ObjectDetection | Object detection example using CNTK and Python | Computer Vision library

 by   bhrnjica Python Version: Current License: No License

kandi X-RAY | ObjectDetection Summary

kandi X-RAY | ObjectDetection Summary

ObjectDetection is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Tensorflow, Keras applications. ObjectDetection has no bugs, it has no vulnerabilities and it has low support. However ObjectDetection build file is not available. You can download it from GitHub.

This example is modified version of predefined CNTK Example of Image detection which can be found at

            kandi-support Support

              ObjectDetection has a low active ecosystem.
              It has 8 star(s) with 7 fork(s). There are 2 watchers for this library.
              It had no major release in the last 6 months.
              There are 1 open issues and 2 have been closed. On average issues are closed in 11 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of ObjectDetection is current.

            kandi-Quality Quality

              ObjectDetection has no bugs reported.

            kandi-Security Security

              ObjectDetection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              ObjectDetection does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              ObjectDetection releases are not available. You will need to build from source code and install.
              ObjectDetection has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions, examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed ObjectDetection and discovered the below as its top functions. This is intended to give you an instant insight into ObjectDetection implemented functionality, and help decide if they suit your requirements.
            • Forward the given bottom box
            • Compute the targets according to the given criteria
            • Unmap data
            • Forward a prediction
            • Wrapper for nms
            • Filter boxes based on given size
            • Forward computation
            • Sample foreground rois
            • Get the labels for the bounding box
            • Compute proposals
            • Plot test set results
            • Measure inference time
            • Set up the layers
            • Generate anchors
            • Create a dict of class dict
            • Evaluates a single image
            • Create map files
            • Helper function to filter results
            • Train an object detector
            • Compute reprojection positions
            • Compute test set
            • Stores the evaluation model with the given uuid
            • Get configuration
            • Read image file
            • Generate a list of anchors
            • Download a model by name
            • Set up the layer
            • Resize image to specified max dimension
            Get all kandi verified functions for this library.

            ObjectDetection Key Features

            No Key Features are available at this moment for ObjectDetection.

            ObjectDetection Examples and Code Snippets

            No Code Snippets are available at this moment for ObjectDetection.

            Community Discussions


            Python: Unable to move between loops correctly
            Asked 2022-Feb-10 at 10:49

            I'm writing an image detection bot and as per the advice from a few members, I refactored some code and separated this section into its own function objectDetection I'm trying to do two things with the array image_list

            1. Iterate through the array and if any image is detected I want to immediately print "Avoided" to the terminal and restart the objectDetection function from the beginning of the array.

            I've tried to do this with the flag variable found_anything = True and break it hasn't worked.

            1. Iterate through the full array of images and if nothing at all is found, execute functionTwo()

            I tried to do this with the break at the end of my for i in image_list: loop, it also hasn't worked.

            So far I've tried....

            Reading through these three pages: Break out of two loops and two if statements - Python break out of two loops without disturbing the if statements after it in python Accessing the index in 'for' loops? and I tried both the variable flags and break statements but I can't get either to work.

            I also had a look at this: How to break out of multiple loops? but what is the difference between return and break in python? made me think in my case the top answer wouldn't be appropriate as I don't think I'm returning data outside of my function.

            Is there a way I can adapt this code to achieve my two uses cases above? Am I missing something obvious? I've been thought all the loop tutorials I can find and I'm still struggling, is this simply a difficult way I'm trying to design things? Or am I simply not getting it and should go back over some tutorials.



            Answered 2022-Feb-10 at 10:49

            I'd refactor the whole thing but something like this answers the main question: Refactor your functions such that you can use 'Return' instead of 'Break'

            Source https://stackoverflow.com/questions/71052673


            How should I structure this code to break out of multiple nested loops at once?
            Asked 2022-Feb-09 at 10:06

            I'm learning image detection and python writing a bot for a 2d game. There are certain targets we want to attack and certain targets we want to avoid. One target is displayed on the screen at a time out of a pool of 100 and you click next or attack depending on what you want to do. In doing this you're able to cycle through targets until you find one you want to attack. My code currently checks to see if it finds one of 24 different targets we want to avoid, if it does it avoids that target. Otherwise, it attacks that target.

            At the moment my code:



            Answered 2022-Feb-08 at 13:17

            You can simply stop the inner loop with the python word break inside your condition, so it will stop whenever it is True. This break will not affect the outer loop. For more info about stopping nested loops I would recommend you this article: 5 Ways To Break Out of Nested Loops in Python

            Source https://stackoverflow.com/questions/71034349


            OpenCV: An Array of images: How can I identify which image has been found?
            Asked 2022-Feb-08 at 13:14

            I'm learning OpenCV & Python by writing a bot for a 2d spaceship game.

            The basic principle is there are certain targets my spaceship can defeat and certain spaceships it cannot defeat. One target is displayed on the screen at a time and you click either next or attack depending on what you want to do. In doing this you're able to cycle through targets until you find one you want to attack.

            At the moment my code:

            1. Loads images of ships it cannot defeat into an numpy array
            2. Some pyautigui interactions to skip through menus
            3. Checks the numpy array to determine if it wants to attack or skip the target it's been given
            4. Clicks attack or skip with pyautogui

            This all works correctly and the bot happily searches away and either clicks skip or attack.

            My issue:

            The names of the images being loaded are human-readable e.g. Ship 1.jpg, Ship 2.jpg, Ship 3.jpg When I load them into the numpy array they lose their human-readable component.

            My Question:

            I want to be able to log what was attacked to refine the detection, at the moment I'm able to output the actual array array([[106, 106, 106, ..., 42, 41, 42], but I can't seem to figure out how to keep the human-readable element. How can I keep the human-readable element?

            I'm loading the images like this:



            Answered 2022-Feb-07 at 15:46

            You can append tuples to your list. Where the first element is the name and the second is the image.

            Source https://stackoverflow.com/questions/71019870


            How do I crop a video steam that's already been resized?
            Asked 2022-Feb-08 at 11:53

            I'm using PILs ImageGrab function to capture an application window in real-time for image detection with OpenCV. I've managed to scale the captured window down to increase the speed of image detection. However, I'm getting a number of false positives I can't seem to avoid. I actually only need to capture a small section of the window 761 34 1142 68



            Answered 2022-Feb-08 at 11:53

            Not sure why, but loading the cropped image into a variable and using that variable worked.

            Source https://stackoverflow.com/questions/71032256


            Object detection using YoloV5 in C#
            Asked 2021-Oct-13 at 01:33

            I am new to ML and am trying to make inferences using the YoloV5 model from a C# program. I am aware of the github port, but would like to use torch instead of ML.NET. I found PythonNET nuget package, and this code is working:



            Answered 2021-Oct-13 at 01:33

            Posting this as an answer for anyone else that is seeking a good way to use YOLOv5 in C#, that doesn't require dealing with python, since it is using ML.Net:


            Source https://stackoverflow.com/questions/69332005


            How do I rotate the live object detection screen on Temi Robot?
            Asked 2021-Jul-02 at 07:51

            I am currently using android-demo-app/ObjectDetection/ On Temi Robot, the preloaded images are working so far but when I press "live" to go to live object detection screen, it is rotated 90 degrees to the right.

            Temi robot only have a front facing camera on the same side of the screen.

            I have tried changing textureView.setTransform() imageAnalysisConfig.Builder().setTargetRotation() imageAnalysis.setTargetRotation() but to no avail

            Also tried changing AndroidManifest.xml screenOrientation under activity tag to fullSenor or Landscape but nothing changed.

            I have been looking up and down on the Android Developer CameraX page for an answer first link second link but I can't find any. Maybe I am not smart enough to find the solution here.

            Any help is much appreciated!




            Answered 2021-Jul-02 at 07:51

            I have changed the cameraX version to 1.0.0 from 1.0.0-alpha5

            Source https://stackoverflow.com/questions/68126998


            Text to speech Android studio- Kotlin Doesn't work
            Asked 2021-May-27 at 07:36

            I want my application to say a voice message when I press the button "btnObjectDetection". The application does an object detection task, and I want a welcome message. Currently, the application compiles and runs without problem but does not say anything from the voice message. Please help me :( This is my code:




            Answered 2021-May-27 at 07:36

            Currently, the application compiles and runs without problem but does not say anything from the voice message.

            I see there is no issue in your code for TTS.

            The problem is with your native lib. Just comment on this code once and try once:

            Source https://stackoverflow.com/questions/67714146


            Cannot export Yolov5 model using export
            Asked 2021-May-21 at 23:22

            I've trained Yolov5s model in colab.research env. After training I've moved best.pt to main yolov5 directory and renamed file to yolov5s.pt.

            After calling export.py i got error listed below



            Answered 2021-May-21 at 23:22

            Fixed with linking model in runs directory:

            Source https://stackoverflow.com/questions/67644548


            Why are images not being acquired by the analyze() method?
            Asked 2021-May-10 at 15:44

            Summary/TL;DR: ML Object Detection application is unable to detect objects because images aren't being acquired by analyze() method.


            I'm currently working on a mobile application using CameraX and Google ML Kit written in Java. The purpose of the application is to detect objects with a real time camera preview. I implemented ML Kit using this guide aptly titled "Detect and track objects with ML Kit on Android" (base model option) to detect objects in successive frames within the application.

            However, upon running the application, it launches on my device and the camera preview continues to work but the application does not carry out its intended effect of actually detecting objects and displaying it on my screen. To attempt to resolve this, I had found this StackOverflow answer that very closely resembles this issue. To my dismay, the user had built their application using a custom model (tflite). This differs from mine as I am using the base model. According to my research, this uses the ML Kit's on-device's object detection. The code being applied is restricted to what is present within the aforementioned documentation. Since my IDE (Android Studio) does not display any errors within the syntax, I am unsure as to why any object detection does not appear to be present on my application. Displayed below is the necessary code that had been used:

            CODE ...


            Answered 2021-Apr-02 at 18:33

            As mentioned in the other StackOverflow question you linked, you need to bind the analysis use case to make it work.

            One tip to help debug this is that you can add some Log.d(..) in onSuccess to check the size of the returned object list and in onFailure to print out the exception. Then when running, you could use adb logcat or the AS log tab to check the info to make sure things are running.

            Another improvement you can make is that, you don't need to create a new object detector each frame. You can create one out side the analyze method and reuse it.

            Source https://stackoverflow.com/questions/66892974


            Keep receiving this error "Failed to initialize detector". Am I not loading the tflite model correctly?
            Asked 2021-Feb-26 at 07:42

            I am trying to setup an ImageAnalyzer with my Android app so I can run object classification using Google's ML Kit API. The issue I am currently facing, as the title suggests, is constantly seeing the error "Failed to initialize detector".

            I've reread this tutorial about three times now and followed this post about someone facing the same error (although for a different reason) to no avail. I've also made sure everything with the CameraX API (except the ImageAnalyzer code that I will show in a second) works as expected.

            As mentioned in the ML Kit documentation, here is the code I have regarding setting up a LocalModel, a CustomObjectDetectorOptions, and an ObjectDetector:



            Answered 2021-Feb-26 at 07:42

            I managed to fix my issue before anyone answered, but in case anyone who just started to learn Android like me I'll leave my solution here.

            Basically, remember to create an asset folder in the /src/main directory rather than the /src/androidTest directory :P

            Once I did that, the model loaded correctly and now I just have to figure out how to display the results in my application.

            Source https://stackoverflow.com/questions/66381004

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


            No vulnerabilities reported

            Install ObjectDetection

            To run Nokia3310 object detection example you need a CNTK 2.5, Python 3.5 environment. In order to install CNTK2.5 you have to install Intel Math Kernel Library (MKLML) from this location https://github.com/intel/mkl-dnn/releases. Anyhow in order for proper installation of CNKT consult to the official site.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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