I have a standalone app that imports the qgis.core libraries to do the GIS mapping stuff. I have a QgsMapCanvas for map display. Now, I can get back the mapUnits() of the map display, but it comes back as a number, such as {UnitType 2}, I know it is the number in the QGis::UnitType enum type, so the question is how to get the name of the UnitType in QGis from this unit type number that I got from the map canvas?
I know I can hard code them in, but it would be better to go to where it is defined. below is the code snippet. the 'mapUnits' call will give you a number, I would like to have the name of that QGis::UnitType enum.
<code>
fileInfo = QFileInfo(raster)
path = fileInfo.filePath()
baseName = fileInfo.baseName()
layer = QgsVectorLayer(path, baseName)
QgsMapLayerRegistry.instance().addMapLayer(layer)
if layer.isValid() is True:
layer.dataProvider().crs().mapUnits()
</code>
You can do
print(QgsUnitTypes.toString(myUnits))
Be just aware that units enum have been renamed and moved out of QGis to QgsunitTypes class in version 3.x:
2.x: QGis::UnitType
3.x: QgsUnitType::DistanceUnit
Related
Can someone please help me with this, am trying to use OpenFileDialog class from System.Windows.Forms to open a file dialog and read the selected file. Then, this error showed up. I've referenced it but still the same, below is the code.
`using UnityEngine
using UnityEngine.UI
using System.Windows.Forms;
public class OpenFileButtonScript : MonoBehaviour
{
public TextFieldScript textFieldScript;
public void OpenFile()
{
OpenFileDialog openFileDialog = new OpenFileDialog();
openFileDialog.Filter = "Text Files (*.txt)|*.txt|All Files (*.*)|*.*";
openFileDialog.FilterIndex = 1;
openFileDialog.Multiselect = false;
if (openFileDialog.ShowDialog() == DialogResult.OK)
{
string filePath = openFileDialog.FileName;
string text = System.IO.File.ReadAllText(filePath);
textFieldScript.inputField.text = text;
}
}
}`
It may look like you have access to all of the native Window system libraries, but it just looks like it. In actuality, a lot of the time you're simply given stubs, or shims, that look like the full Window libraries, because there's a certain element that Unity wants to use from those namespaces. If you think about it, the code you present above, what do you think it should do on Android or Nintendo devices? The simple answer is, it simply won't work.
Generally in cases like this, you have to gain access to the native operating system, and perform those calls directly. For example, there is a file browser asset on the Asset Store, that does this for you. It's not free, because the process isn't trivial.
Depending on how much effort you want to put in, you CAN read files from the local file stores (to varying degrees based on platform). It's possible to read the list of files in a location, and use either uGUI or UIToolkit to create your own File Open Dialogue box. Again, this isn't a trivial task either. So you have to be sure that you'd want to go down that path.
I'm developing an application for an nRF52 SoC to access some external devices, kind of detectors in this case, so I have defined a custom format (and its corresponding yaml file) for my device access description node. It is kind of:
n: detectors {
compatible = "foo-detectors";
// Definition of first channel
det0: det_0 {
irq-pins = <13 (GPIO_PULL_UP | GPIO_ACTIVE_LOW)>;
label = "Bar detector channel 1";
};
// Definition of second channel
det1: det_1 {
irq-pins = <17 (GPIO_PULL_UP | GPIO_ACTIVE_LOW)>;
label = "Bar detector channel 2";
};
};
Suppose I have a structure definition for holding data about the pins to which those devices are physically connected, say:
struct foo_detector_desc {
int irqpin;
int irqpin_flags;
}
Using Zephyr macros, I can use from my code the individual values for those nodes. For instance, DT_PROP_BY_IDX(DT_NODELABEL(det0), irq_pins, 0) expands to 13, DT_PROP_BY_IDX(DT_NODELABEL(det0), irq_pins, 1) expands to the value of OR'ed flags GPIO_PULL_UP | GPIO_ACTIVE_LOW.
But I don't want to create a ten-page code full of conditionals in the form DT_NODE_EXISTS(DT_ALIAS(det#)), but something more compact, flexible and maintainable.
I came across Zephyr macro DT_FOREACH_CHILD that is intended for being used in that scenario with which I can create a list with the labels, as showcased in the example embedded in the documentation:
#define LABEL_AND_COMMA(node_id) DT_LABEL(node_id),
const char *child_labels[] = {
DT_FOREACH_CHILD(DT_NODELABEL(n), LABEL_AND_COMMA)
};
Trying to use that for filling a static structures array, I tried following code but, yet it expands to two elements in the array, the structure fields are not initialised with desired values.
#define PIN_INFO_AND_COMMA(node_id) \
{ \
.pin=DT_PROP_BY_IDX(node_id, irq_pins, 0),\
.flags=DT_PROP_BY_IDX(node_id, irq_pins, 1),\
},
const struct detector_data _det_data[] = {
DT_FOREACH_CHILD(DT_NODELABEL(n), PIN_INFO_AND_COMMA)
};
I'm using Visual Studio Code with the nRF Connect plugin.
Is there a way to generate/see how those macros expand when compiled?
What is the correct way for initialising the structure fields (pins, flags)?
BR
It is possible to expand the macros one level at a time in VS Code. It is needed to click over the macro, then select it by double-clicking on it, and a bulb light will, eventually, show up. The option Insert Macro will replace the macro with its expansion.
Regarding using the DTS in code, the code I wrote in my previous post is OK, but I think I found a bug in the debugger. If I don't include any code using the value of _det_data, the debugger doesn't say the constant was optimised-out and displays wrong values when inspecting its content. That made me waste a lot of time.
For anyone interested on using DTS files for nRF devices in Zephyr, I posted all details in a thread in Nordic's developers forum (here).
BR
I'm trying to run this example about how to use Flask-Admin displaying maps: https://github.com/flask-admin/flask-admin/tree/master/examples/geo_alchemy.
In README.rst, there's this instruction:
You will notice that the maps are not rendered. To see them, you will have to register for a free account at Mapbox and set the MAPBOX_MAP_ID and MAPBOX_ACCESS_TOKEN config variables accordingly.
I already have a valid MAPBOX_ACCESS_TOKEN, and I went to MapBox to look for a MAPBOX_MAP_ID. There I read that MAP_ID was deprecated, and now I'll have to obtain a tileset ID, and it's described as a label composed by <my_mapbox_user_name>.the_tileset_ID itself.
So I located the code as they described in the instructions (in my case, mapbox-streets-v8) and fulfilled the config.py parameters:
MAPBOX_MAP_ID = '<my_mapbox_user_name>.mapbox-streets-v8'
MAPBOX_ACCESS_TOKEN = 'pk.eyJ1...'
However, I couldn't see any map displayed or any error message.
How can I fix it?
I think there is a small bug in file Lib\site-packages\flask_admin\static\admin\js\form.js. The original URL generated to get a tile is:
https://api.mapbox.com/styles/v1/mapbox/<MAPBOX_MAP_ID parameter>/tiles/12/2258/2457?access_token=<MAPBOX_ACCESS_TOKEN parameter>
However, the correct one is:
https://api.mapbox.com/styles/v1/<MAPBOX_MAP_ID parameter>/tiles/12/2258/2457?access_token=<MAPBOX_ACCESS_TOKEN parameter>
That is, I had to remove the mapbox word from the URL.
To do that I made some changes in form.js file:
//var mapboxUrl = 'https://api.mapbox.com/styles/v1/mapbox/'+window.MAPBOX_MAP_ID+'/tiles/{z}/{x}/{y}?access_token='+window.MAPBOX_ACCESS_TOKEN
var mapboxUrl = 'https://api.mapbox.com/styles/v1/'+window.MAPBOX_MAP_ID+'/tiles/{z}/{x}/{y}?access_token='+window.MAPBOX_ACCESS_TOKEN
Then, it's working now:
I am working on a project where I am using Ionic and TensorFlow for machine learning. I have converted my TensorFlow model to a tensorflowjs model. I have put the model.json file and shard files of the tensorflowjs model in the assets folder in Ionic. Basically, I have put my tensorflowjs model in the assets folder of ionic. I am wanting to use Capacitor to access the camera and allow users to take photos. Then, the photos will be passed to the tensorflowjs model in assets to get and display a prediction for that user.
Here is my typescript code:
import { Component, OnInit, ViewChild, ElementRef, Renderer2 } from '#angular/core';
import { Plugins, CameraResultType, CameraSource} from '#capacitor/core';
import { DomSanitizer, SafeResourceUrl} from '#angular/platform-browser';
import { Platform } from '#ionic/angular';
import * as tf from '#tensorflow/tfjs';
import { rendererTypeName } from '#angular/compiler';
import { Base64 } from '#ionic-native/base64/ngx';
import { defineCustomElements } from '#ionic/pwa-elements/loader';
const { Camera } = Plugins;
#Component({
selector: 'app-predict',
templateUrl: './predict.page.html',
styleUrls: ['./predict.page.scss'],
})
export class PredictPage{
linearModel : tf.Sequential;
prediction : any;
InputTaken : any;
ctx: CanvasRenderingContext2D;
pos = { x: 0, y: 0 };
canvasElement : any;
photo: SafeResourceUrl;
model: tf.LayersModel;
constructor(public el : ElementRef , public renderer : Renderer2 , public platform : Platform, private base64: Base64,
private sanitizer: DomSanitizer)
{}
async takePicture() {
const image = await Camera.getPhoto({
quality: 90,
allowEditing: true,
resultType: CameraResultType.DataUrl,
source: CameraSource.Camera});
const model = await tf.loadLayersModel('src/app/assets/model.json');
this.photo = this.sanitizer.bypassSecurityTrustResourceUrl(image.base64String);
defineCustomElements(window);
const pred = await tf.tidy(() => {
// Make and format the predications
const output = this.model.predict((this.photo)) as any;
// Save predictions on the component
this.prediction = Array.from(output.dataSync());
});
}
}
In this code, I have imported the necessary tools. Then, I have my constructor function and a takepicture() function. In the takepicture function, I have included functionality for the user to take pictures. However, I am having trouble with passing the pictures taken to the tensorflowjs model to get a prediction. I am passing the picture taken to the tensorflowjs model in this line of code:
const output = this.model.predict((this.photo)) as any;
However, I am getting an error stating that:
Argument of type 'SafeResourceUrl' is not assignable to parameter of type 'Tensor | Tensor[]'.\n Type 'SafeResourceUrl' is missing the following properties from type 'Tensor[]': length, pop, push, concat, and 26 more.
It would be appreciated if I could receive some guidance regarding this topic.
The model is expecting you to pass in a Tensor input, but you're passing it some other image format that isn't in the tfjs ecosystem. You should first convert this.photo to a Tensor, or perhaps easier, convert image.base64String to tensor.
Since you seem to be using node, try this code
// Move the base64 image into a buffer
const b = Buffer.from(image.base64String, 'base64')
// get the tensor
const image = tf.node.decodeImage(b)
// Compute the output
const output = this.model.predict(image) as any;
Other conversion solutions here: convert base64 image to tensor
I have created an AEM Dialog which prompts the user for a set of links and labels.
These links and labels are stored in a jcr node and are used to generate a menu.
To avoid having to create a custom xtype, I am using the acs-commons multifieldpanel solution, which enables me to nest children under the fieldConfig node.
This works great with only 1 Label/Link pair, but when I add a second one - the property cannot be fetched anymore, since instead of a String, it returns the String hashcode.
The property generated by the multifieldpanel in the jcr node is of type String and is filled correctly when inspecting in CRXDE. The problem occurs when I try to fetch the value from within a Sightly HTML file.
Code
Dialog:
Definitions.js:
"use strict";
use(function () {
var CONST = {
PROP_URLS: "definitions",
};
var json = granite.resource.properties[CONST.PROP_URLS];
log.error(json);
return {
urls: json
};
});
Log output
1 element in multifieldpanel
jcr node variable content
definitions: {"listText": "facebook", "listPath": "/content/en"}
log output
{"linkText":"facebook","linkPath":"/content/en"}
Multiple elements in multifieldpanel
jcr node variable content
definitions: {"listText": "facebook", "listPath": "/content/en"},{"listText": "google", "listPath": "/content/en"}
log output
[Ljava.lang.String;#7b086b97
Conclusion
Once the multifieldpanel has multiple components and stores it, when accessing the property the node returns the String hashcode instead of the value of the property.
A colleague has pointed out that I should use the MultiFieldPanelFunctions class to access the properties, but we are using HTML+Sightly+js and are trying to avoid .jsp files at all cost. In JavaScript, this function is not available. Does anyone have any idea how to solve this issue?
That is because, when there is a single item in the multifield, it returns a String, where as it returns a String[] when there is more than a single item configured.
Use the following syntax to read the property as a String array always.
var json = granite.resource.properties[CONST.PROP_URLS] || [];
Additionally, you can also use TypeHints to make sure your dialog saves the value as String[] always, be it single item or multiple items that is configured.
Don't forget that the use() in JS is compiled into Java Byte code and if you are reading Java "primitives", make sure you convert them to JS types. It's part of the Rhino subtleties.
On another note, I tend to not use the granite.* because they are not documented no where, I use the Sightly global objects instead https://docs.adobe.com/content/docs/en/aem/6-0/develop/sightly/global-objects.html
To access properties, I use properties.get("key")
Hope this help.