li></ul><ul style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><li style="margin-left:15px">Train the RNN; </li></ul><ul style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><li style="margin-left:15px">Export the generated model for persistence;</li></ul><ul style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><li style="margin-left:15px">Use the model to <span style="color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">produce a<span> </span><span style="color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">LCLU </span>map for the specified targets.</span></li></ul>The idea is to start a new Plugin that use not only RNN models, but, in the future, incorporate many other novel approaches to perform accurate <span style="color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">LCLU maps, like semantic segmentation using U-Nets and a combination of the two approaches.<br></span></blockquote><p style="font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255);box-sizing:border-box;margin-top:0px;margin-bottom:16px;color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px"></p><p style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"></p></span>Not everyone probably wants (or has the resources) to train the data. Why not, for example, have a model zoo platform where users can share their models for particular defined classifications? or will the training always be lightweight and instant?<div><br></div><div>Cheers<br class="m_-2061592213586581222m_-2680753687475188555gmail-Apple-interchange-newline"><br></div></div><div class="gmail_extra"><br><div class="gmail_quote"><div><div class="m_-2061592213586581222h5">On Fri, Mar 23, 2018 at 2:52 PM, Evandro Carrijo <span dir="ltr"><<a href="mailto:evandro.taquary@gmail.com" target="_blank">evandro.taquary@gmail.com</a>></span> wrote:<br></div></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div class="m_-2061592213586581222h5"><div dir="ltr"><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255)">Hello there!</div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255)"><br></div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255)"><span style="font-size:12.8px">I'm a Computer Science Master's Degree student whose research if focused on Deep Learning algorithms applied to Remote Sensing. Currently working at the </span><a href="https://github.com/lapig-ufg" style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-transform:none;white-space:normal;word-spacing:0px" target="_blank">Laboratory of Image Processing and Geoprocessing</a><span style="font-size:12.8px"> settled at Federal University of Goiás - Brazil. I'm also member of the High Performance Computing group of the same university (more information</span><span style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-transform:none;white-space:normal;word-spacing:0px"> </span><a href="http://dgp.cnpq.br/dgp/espelhogrupo/7985061476854055" style="color:rgb(17,85,204);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-transform:none;white-space:normal;word-spacing:0px" target="_blank">here</a><span style="font-size:12.8px">). </span><br><br><span style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-transform:none;white-space:normal;word-spacing:0px">Below I present an</span><span style="font-size:12.8px"> idea to explain how I can contribute to OSGeo/QGIS community and I'm seeking for mentors interested in assist my development. Please, feel free to argue me any matter about the project idea. </span><br><br><span style="font-size:12.8px">I would also appreciate a lot if you guys indicate a potential interested mentor to my project idea.</span><br><br><span style="font-size:12.8px">Hope there's some Interested ones out there!</span><br><br><span style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:small;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:600;letter-spacing:normal;text-transform:none;white-space:normal;word-spacing:0px;box-sizing:border-box">Idea</span><br></div><p style="color:rgb(34,34,34);font-family:arial,sans-serif;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255);font-size:small"></p><p style="font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255);box-sizing:border-box;margin-top:0px;margin-bottom:16px;color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px">The increasing number of sensors orbiting the earth is systematically producing larger volumes of data, with better spatiotemporal resolutions. To deal with that, better accurate machine learning approaches, such as Deep Learning (DL), are needed to transform raw data into applicable Information. Several DL architectures (e.g. CNN, semantic segmentation) rely only at spatial dimension to perform, for example, land-cover/land-use (LCLU) maps, disregarding the temporal dependencies between pixels observations over the time. Also, high-res remote sensing data (e.g. Planet, Sentinel) may provide more consistent time-series, that can be use in the identification of important LCLU classes, like crop, pastureland and grasslands.</p><p style="font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255);box-sizing:border-box;margin-top:0px;margin-bottom:16px;color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px">This potential can be explored using Recurrent Neural Networks (RNN), a specific family of DL approaches which can take into account time dimension. A promising project idea would be implement a RNN approach (e.g. LSTM) to classify, for example, a Sentinel time-series, that will organize and preprocess the input data set (e.g. labeled time-series), calibrate and evaluate a RNN model, and finally classify an entire region (i.e. 2 or 3 scenes) to produce a map for one or more LCLU class. It will be great evaluate the accuracy and the spatial consistent of a map produced with a RNN approach.<br><br>The RNN model can then be shipped into a QGIS Plugin with a convenient interface such that one could accomplish the following tasks:</p><p style="font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255);box-sizing:border-box;margin-top:0px;margin-bottom:16px;color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px"></p><ul><li>Select the input data;</li><li>Adjust some model hyperparameters (if desirable);</li><li>Train the RNN; </li><li>Export the generated model for persistence;<br></li><li>Use the model to <span style="color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">produce a <span style="color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">LCLU </span>map for the specified targets.</span></li></ul><div>The idea is to start a new Plugin that use not only RNN models, but, in the future, incorporate many other novel approaches to perform accurate <span style="color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">LCLU maps, like semantic segmentation using U-Nets and a combination of the two approaches.<br></span></div><p></p><p style="font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255);box-sizing:border-box;margin-top:0px;margin-bottom:16px;color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px">A simple example on classifying LCLU with two classes (pastureland and non-pastureland):</p><p style="font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255);box-sizing:border-box;margin-top:0px;margin-bottom:16px;color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px"><a href="https://user-images.githubusercontent.com/37085598/37687055-cc5236a8-2c78-11e8-8892-d113df44e235.jpg" style="color:rgb(3,102,214);box-sizing:border-box;background-color:transparent;text-decoration:none" target="_blank"><img src="https://user-images.githubusercontent.com/37085598/37687055-cc5236a8-2c78-11e8-8892-d113df44e235.jpg" alt="itapirapua" class="m_-2061592213586581222m_-2680753687475188555m_4799830794287417317gmail-m_-2131407837738034495gmail-CToWUd m_-2061592213586581222m_-2680753687475188555m_4799830794287417317gmail-CToWUd" style="box-sizing:content-box;border-style:none;max-width:100%;background-color:rgb(255,255,255)"></a><br style="box-sizing:border-box"><strong style="box-sizing:border-box;font-weight:600">Target region (input)</strong></p><p style="font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255);box-sizing:border-box;margin-top:0px;margin-bottom:16px;color:rgb(36,41,46);font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:14px"><a href="https://user-images.githubusercontent.com/37085598/37732806-ec792782-2d24-11e8-8ad9-18867768e998.jpg" style="color:rgb(3,102,214);box-sizing:border-box;background-color:transparent;text-decoration:none" target="_blank"><img src="https://user-images.githubusercontent.com/37085598/37732806-ec792782-2d24-11e8-8ad9-18867768e998.jpg" alt="itapirapua_ref" class="m_-2061592213586581222m_-2680753687475188555m_4799830794287417317gmail-m_-2131407837738034495gmail-CToWUd m_-2061592213586581222m_-2680753687475188555m_4799830794287417317gmail-CToWUd" style="box-sizing:content-box;border-style:none;max-width:100%;background-color:rgb(255,255,255)"></a><br style="box-sizing:border-box"><strong style="box-sizing:border-box;font-weight:600">Generated LCLU map (output)</strong></p><span style="color:rgb(34,34,34);font-family:arial,sans-serif;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;font-size:small;background-color:rgb(255,255,255);float:none;display:inline">Best,</span><br style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255)"><br style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255)"><span style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255);float:none;display:inline">Evandro Carrijo Taquary</span><br style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255)"><span style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;background-color:rgb(255,255,255);float:none;display:inline">Federal University of Goiás</span><br></div>
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