![]() I don't want to approach this using ML because I don't have the manpower or a large enough dataset to make a good training set, so I would truly appreciate some easier vision processing tools. I was hoping to box and label the larger hydra plants but couldn't find much applicable literature for differentiating between large and small objects of similar attributes in an image, to achieve my goal. There is some residual light artifacts left in the filtered image, but I have to bite the cost or else I lose the resolution of the very thin hydra such as in the top left of the original image. I have so far applied a circle mask and an orange color space mask to create a cleaned up image so that it's mostly just the shrimp and hydra. An example of a snap image from the machine of the petri dish looks like so: Here is how the code could look like:įor my research project I'm trying to distinguish between hydra plant (the larger amoeba looking oranges things) and their brine shrimp feed (the smaller orange specks) so that we can automate the cleaning of petri dishes using a pipetting machine. One way to do that is to create a CGImage from CAShapeLayer containing the mask and then create CIImage out of it. So the mask image has to be a CIImage as well. And now you can use the CIKMeans filter with it as described at the beginning.īTW, if you want to play with every single of the 230 filters out there check this app out: ĬIFilters can only work with CIImages. The output of that filter will give you the image with all pixels outside the contour fully transparent. ![]() inputMaskImage is the mask you created above.inputBackgroundImage is a fully transparent (clear) image.Create a mask image but setting all pixels inside the contour white and black outside (set background to black and fill the path with white).Now, to make all pixels transparent outside of the contour, you could do something like this: WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.If you could make all pixels outside of the contour transparent then you could use CIKmeans filter with inputCount equal 1 and the inputExtent set to the extent of the frame to get the average color of the area inside the contour (the output of the filter will contain 1-pixel image and the color of the pixel is what you are looking for). Unless required by applicable law or agreed to in writing, softwareĭistributed under the License is distributed on an "AS IS" BASIS, You may not use this file except in compliance with the License. Licensed under the Apache License, Version 2.0 (the "License") Please also make sure your code compiles by running mvn clean verify.īefore your code can be accepted into the project you must also sign the Individual Contributor License Agreement (CLA). When submitting code, please make every effort to follow existing conventions and style in order to keep the code as readable as possible. If you would like to contribute code you can do so through GitHub by forking the repository and sending a pull request. Gradle implementation ':picasso: (insert latest version)' Contributing The source code to the Picasso, its samples, and this website is available on GitHub. Call setIndicatorsEnabled(true) on the Picasso instance. Picasso.get().load(new File(.)).into(imageView3) Debug Indicatorsįor development you can enable the display of a colored ribbon which indicates the image source. Picasso.get().load("file:///android_asset/DvpvklR.png").into(imageView2) Picasso.get().load(R.drawable.landing_screen).into(imageView1) Resources, assets, files, content providers are all supported as image sources. error(R.er_placeholder_error)Ī request will be retried three times before the error placeholder is shown. Picasso supports both download and error placeholders as optional features. Pass an instance of this class to the transform method. public void getView(int position, View convertView, ViewGroup parent) Complex image transformations with minimal memory use.Īdapter re-use is automatically detected and the previous download canceled.Handling ImageView recycling and download cancelation in an adapter.Many common pitfalls of image loading on Android are handled automatically by Picasso: Picasso allows for hassle-free image loading in your application-often in one line of code! Picasso.get().load("").into(imageView) Images add much-needed context and visual flair to Android applications.
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