terraformer-java | modular toolkit for working with geographic data

 by   unicornerpdx Java Version: Current License: Apache-2.0

kandi X-RAY | terraformer-java Summary

kandi X-RAY | terraformer-java Summary

terraformer-java is a Java library typically used in Data Preparation applications. terraformer-java has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Terraformer is a modular toolkit for working with geographic data.
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            kandi-support Support

              terraformer-java has a low active ecosystem.
              It has 3 star(s) with 2 fork(s). There are no watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 2 open issues and 1 have been closed. On average issues are closed in 1 days. There are 2 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of terraformer-java is current.

            kandi-Quality Quality

              terraformer-java has no bugs reported.

            kandi-Security Security

              terraformer-java has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              terraformer-java is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              terraformer-java releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed terraformer-java and discovered the below as its top functions. This is intended to give you an instant insight into terraformer-java implemented functionality, and help decide if they suit your requirements.
            • Returns true if this MultiLineString contains another
            • Compare two lines
            • Compares this geometry to another
            • Compare two geometries
            • Returns true if this MultiPolygon is equivalent to this MultiPolygon
            • Checks if one polygon contains another polygon
            • Checks if this polygon is equivalent to this one
            • Checks if two multiPolygon contains one polygon
            • Returns true if this Geometry is equivalent to this one
            • Compares two geometries
            • Checks if two feature collections contain equivalent features
            • Decode a JSON geometry collection
            • Convert a json object to a base geometry object
            • Create a feature from a JSON object
            • Returns true if this GeometryCollection is equivalent to this one
            • Checks if two geometries contain equivalent geometries
            • Replace all the geometries in the specified collection
            • Replaces the given geometries in the given collection
            • Construct a feature from a JSON string
            • Decode a polygon JSON string
            • Parse a point JSON string
            • Decode a JSON string from a JSON string
            • Parse a featurecollection JSON string
            • Parse a multi polygon JSON string
            • Decode a MultiPoint JSON string
            • Decodes a MultiLineString JSON string
            Get all kandi verified functions for this library.

            terraformer-java Key Features

            No Key Features are available at this moment for terraformer-java.

            terraformer-java Examples and Code Snippets

            No Code Snippets are available at this moment for terraformer-java.

            Community Discussions

            QUESTION

            Prepare for Binary Masks used for the image segmentation
            Asked 2022-Mar-30 at 08:33

            I am trying to prepare the masks for image segmentation with Pytorch. I have three questions about data preparation.

            1. What is the appropriate data format to save the binary mask in general? PNG? JPEG?

            2. Is the mask size needed to be set square such as (224x224), not a rectangle such as (224x448)?

            3. Is the mask value fixed when the size is converted from rectangle to square?

            For example, the original mask image size is (600x900), which is binary [0,1]. However, when I applied

            ...

            ANSWER

            Answered 2022-Mar-30 at 08:33
            1. PNG, because it is lossless by design.
            2. It depends. More convenient is to use standard resolution, (224x224), I would start with that.
            3. Use resize without interpolation transforms.Resize((300, 300), interpolation=InterpolationMode.NEAREST)

            Source https://stackoverflow.com/questions/71669952

            QUESTION

            Yolov5 object detection training
            Asked 2022-Mar-25 at 04:06

            Please i need you help concerning my yolov5 training process for object detection!

            I try to train my object detection model yolov5 for detecting small object ( scratch). For labelling my images i used roboflow, where i applied some data augmentation and some pre-processing that roboflow offers as a services. when i finish the pre-processing step and the data augmentation roboflow gives the choice for different output format, in my case it is yolov5 pytorch, and roboflow does everything for me splitting the data into training validation and test. Hence, Everything was set up as it should be for my data preparation and i got at the end the folder with data.yaml and the images with its labels, in data.yaml i put the path of my training and validation sets as i saw in the GitHub tutorial for yolov5. I followed the steps very carefully tought.

            The problem is when the training start i get nan in the obj and box column as you can see in the picture bellow, that i don't know the reason why, can someone relate to that or give me any clue to find the solution please, it's my first project in computer vision.

            This is what i get when the training process starts

            This the last message error when the training finish

            I think the problem comes maybe from here but i don't know how to fix it, i used the code of yolov5 team as it's in the tuto

            The training continue without any problem but the map and precision remains 0 all the process !!

            Ps : Here is the link of tuto i followed : https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data

            ...

            ANSWER

            Answered 2021-Dec-04 at 09:38

            Running my code in colab worked successfully and the resulats were good. I think that the problem was in my personnel laptop environment maybe the version of pytorch i was using '1.10.0+cu113', or something else ! If you have any advices to set up my environnement for yolov5 properly i would be happy to take from you guys. many Thanks again to @alexheat

            Source https://stackoverflow.com/questions/70199621

            QUESTION

            scatter plot color bar does not look right
            Asked 2022-Mar-24 at 22:20

            I have written my code to create a scatter plot with a color bar on the right. But the color bar does not look right, in the sense that the color is too light to be mapped to the actual color used in the plot. I am not sure what is missing or wrong here. But I am hoping to get something similar to what's shown here: https://medium.com/@juliansteam/what-bert-topic-modelling-reveal-about-the-2021-unrest-in-south-africa-d0d15629a9b4 (about in the middle of the page)

            ...

            ANSWER

            Answered 2022-Mar-24 at 22:20

            The colorbar uses the given alpha=.3. In the scatterplot, many dots with the same color are superimposed, causing them to look brighter than a single dot.

            One way to tackle this, is to create a ScalarMappable object to be used by the colorbar, taking the colormap and the norm of the scatter plot (but not its alpha). Note that simply changing the alpha of the scatter object (scatter.set_alpha(1)) would also change the plot itself.

            Source https://stackoverflow.com/questions/71608280

            QUESTION

            using DelimitedFiles with title of the header
            Asked 2022-Mar-09 at 19:26

            When importing a .csv file, is there any way to read the data from the title of the header? Consider the .csv file in the following:

            I mean, instead of start_node = round.(Int64, data[:,1]) is there another way to say "start_node" is the one in the .csv file that its header is "start node i"

            ...

            ANSWER

            Answered 2022-Mar-09 at 19:08

            The most natural way is to use CSV along with the DataFrames package.

            Consider file:

            Source https://stackoverflow.com/questions/71414537

            QUESTION

            Pytorch : different behaviours in GAN training with different, but conceptually equivalent, code
            Asked 2022-Feb-16 at 13:43

            I'm trying to implement a simple GAN in Pytorch. The following training code works:

            ...

            ANSWER

            Answered 2022-Feb-16 at 13:43
            Why do we different results?

            Supplying inputs in either the same batch, or separate batches, can make a difference if the model includes dependencies between different elements of the batch. By far the most common source in current deep learning models is batch normalization. As you mentioned, the discriminator does include batchnorm, so this is likely the reason for different behaviors. Here is an example. Using single numbers and a batch size of 4:

            Source https://stackoverflow.com/questions/71140227

            QUESTION

            Is there a way to query a csv file in Karate?
            Asked 2022-Feb-02 at 03:20

            I am looking for a similar functionality like Fillo Excel API where we can do CRUD operations in an excel file using query like statements.

            A select statement in a csv file is a great addition to the framework to provide more flexibility in test data driven approach testing.

            Sample scenario: A test case that needs to have multiple data preparation of inserting records to database.

            Instead of putting all test data in 1 row or 1 cell like this and do a string split before processing.

            ...

            ANSWER

            Answered 2022-Feb-02 at 03:20

            There's no need. Karate can transform a CSV file into a JSON array in one line:

            Source https://stackoverflow.com/questions/70949738

            QUESTION

            Multi Processing with sqlalchemy
            Asked 2022-Feb-01 at 22:50

            I have a python script that handles data transactions through sqlalchemy using:

            ...

            ANSWER

            Answered 2022-Jan-31 at 06:48

            This is an interesting situation. It seems that maybe you can sidestep some of the manual process/thread handling and utilize something like multiprocessing's Pool. I made an example based on some other data initializing code I had. This delegates creating test data and inserting it for each of 10 "devices" to a pool of 3 processes. One caveat that seems necessary is to dispose of the engine before it is shared across fork(), ie. before the Pool tasks are created, this is mentioned here: engine-disposal

            Source https://stackoverflow.com/questions/70918448

            QUESTION

            Trouble changing imputer strategy in scikit-learn pipeline
            Asked 2022-Jan-27 at 05:26

            I am trying to use GridSearchCV to select the best imputer strategy but I am having trouble doing that.

            First, I have a data preparation pipeline for numerical and categorical columns-

            ...

            ANSWER

            Answered 2022-Jan-27 at 05:26

            The way you specify the parameter is via a dictionary that maps the name of the estimator/transformer and name of the parameter you want to change to the parameters you want to try. If you have a pipeline or a pipeline of pipelines, the name is the names of all its parents combined with a double underscore. So for your case, it looks like

            Source https://stackoverflow.com/questions/70873560

            QUESTION

            Does tensorflow re-initialize weights when training in a for loop?
            Asked 2022-Jan-20 at 15:12

            I'm training a model within a for loop, because...I can. I know there are alternative like tf.Dataset API with generators to stream data from disk, but my question is on the specific case of a loop.

            Does TF re-initialize weights of the model at the beginning of each loop ? Or does the initialization only occurs the first time the model is instantiated ?

            EDIT :

            ...

            ANSWER

            Answered 2022-Jan-20 at 15:06

            Weights are initialized when the layers are defined (before fit). It does not re-initialize weights afterward - even if you call fit multiple times.

            To show this is the case, I plotted the decision boundary at regular training epochs (by calling fit and then predict):

            Source https://stackoverflow.com/questions/70788383

            QUESTION

            How to force Pytest to execute the only function in parametrize?
            Asked 2022-Jan-20 at 14:32

            I have 2 tests. I want to run the only one:

            ...

            ANSWER

            Answered 2022-Jan-20 at 14:32

            It looks like that only something like that can resolved the issue.

            Source https://stackoverflow.com/questions/70721021

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

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