imagelabeler | Add labels to an image | Data Labeling library
kandi X-RAY | imagelabeler Summary
kandi X-RAY | imagelabeler Summary
Add labels to an image
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Top functions reviewed by kandi - BETA
- get position of tooltip
- draw a label based on a label
- show image box
- Downloads a file as a Blob object .
- Draw the canvas
imagelabeler Key Features
imagelabeler Examples and Code Snippets
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Trending Discussions on imagelabeler
QUESTION
I'm a beginner in kotlin and I use coroutine for the first time in android.
I want to get the value of classification after the async call is completed and transfer the result to the fragment, where this function exists in the non-activity class.
I wrote the following function but it return an empty string with the first click of the button and return the value with the second click.
Could you please help me?
The calling in a fragment:
...ANSWER
Answered 2022-Mar-22 at 16:24The problem here is that you're not waiting for the actual asynchronous operation (which is callback-based). You're wrapping it in an unnecessary async which you then await, but the underlying operation (imageLabeler.process()) is still asynchronous within the async block and nothing waits for it.
Here are several things about your code:
using
await()right afterasync { ... }defeats the purpose ofasync. The goal of usingasyncis to run whatever is inside the block concurrently with what is outside (after) the block, until youawait()it. When youawait()immediately, it's as if you simply called the code that's inside directly. So you can removeasync,awaitandcoroutineScope, which you don't seem to need.there is no need for
var x = nullfollowed byx = something- just initialize the variable right away. Also, if it won't be changed later, you can usevalinstead.
What you probably want instead is to wrap your callback-based API into a suspending function. That you can do with suspendCoroutine or suspendCancellableCoroutine (depending on whether the API you call is cancellable and/or if you want your function to be cancellable anyway).
The doc provides examples on how to do that.
QUESTION
I was trying a demo code on the google_ml_kit plugin and ran into this error-
ANSWER
Answered 2022-Feb-12 at 05:04The exception appeared because the plug-in google_ml_kit is not supported for web but only iOS and android
QUESTION
I have a Google MLKit model for labeling an Image after capturing the image, but everytime I tried to process the Image, it always give me this error:
label process error:: Pipeline failed to fully start: Calculator::Open() for node "ClassifierClientCalculator" failed: #vk The TFLite Model Metadata must not contain label maps when
text_label_map_fileis used.
Here's my MLKit image labeler configuration code (this code is based on MLKit's documentation):
...ANSWER
Answered 2021-Apr-06 at 18:13Here's my understanding based on the error message:
Given you are using the LocalModel(manifestPath: manifestPath) API, it is expecting a legacy TFLite model format where the label map is provided through a separate text file and the model.tflite itself does not contain the label map. That's why your file before your model update works.
To use your updated model.tflite (which seems to contain the lab map inside its metadata), I think you can try the following to use the model.tflite file directly with the custom models API without going through the filename.json manifest:
QUESTION
I'm new to MLKit.
One of the first thing I've noticed from looking at the docs as well as the sample MLKit apps is that there seems to be multiple ways to attach/use image processors/analyzers.
In some cases they demonstrate using the ImageAnalyzer api https://developers.google.com/ml-kit/vision/image-labeling/custom-models/android
...ANSWER
Answered 2021-Feb-05 at 19:10The difference is due to the underlying camera implementation. The analyzer interface is from CameraX while the processor needs to be written by developer for camera1.
If you want to use android.hardware.Camera, you need to follow the example to create a processor and feed camera output to MLKit. If you want to use cameraX, then you can follow the example in the vision sample app and find CameraXLivePreviewActivity.
QUESTION
So I have an Android app where a user can take a picture of a bird using the camera app and it will classify the bird. I followed the documentation for label images with a custom model for Android and it's not working. I have this piece of code in my onActivityResult:
ANSWER
Answered 2020-Jul-24 at 18:40Looking at the stacktrace, it seems like the input Bitmap is taken directly from the camera and it resides in-memory (Bitmap.Config.HARDWARE). ML Kit only supports bitmap of ARGB_8888 format so please try:
QUESTION
I'm working in an app flutter. Android working fine but in ios no. I need some help to run this on ios mobile. I'm using lib: google_maps_flutter: ^0.5.27+3 and firebase_ml_vision: ^0.9.3+8. Xcode 11.4.1 and Mac os Catalina 10.15.4. Someone knows how to solve this. I didn't found yet.
...ANSWER
Answered 2020-May-14 at 19:57Probably the error is on some of the XCode project files, try:
- Make a backup of your project.
Run this command
flutter clean && \ rm ios/Podfile ios/Podfile.lock pubspec.lock && \ rm -rf ios/Pods ios/Runner.xcworkspace && \ flutter run
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