From f6812487520d7f6583048862db8307f6396ad2f0 Mon Sep 17 00:00:00 2001 From: dbuscombe-usgs Date: Sat, 7 Aug 2021 17:17:27 -0700 Subject: [PATCH] 08/07/21. v 1.2.5 --- README.md | 35 ++++++++- website/blog/2021-05-09-blog-post.md | 65 ++++++++++++++++- website/blog/2021-05-10-blog-post.md | 7 -- website/blog/2021-05-11-blog-post.md | 7 -- website/blog/2021-05-12-blog-post.md | 7 -- website/blog/2021-05-13-blog-post.md | 7 -- website/blog/2021-05-14-blog-post.md | 29 -------- website/blog/2021-05-15-blog-post.md | 2 +- website/blog/2021-05-16-blog-post.md | 2 +- website/docs/intro.md | 9 +-- website/docs/tutorial-basics/deploy-local.md | 6 +- website/docs/tutorial-basics/faqs.md | 43 +++++++---- website/docs/tutorial-basics/getting-help.md | 2 +- website/docs/tutorial-basics/glossary.md | 68 ------------------ website/docs/tutorial-basics/what-to-do.md | 3 +- .../docs/tutorial-extras/how-doodler-works.md | 2 +- website/static/img/cropping/big.jpg | Bin 0 -> 5212130 bytes website/static/img/cropping/fordoodler_00.jpg | Bin 0 -> 1111031 bytes website/static/img/cropping/fordoodler_01.jpg | Bin 0 -> 1160715 bytes .../img/cropping/px1024_fordoodler_00.jpg | Bin 0 -> 26165 bytes .../img/cropping/px1024_fordoodler_01.jpg | Bin 0 -> 46774 bytes .../img/cropping/px1024_fordoodler_02.jpg | Bin 0 -> 48750 bytes .../img/cropping/quarters_fordoodler_00.jpg | Bin 0 -> 477410 bytes .../img/cropping/quarters_fordoodler_01.jpg | Bin 0 -> 615083 bytes 24 files changed, 137 insertions(+), 157 deletions(-) delete mode 100644 website/blog/2021-05-10-blog-post.md delete mode 100644 website/blog/2021-05-11-blog-post.md delete mode 100644 website/blog/2021-05-12-blog-post.md delete mode 100644 website/blog/2021-05-13-blog-post.md delete mode 100644 website/blog/2021-05-14-blog-post.md delete mode 100644 website/docs/tutorial-basics/glossary.md create mode 100755 website/static/img/cropping/big.jpg create mode 100644 website/static/img/cropping/fordoodler_00.jpg create mode 100644 website/static/img/cropping/fordoodler_01.jpg create mode 100644 website/static/img/cropping/px1024_fordoodler_00.jpg create mode 100644 website/static/img/cropping/px1024_fordoodler_01.jpg create mode 100644 website/static/img/cropping/px1024_fordoodler_02.jpg create mode 100644 website/static/img/cropping/quarters_fordoodler_00.jpg create mode 100644 website/static/img/cropping/quarters_fordoodler_01.jpg diff --git a/README.md b/README.md index a400142..b803eac 100644 --- a/README.md +++ b/README.md @@ -25,6 +25,7 @@ ![](doodler-logo.png) +## Website Check out the [Doodler website](https://dbuscombe-usgs.github.io/dash_doodler/) @@ -89,6 +90,8 @@ This is python software that is designed to be used from within a `conda` enviro ## Installation +> Check out the installation guide on the [Doodler website](https://dbuscombe-usgs.github.io/dash_doodler/docs/tutorial-basics/deploy-local) + Open a terminal Clone/download this repository @@ -122,6 +125,8 @@ pip install -r environment/requirements.txt and good luck to you! ## Use +> Check out the user guide on the [Doodler website](https://dbuscombe-usgs.github.io/dash_doodler/docs/tutorial-basics/what-to-do) + Move your images into the `assets` folder. For the moment, they must be jpegs with the `.jpg` (or `JPG` or `jpeg`) extension. Support for other image types forthcoming ... Run the app. An IP address where you can view the app in your browser will be displayed in the terminal. Some browsers will launch automatically, while others you may have to manually type (or copy/paste) the IP address into a browser. Tested so far with Chrome, Firefox, and Edge. @@ -213,12 +218,12 @@ sudo docker stop www sudo docker rm www ``` -Don't ask me about Docker. That's all I know. Please contribute Docker workflows and suggestions! +Please don't ask me about Docker - that's all I know. Please contribute Docker workflows and suggestions! ## Acknowledgements -Based on [this plotly example](https://github.com/plotly/dash-sample-apps/tree/master/apps/dash-image-segmentation) and the previous openCV based implementation [doodle_labeller](https://github.com/dbuscombe-usgs/doodle_labeller), that actually has origins in a USGS CDI-sponsored class I taught in summer of 2018, called [dl-tools](https://github.com/dbuscombe-usgs/dl_tools). So, it's been a 3+ year effort! +Inspired by [this plotly example](https://github.com/plotly/dash-sample-apps/tree/master/apps/dash-image-segmentation) and the previous openCV based implementation [doodle_labeller](https://github.com/dbuscombe-usgs/doodle_labeller), that actually has origins in a USGS CDI-sponsored class I taught in summer of 2018, called [dl-tools](https://github.com/dbuscombe-usgs/dl_tools). So, it's been a 3+ year effort! ## Contributing Contributions are welcome, and they are greatly appreciated! Credit will always be given. @@ -248,6 +253,8 @@ We could always use more documentation, whether as part of the docs, in docstrin #### Get Started! +> See the [how to contribute](https://dbuscombe-usgs.github.io/dash_doodler/docs/tutorial-extras/how-to-contribute) section of the Doodler website + Ready to contribute? Here's how to set up for local development. * Fork the dash_doodler repo on GitHub. @@ -281,7 +288,29 @@ Submit a pull request through the GitHub website. ## Developers notes +### Entrypoint +* The entrypoint is `doodler.py`, which will first download sample imagery if `DOWNLOAD_SAMPLE=True` in `environment\settings.py`. + +* By default, `DOWNLOAD_SAMPLE=False` so imagery is not downloaded. + +* The other variables in `environment\settings.py` are found in Dash's `app.run_server()` documentation. + * `HOST="127.0.0.1"`` (should be `#"0.0.0.0"` for web deployment) + * `PORT="8050"` + * `DEBUG=False` + * `DEV_TOOLS_PROPS_CHECK=False` + +* `doodler.py` basically just calls and serves `app`, from `app.py` + +## Application + +* Loads classes and files and creates results folders and log file +* Creates the application layout and links all buttons to callback functions +## Callbacks +* utility functions are in `app_files\src\app_funcs.py` +* functions for drawing the imagery on the screen and making label overlays are in `app_files\src\plot_utils.py` +* functions for converting SVG annotations to raster label annotations and segmentations are in `app_files\src\annotations_to_segmentations.py` +* image segmentation/ML functions are in `app_files\src\image_segmentation.py` ## Progress report @@ -291,7 +320,7 @@ Submit a pull request through the GitHub website. 10/22/20 * modified layout so image window is larger, and button bank is narrower. Hopefully easier to label, less zooming, etc. see https://github.com/dbuscombe-usgs/dash_doodler/issues/4. Thanks Dan Nowacki -* added yml installation file, modified requirements.txt to remove gunicorn dependency. see https://github.com/dbuscombe-usgs/dash_doodler/issues/1. Thanks Dan Nowacki, Chris Sherwood, Rich Signell +* added yml installation file, modified requirements.txt to remove gunicorn dependency. see https://github.com/dbuscombe-usgs/dash_doodler/issues/1. * updates to docs, README, videos 10/29/20 diff --git a/website/blog/2021-05-09-blog-post.md b/website/blog/2021-05-09-blog-post.md index 96aa5b8..e4a8175 100644 --- a/website/blog/2021-05-09-blog-post.md +++ b/website/blog/2021-05-09-blog-post.md @@ -4,4 +4,67 @@ author: Dan Buscombe authorURL: http://twitter.com/magic_walnut --- -Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nunc vehicula nunc sit amet augue vehicula, ut rutrum felis accumsan. Cras a magna porttitor nunc imperdiet ultricies. Donec egestas sed quam vel convallis. Duis magna ipsum, hendrerit molestie risus pretium, sagittis fringilla libero. Maecenas convallis accumsan velit, rhoncus pulvinar ante vulputate non. Vestibulum consectetur interdum purus eu ultricies. Proin finibus, nibh sed consectetur egestas, sapien sem tempus dui, eget cursus ex lacus non massa. Praesent vestibulum justo a risus ultricies, nec feugiat eros ultrices. Ut laoreet velit eu aliquet dignissim. Suspendisse dignissim, tellus quis eleifend rhoncus, ante urna feugiat lorem, nec volutpat sapien odio ac magna. Duis ornare scelerisque metus, at sodales orci pulvinar at. Quisque id nisi a ante congue malesuada. Nulla venenatis nisi sed neque facilisis, ac condimentum quam egestas. Nam eros ex, sagittis ac dignissim nec, lobortis vitae nibh. Suspendisse risus felis, luctus vitae mauris id, placerat consectetur nulla. Proin mauris dui, euismod sed lectus scelerisque, malesuada sagittis mauris. +Doodler works well with small to medium sized imagery where the features and objects can be labeled without much or any zoom or pan. This depends a lot on the image resolution and content so it is difficult to make general guidelines. + +But it's easy enough to chop images into pieces, so you should experiment with a few different image sizes. + +Let's start with this image called `big.jpg`: + +![](../static/img/cropping/big.jpg) + +I recommend the command-line program [imagemagick](https://imagemagick.org/index.php), available for all major platforms. It's an incredibly powerful and useful set of tools for manipulating images. You can use the imagemagick command line [tools](https://imagemagick.org/script/command-line-processing.php) for splitting and merging imagery. We use the `magick` command (`convert` on some Linux distributions) + +## Halves +Split into two lengthways: + +```cmd +magick big.jpg -crop 50%x100% +repage fordoodler_%02d.jpg +``` + +![](../static/img/cropping/fordoodler_00.jpg) +![](../static/img/cropping/fordoodler_01.jpg) + + +## Quarters +Following the same logic, to chop the image into quarters, use: + +```cmd +magick big.jpg -crop 50%x50% +repage quarters_fordoodler_%02d.jpg +``` + +The first two quarters are shown below: + +![](../static/img/cropping/quarters_fordoodler_00.jpg) +![](../static/img/cropping/quarters_fordoodler_01.jpg) + + +## Specific size +To chop the image into tiles of a specific size, for example 1024x1024 pixels, use: + +```cmd +magick big.jpg -crop 1024x1024 +repage px1024_fordoodler_%02d.jpg +``` + +The first three tiles are shown below: + +![](../static/img/cropping/px1024_fordoodler_00.jpg) +![](../static/img/cropping/px1024_fordoodler_01.jpg) +![](../static/img/cropping/px1024_fordoodler_02.jpg) + + +Easy peasy! + +## Recombine + +After you've labeled, you may want to recombine your label image. Imagemagick includes the [montage](https://imagemagick.org/script/montage.php) tool that is handy for the task. For example, the image quarters can be recombined like this: + +```cmd +magick montage -mode concatenate -tile 2x2 quarters*.jpg recombined.jpg +``` +and the equivalent command to combine the two vertical halves is: + +```cmd +magick montage -mode concatenate -tile 2x1 fordoodler*.jpg recombined.jpg +``` + +Happy image cropping! diff --git a/website/blog/2021-05-10-blog-post.md b/website/blog/2021-05-10-blog-post.md deleted file mode 100644 index 06db6f5..0000000 --- a/website/blog/2021-05-10-blog-post.md +++ /dev/null @@ -1,7 +0,0 @@ ---- -title: Let's talk about zooming -author: Dan Buscombe -authorURL: http://twitter.com/magic_walnut ---- - -Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nunc vehicula nunc sit amet augue vehicula, ut rutrum felis accumsan. Cras a magna porttitor nunc imperdiet ultricies. Donec egestas sed quam vel convallis. Duis magna ipsum, hendrerit molestie risus pretium, sagittis fringilla libero. Maecenas convallis accumsan velit, rhoncus pulvinar ante vulputate non. Vestibulum consectetur interdum purus eu ultricies. Proin finibus, nibh sed consectetur egestas, sapien sem tempus dui, eget cursus ex lacus non massa. Praesent vestibulum justo a risus ultricies, nec feugiat eros ultrices. Ut laoreet velit eu aliquet dignissim. Suspendisse dignissim, tellus quis eleifend rhoncus, ante urna feugiat lorem, nec volutpat sapien odio ac magna. Duis ornare scelerisque metus, at sodales orci pulvinar at. Quisque id nisi a ante congue malesuada. Nulla venenatis nisi sed neque facilisis, ac condimentum quam egestas. Nam eros ex, sagittis ac dignissim nec, lobortis vitae nibh. Suspendisse risus felis, luctus vitae mauris id, placerat consectetur nulla. Proin mauris dui, euismod sed lectus scelerisque, malesuada sagittis mauris. diff --git a/website/blog/2021-05-11-blog-post.md b/website/blog/2021-05-11-blog-post.md deleted file mode 100644 index 7b85224..0000000 --- a/website/blog/2021-05-11-blog-post.md +++ /dev/null @@ -1,7 +0,0 @@ ---- -title: When things go wrong ... -author: Dan Buscombe -authorURL: http://twitter.com/magic_walnut ---- - -Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nunc vehicula nunc sit amet augue vehicula, ut rutrum felis accumsan. Cras a magna porttitor nunc imperdiet ultricies. Donec egestas sed quam vel convallis. Duis magna ipsum, hendrerit molestie risus pretium, sagittis fringilla libero. Maecenas convallis accumsan velit, rhoncus pulvinar ante vulputate non. Vestibulum consectetur interdum purus eu ultricies. Proin finibus, nibh sed consectetur egestas, sapien sem tempus dui, eget cursus ex lacus non massa. Praesent vestibulum justo a risus ultricies, nec feugiat eros ultrices. Ut laoreet velit eu aliquet dignissim. Suspendisse dignissim, tellus quis eleifend rhoncus, ante urna feugiat lorem, nec volutpat sapien odio ac magna. Duis ornare scelerisque metus, at sodales orci pulvinar at. Quisque id nisi a ante congue malesuada. Nulla venenatis nisi sed neque facilisis, ac condimentum quam egestas. Nam eros ex, sagittis ac dignissim nec, lobortis vitae nibh. Suspendisse risus felis, luctus vitae mauris id, placerat consectetur nulla. Proin mauris dui, euismod sed lectus scelerisque, malesuada sagittis mauris. diff --git a/website/blog/2021-05-12-blog-post.md b/website/blog/2021-05-12-blog-post.md deleted file mode 100644 index 445c08a..0000000 --- a/website/blog/2021-05-12-blog-post.md +++ /dev/null @@ -1,7 +0,0 @@ ---- -title: Long, stringy things -author: Dan Buscombe -authorURL: http://twitter.com/magic_walnut ---- - -Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nunc vehicula nunc sit amet augue vehicula, ut rutrum felis accumsan. Cras a magna porttitor nunc imperdiet ultricies. Donec egestas sed quam vel convallis. Duis magna ipsum, hendrerit molestie risus pretium, sagittis fringilla libero. Maecenas convallis accumsan velit, rhoncus pulvinar ante vulputate non. Vestibulum consectetur interdum purus eu ultricies. Proin finibus, nibh sed consectetur egestas, sapien sem tempus dui, eget cursus ex lacus non massa. Praesent vestibulum justo a risus ultricies, nec feugiat eros ultrices. Ut laoreet velit eu aliquet dignissim. Suspendisse dignissim, tellus quis eleifend rhoncus, ante urna feugiat lorem, nec volutpat sapien odio ac magna. Duis ornare scelerisque metus, at sodales orci pulvinar at. Quisque id nisi a ante congue malesuada. Nulla venenatis nisi sed neque facilisis, ac condimentum quam egestas. Nam eros ex, sagittis ac dignissim nec, lobortis vitae nibh. Suspendisse risus felis, luctus vitae mauris id, placerat consectetur nulla. Proin mauris dui, euismod sed lectus scelerisque, malesuada sagittis mauris. diff --git a/website/blog/2021-05-13-blog-post.md b/website/blog/2021-05-13-blog-post.md deleted file mode 100644 index 5abc4e6..0000000 --- a/website/blog/2021-05-13-blog-post.md +++ /dev/null @@ -1,7 +0,0 @@ ---- -title: Your imagery is too big -author: Dan Buscombe -authorURL: http://twitter.com/magic_walnut ---- - -Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nunc vehicula nunc sit amet augue vehicula, ut rutrum felis accumsan. Cras a magna porttitor nunc imperdiet ultricies. Donec egestas sed quam vel convallis. Duis magna ipsum, hendrerit molestie risus pretium, sagittis fringilla libero. Maecenas convallis accumsan velit, rhoncus pulvinar ante vulputate non. Vestibulum consectetur interdum purus eu ultricies. Proin finibus, nibh sed consectetur egestas, sapien sem tempus dui, eget cursus ex lacus non massa. Praesent vestibulum justo a risus ultricies, nec feugiat eros ultrices. Ut laoreet velit eu aliquet dignissim. Suspendisse dignissim, tellus quis eleifend rhoncus, ante urna feugiat lorem, nec volutpat sapien odio ac magna. Duis ornare scelerisque metus, at sodales orci pulvinar at. Quisque id nisi a ante congue malesuada. Nulla venenatis nisi sed neque facilisis, ac condimentum quam egestas. Nam eros ex, sagittis ac dignissim nec, lobortis vitae nibh. Suspendisse risus felis, luctus vitae mauris id, placerat consectetur nulla. Proin mauris dui, euismod sed lectus scelerisque, malesuada sagittis mauris. diff --git a/website/blog/2021-05-14-blog-post.md b/website/blog/2021-05-14-blog-post.md deleted file mode 100644 index 82c8062..0000000 --- a/website/blog/2021-05-14-blog-post.md +++ /dev/null @@ -1,29 +0,0 @@ ---- -title: The blur and model independence factors -author: Dan Buscombe -authorURL: http://twitter.com/magic_walnut ---- - -What *are* the blur and model independence factors? - -The are both names I made up for parameters of the CRF model used on the image-by-image or 'local' level of prediction, as described in the [How Doodler works](https://dbuscombe-usgs.github.io/dash_doodler/docs/tutorial-extras/how-doodler-works) section. - -What do they mean? When should their values be changed? Read on ... - -![](../static/img/parameters/doodles.png) - - -### Blur factor - -![](../static/img/parameters/theta1-mu1.png) -![](../static/img/parameters/theta15-mu1.png) -![](../static/img/parameters/theta35-mu1.png) -![](../static/img/parameters/theta63-mu1.png) - - -### Model independence factor - -![](../static/img/parameters/theta1-mu1.png) -![](../static/img/parameters/theta1-mu14.png) -![](../static/img/parameters/theta1-mu34.png) -![](../static/img/parameters/theta1-mu73.png) diff --git a/website/blog/2021-05-15-blog-post.md b/website/blog/2021-05-15-blog-post.md index 41e431b..f701854 100644 --- a/website/blog/2021-05-15-blog-post.md +++ b/website/blog/2021-05-15-blog-post.md @@ -1,5 +1,5 @@ --- -title: viz_npz.py +title: How to use viz_npz.py author: Dan Buscombe authorURL: http://twitter.com/magic_walnut --- diff --git a/website/blog/2021-05-16-blog-post.md b/website/blog/2021-05-16-blog-post.md index b0ffbe1..76a9c86 100644 --- a/website/blog/2021-05-16-blog-post.md +++ b/website/blog/2021-05-16-blog-post.md @@ -1,5 +1,5 @@ --- -title: What's new in version 1.2.1 (May 10, 2021) +title: What's new in version 1.2.1? (May 10, 2021) author: Dan Buscombe authorURL: http://twitter.com/magic_walnut --- diff --git a/website/docs/intro.md b/website/docs/intro.md index d4ceb37..0ce3b7d 100644 --- a/website/docs/intro.md +++ b/website/docs/intro.md @@ -5,7 +5,7 @@ sidebar_position: 1 # What is Doodler for? -Doodler is a web application for [image segmentation](tutorial-basics/glossary#image-segmentation), which is the process of turning this (for example): +Doodler is a web application for image segmentation, which is the process of turning this (for example): ![](/img/ex_image.jpg) @@ -37,7 +37,7 @@ For natural and other scenes, doodler can be a relatively quick (in terms of the Here's a movie of Doodler in action: -![](https://raw.githubusercontent.com/dbuscombe-usgs/dash_doodler/main/assets/logos/quick-satshoreline-x2c.gif) +![](https://github.com/dbuscombe-usgs/dash_doodler/releases/download/gifs/quick-satshoreline-x2c.gif) There are two tabs, one for 'doodling' on images, and one for selecting new images from a 'to-do' list. Doodler will remove image names from the list if a label image has previously been generated. The basic workflow is: @@ -47,8 +47,9 @@ There are two tabs, one for 'doodling' on images, and one for selecting new imag 4. [if still not happy with the result] Modify the parameters and repeat step 2. above Here are more examples of Doodler in action +![](https://github.com/dbuscombe-usgs/dash_doodler/releases/download/gifs/doodler-demo-2-9-21-short-elwha.gif) -![](https://raw.githubusercontent.com/dbuscombe-usgs/dash_doodler/main/assets/logos/quick-satshore2-x2c.gif) +![](https://github.com/dbuscombe-usgs/dash_doodler/releases/download/gifs/doodler-demo-2-9-21-short-coast2.gif) You upload your own imagery, and define your own class set (list of class names, each of which will be assigned a different color button like in the examples above), and off you go! @@ -66,7 +67,7 @@ Before we begin, let's state some important factors around Doodler and its use ### Credits Doodler is written and maintained by Dr Daniel Buscombe, Marda Science, LLC, contracted to the U.S. Geological Survey Pacific Coastal and Marine Science Center in Santa Cruz, CA. Doodler development is funded by the U.S. Geological Survey Coastal Hazards Program, and is for the primary usage of U.S. Geological Survey scientists, researchers and affiliated colleagues working on the Hurricane Florence Supplemental Project and other coastal hazards research. -Thanks to Jon Warrick, Phil Wernette, Chris Sherwood, Jenna Brown, Andy Ritchie, Jin-Si Over, Christine Kranenburg, and the rest of the Florence Supplemental team; to Evan Goldstein and colleagues at University of North Carolina Greensboro; Leslie Hsu at the USGS Community for Data Integration; and LCDR Brodie Wells, formerly of Naval Postgraduate School, Monterey. Doodler was initially based on [this](https://github.com/plotly/dash-sample-apps/tree/master/apps/dash-image-segmentation) plotly example and also the previous openCV based implementation called [doodle_labeller](https://github.com/dbuscombe-usgs/doodle_labeller), also written by Dr Daniel Buscombe. +Thanks to Jon Warrick, Phil Wernette, Chris Sherwood, Jenna Brown, Andy Ritchie, Jin-Si Over, Christine Kranenburg, and the rest of the Florence Supplemental team; to Evan Goldstein and colleagues at University of North Carolina Greensboro; Leslie Hsu at the USGS Community for Data Integration; and LCDR Brodie Wells, formerly of Naval Postgraduate School, Monterey. Doodler was inspired by [this](https://github.com/plotly/dash-sample-apps/tree/master/apps/dash-image-segmentation) plotly example and also the previous openCV based implementation called [doodle_labeller](https://github.com/dbuscombe-usgs/doodle_labeller), also written by Dr Daniel Buscombe. ### Sounds good! How do I install? diff --git a/website/docs/tutorial-basics/deploy-local.md b/website/docs/tutorial-basics/deploy-local.md index 6d9c504..19e06df 100644 --- a/website/docs/tutorial-basics/deploy-local.md +++ b/website/docs/tutorial-basics/deploy-local.md @@ -90,7 +90,7 @@ It's important you know what the various files do. It's also important to stress ![](/img/install/install4.PNG) #### Assets folder -This is the `assets` folder where you should put the images you want to label. The program comes with a set of default files that look like this: +This is the `assets` folder where you should put the images you want to label. The program comes with a set of default files that can optionally download by running the `download_data.py` script that look like this: ![](/img/install/install5.PNG) @@ -106,10 +106,6 @@ This is the 'labeled' folder, where the program copies the images you have label ![](/img/install/install9.PNG) -#### Sample folder -The program also comes with a `sample` directory to test the default classifier (water/land). However, your sample images don't need to be located here; they can be anywhere you have read and write access to on your computer - -![](/img/install/install7.PNG) #### Utils folder Finally, these python scripts are run from the command line, and are a handy collection of things once you have some data, so we'll talk about them later diff --git a/website/docs/tutorial-basics/faqs.md b/website/docs/tutorial-basics/faqs.md index 8c5257f..b82d9a5 100644 --- a/website/docs/tutorial-basics/faqs.md +++ b/website/docs/tutorial-basics/faqs.md @@ -3,7 +3,6 @@ sidebar_position: 4 --- # Frequently Asked Questions -(page under construction) Please read this page before submitting your Issue on Github @@ -18,23 +17,21 @@ In typical order of importance: 5. If possible, use fewer classes 6. If possible, use more and faster CPU cores -### Why are my results poor? -See [this](../../blog/2021/05/11/blog-post) - - ### What is the maximum number of classes? - +2. The maximum number of allowable classes in the program is 24 -### How should I choose classes? +### I have pngs or tiffs - how do I convert to jpg? -See [this](how-to-doodle#how-to-decide-on-classes) +Use imagemagick, specifically the `convert` command - see [here](https://imagemagick.org/script/convert.php) +### My images are too big. How do I tile them? + +See [this](../../blog/2021/05/09/blog-post) for regular imagery, and [this](../../blog/2020/08/01/blog-post) for geotiffs ### Okay, I can use Doodler to make label images. Now what? @@ -44,15 +41,33 @@ The primary purpose of Doodler is to create enough label images that Deep Learni See [this](../../blog/2021/05/15/blog-post) +## When should I adjust the parameters? -### What do the blur and model independence parameters dp? +It is generally considered a good thing if you can get a good result without adjusting hyperparameters, or using high values of blur, model independence and data downsample factors. So, focus on how to annotate well and use the hyperparameters as a last resort -See [this](../../blog/2021/05/14/blog-post) +On datasets tested to date, we estimate that approximately half or more of images require the addition of annotations beyond the initial sparse set, and approximately a tenth or less require the removal of annotations or the adjustment of hyperparameters. -## My images are too big. How to I tile them? -See [this](../../blog/2021/05/09/blog-post) for regular imagery, and [this](../../blog/2020/08/01/blog-post) for geotiffs +## When should I increase the downsample factors? +Downsampling is a memory management strategy so use larger values if the program crashes (which is likely because of insufficient RAM or computer memory). Generally, you want to use as low a value of either as possible to avoid downsampling. + + +## What do the blur and model independence parameters do? +#### Blur +The CRF feature extractor to extract color image features and map them to classes. These features are engineered, by convolving Gaussian kernels with the imagery. The blur parameter controls the degree of allowable similarity in image features between classes, therefore a value of 1 (the default) only tolerates image features with small differences in intensity being assigned the same class label. That's a lot of detail to put into a one-word name, so we called it the `blur` parameter because it generally controls the sharpness of the class boundaries in the label image. It is also named after [these guys](https://youtu.be/WIS-9_KS1To?t=1217). + +#### Model independence +The `model independence` is used to define pairwise potentials used by the model to encourage adjacent pixels to be the same class label. Values greater than 1 weight the pairwise potentials more than the unary potentials, which might be useful when the MLP prediction is poor. In general, larger values of `model independence` tend to give the model greater independence, resulting in the reclassification of more pixels. This is intended behavior: the importance of pairwise potentials becomes much greater than unary potentials, and spatial inconsistencies in feature-label pairings have greater likelihood of being reclassified. + +#### Caution +Note that neither effect necessarily improves the result. + + +## Why are my results poor? +See our forthcoming paper. In the meantime, [this](https://youtu.be/dQw4w9WgXcQ?t=76) short video. + + diff --git a/website/docs/tutorial-basics/what-to-do.md b/website/docs/tutorial-basics/what-to-do.md index 01d0895..99d004c 100644 --- a/website/docs/tutorial-basics/what-to-do.md +++ b/website/docs/tutorial-basics/what-to-do.md @@ -96,7 +96,8 @@ And you should see something like this: Excellent, in no time you'll be doodling like this: -![](https://raw.githubusercontent.com/dbuscombe-usgs/dash_doodler/main/assets/logos/quick-satshore2-x2c.gif) + +![](https://github.com/dbuscombe-usgs/dash_doodler/releases/download/gifs/doodler-demo-2-9-21-short-coast.gif) ### Identify yourself and select a file diff --git a/website/docs/tutorial-extras/how-doodler-works.md b/website/docs/tutorial-extras/how-doodler-works.md index f2c75a1..9bd20fb 100644 --- a/website/docs/tutorial-extras/how-doodler-works.md +++ b/website/docs/tutorial-extras/how-doodler-works.md @@ -127,7 +127,7 @@ The local predictions are provided by a different type of ML model, called a CRF That initial MLP provides an initial estimate of the entire label estimate, which is fed (with the original image) to a secondary post-processing model based on a fully connected Conditional Random Field model, or CRF for short. The CRF model refines the label image, using the MLP model output as priors that are refined to posteriors given the specific image. As such, the MLP model is treated as a initial model and the CRF model is for 'local' (i.e. image-specific) refinement. -The CRF builds a model for the likelihood of the MLP-predicted labels based on the distributions of features it extracts from the imagery, and can reclassify pixels (it is intended to do so). Its feature extraction and decision making behavior is complex and governed by parameters. That prediction then is further refined by applying the model to numerous transformed versions of the image, making predictions, untransforming, and then averaging the stack of resulting predictions. This concept is called [test-time-augmentation](../tutorial-basics/glossary#test-time-augmentation) and is illustrated in the figure below as outputs from using 10 'test-time augmented' inputs: +The CRF builds a model for the likelihood of the MLP-predicted labels based on the distributions of features it extracts from the imagery, and can reclassify pixels (it is intended to do so). Its feature extraction and decision making behavior is complex and governed by parameters. That prediction then is further refined by applying the model to numerous transformed versions of the image, making predictions, untransforming, and then averaging the stack of resulting predictions. 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