70 20 10 Learning Model

[Doris Joo]

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I had been used the trial version of ArcGIS Pro and I was able to train deep learning model with 6 bands (channels) with 32 bits. But now few days later, I got a license for ArcGIS Pro 2.8 and I'm only able to train an image with 3 bands (channels) with 8bits. Even I have modified my image to 3 bands with 8 bits I'm still having this problem.

I exported as classified tiles.

I saw past posts asking about it with not resolved answers. So, I'm creating this post maybe someone could see this and help with it.

In this case, I exported my training as classified tile, so I'm trying to train using deeplabv3 and backbone model : vgg19. However, before I click "run" (after loading my input training folder) appear an "x" for Input training data and this error message.

You can also click the Manage Environments button to see if there are any other Python cloned environments which may have the deep learning packages installed. If so, that environment should be the active one.

If you cannot see the deep learning packages installed, then firstly ensure that the default arcgispro-py3 environment is active (as shown in the screenshot above. Then go to the Esri Deep Learning Frameworks Github site and download and install the Deep Learning Libraries Installer for your version.

Note: These installers will place the deep learning packages in the default arcgispro-py3 environment. If you need to clone environments and use deep learning, then make sure you clone the environment after doing the install.

When I saw you message I just had uninstalled the 2.8 version and installed the 2.7 version to do some tests if could solve my problem. As the same I did before with trial and 2.8, I did again with 2.7. The quantity of packages installed is 251 lower then your, but worked fine, didn't appear the error with 3 bands and 8bits, and finally completed the training.

I realized that the tile size during the exportation caninfluence using the 2.7 version for low tile size, which starts appearing the error again. I installed the other packages you recommend now to know if could help and the error continued for this low tile size. I think could be a limitation for lower tile size.

This seems silly - why should I have to uninstall the current version of Pro and re-install a previous one to get a tool to work. I successfully Exported Training Data and Trained a Model previously - I am using the same settings as last time and getting this error as well trying to run it again.

Yes, apparently - I am careful to set the output folder for the images and labels in a folder outside the parent folder where my other data is. I am not positive though - I have been through multiple iterations of collecting training samples, exporting and training.

The input folder is never recognized (which is: \deep_learning\redlands_img that contains the above folders and files). I get the following error and cannot seem to fix it. Any help is appreciated. I am including my zip file of output.

Also, the documentation for the specific tools and the overview don't really provide enough details to set tool parameters or suggestions for different types of scenarios. Some updated material would be most helpful for the deep learning community that support Pro 2.5.

Hi Masita, thank you for reaching out on GeoNet. This issue was logged as a bug and the current bug status is 'Implemented', which means the defect has been addressed for the next software release. As a workaround for now, for the Export Training Data For Deep Learning tool, under Meta Data Format, choose any format other than KITTI Labels, such as PASCAL Visual Object Classes. Please refer to this page for more information.

I was having a similar issue in a different Esri training module: Use deep learning to assess palm tree health. I created a new deep learning environment using your steps and the problem was solved. Thank you.p learning to assess palm tree health

Hi @PriyankaTuteja, thank you for your reply. I have solved my problem. There's a new Jupyter installed together with the ArcGIS pro update. So i just opened it and it works fine. Thanks again for this reply.

Roseman University uses unique teaching methods to produce graduates that are competent and to provide an educational environment that not only produces and ensures high levels of achievement from all students but also fosters cooperation and collaboration in the learning process. This is the concept of mastery learning.

The Roseman University Six-Point Mastery Learning Model consists of Block Curriculum, Active and Collaborative Learning, Competency-based Education, Assessment Learning, Early Experiential Learning, and a Classroom Design that facilitates learning. All of these components reinforce one another and contribute to an unparalleled educational environment.

With a block curriculum, students take only one class at a time, focus intently on that content area, and master the content before proceeding to the next block or course. Students attend classes from 8 am to 3 pm daily, which is advantageous because faculty can deliver the classroom (didactic) component of the course content with more direct contact hours between faculty and students. It also encourages faculty to incorporate many different learning techniques, including discussions, activities, and breaks in the content delivery can occur naturally with the flow of instruction, so the important concepts can be reinforced.

Roseman University assessments are frequent, occurring every two to three weeks. Learning, assessment, feedback, and re-assessment are ongoing and continuous in the curriculum. Thus, students are better able to gauge their learning and detect areas of misunderstanding early so they can correct them prior to moving on to other subject areas.

Early exposure to clinical experiences is critical in building basic clinical skills. Roseman University enhances and supports learning in the classroom by providing students the opportunity to see, feel, and understand what was presented in the classroom in an actual healthcare setting at the beginning of their programs rather than one to two years after the completion of classroom learning.

Our courses focus less on final products and more on helping you learn how to learn, how to take risks in your learning, and how to find, understand, and use academic knowledge to help you reach your life and career goals.

The Cluster Model at Plymouth State University is a transformative approach to education that emphasizes collaborative, multidisciplinary work transcending individual disciplines. It is designed to prepare students for the challenges of the 21st century by engaging them in real-world projects that address complex societal issues. Through the Integrated Cluster Learning Model, students work with diverse teams from various backgrounds, partnering with local communities and organizations to create a more efficient, equitable, and forward-thinking ecosystem of ideas. This model blends practice with innovation, providing students with hands-on experience and a skill set sought after by future employers, fostering critical thinking, collaboration, and career readiness.

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