Vision | Sidewalk Detection Algorithm based on Line Detection | Computer Vision library

 by   codertimo Java Version: Current License: No License

kandi X-RAY | Vision Summary

kandi X-RAY | Vision Summary

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

Sidewalk Detection Algorithm based on Line Detection
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            kandi-support Support

              Vision has a low active ecosystem.
              It has 21 star(s) with 2 fork(s). There are 6 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 4 open issues and 13 have been closed. On average issues are closed in 20 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Vision is current.

            kandi-Quality Quality

              Vision has 0 bugs and 0 code smells.

            kandi-Security Security

              Vision has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              Vision code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

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

            kandi-Reuse Reuse

              Vision releases are not available. You will need to build from source code and install.
              Vision has no build file. You will be need to create the build yourself to build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed Vision and discovered the below as its top functions. This is intended to give you an instant insight into Vision implemented functionality, and help decide if they suit your requirements.
            • Opens the camera with the specified width and height
            • Open camera .
            • Installs OpenCV service .
            • Called when OpenCV library is connected .
            • This method initializes camera preview
            • Converts a vector into a Matcher .
            • Load a vertex shader .
            • Delivers the camera frame .
            • Completes state
            • Returns a string representation of a CVType value .
            Get all kandi verified functions for this library.

            Vision Key Features

            No Key Features are available at this moment for Vision.

            Vision Examples and Code Snippets

            No Code Snippets are available at this moment for Vision.

            Community Discussions

            QUESTION

            Camera calibration, focal length value seems too large
            Asked 2022-Mar-16 at 16:58

            I tried a camera calibration with python and opencv to find the camera matrix. I used the following code from this link

            https://automaticaddison.com/how-to-perform-camera-calibration-using-opencv/

            ...

            ANSWER

            Answered 2021-Sep-13 at 11:31

            Your misconception is about "focal length". It's an overloaded term.

            • "focal length" (unit mm) in the optical part: it describes the distance between the lens plane and image/sensor plane
            • "focal length" (unit pixels) in the camera matrix: it describes a scale factor for mapping the real world to a picture of a certain resolution

            1750 may very well be correct, if you have a high resolution picture (Full HD or something).

            The calculation goes:

            f [pixels] = (focal length [mm]) / (pixel pitch [µm / pixel])

            (take care of the units and prefixes, 1 mm = 1000 µm)

            Example: a Pixel 4a phone, which has 1.40 µm pixel pitch and 4.38 mm focal length, has f = ~3128.57 (= fx = fy).

            Another example: A Pixel 4a has a diagonal Field of View of approximately 77.7 degrees, and a resolution of 4032 x 3024 pixels, so that's 5040 pixels diagonally. You can calculate:

            f = (5040 / 2) / tan(~77.7° / 2)

            f = ~3128.6 [pixels]

            And that calculation you can apply to arbitrary cameras for which you know the field of view and picture size. Use horizontal FoV and horizontal resolution if the diagonal resolution is ambiguous. That can happen if the sensor isn't 16:9 but the video you take from it is cropped to 16:9... assuming the crop only crops vertically, and leaves the horizontal alone.

            Why don't you need the size of the chessboard squares in this code? Because it only calibrates the intrinsic parameters (camera matrix and distortion coefficients). Those don't depend on the distance to the board or any other object in the scene.

            If you were to calibrate extrinsic parameters, i.e. the distance of cameras in a stereo setup, then you would need to give the size of the squares.

            Source https://stackoverflow.com/questions/69159247

            QUESTION

            React-native-vision-camera can't access to normal camera in back
            Asked 2022-Mar-07 at 07:02

            i am trying to use 'normal' camera on my iphone 11 pro. I use react-native-vision-camera. When i run this code:

            ...

            ANSWER

            Answered 2022-Mar-07 at 07:02

            tl;dr - Single-lens smartphone cameras commonly have a wide-angle lens of roughly 22mm and 30mm equivalent. So basically, you would want to choose wide-angle, as this is the "normal" type.

            based on the react-native documentation, there are three Identifiers for a physical camera (one that exists on the back/front of the device):

            "ultra-wide-angle-camera" | "wide-angle-camera" | "telephoto-camera"

            "ultra-wide-angle-camera": A built-in camera with a shorter focal length than that of a wide-angle camera. (focal length between below 24mm)

            "wide-angle-camera": A built-in wide-angle camera. (focal length between 24mm and 35mm)

            "telephoto-camera": A built-in camera device with a longer focal length than a wide-angle camera. (focal length between above 85mm)

            now that we have that settled, let's take a look at cameras' focal lengths that are equivalent to phone cameras' focal length (resource)

            Camera type Focal length Angle-of-view Wide-angle 22mm to 30mm ~84° to ~62° Telephoto 50mm to 80mm ~40° to ~25° Ultrawide-angle 12mm to 18mm ~112° to ~90° Periscope 103mm to 125mm ~20° to ~16°

            what is considered a "normal" focal length is 35mm, so you should choose wide-angle since it is the closest (and eventually with the angle of view the user might be even closer to 35mm), further more the wide-angle is the most common focal-length for phone camera lens

            Source https://stackoverflow.com/questions/71287639

            QUESTION

            Create new boolean fields based on specific bigrams appearing in a tokenized pandas dataframe
            Asked 2022-Feb-16 at 20:47

            Looping over a list of bigrams to search for, I need to create a boolean field for each bigram according to whether or not it is present in a tokenized pandas series. And I'd appreciate an upvote if you think this is a good question!

            List of bigrams:

            ...

            ANSWER

            Answered 2022-Feb-16 at 20:28

            You could use a regex and extractall:

            Source https://stackoverflow.com/questions/71147799

            QUESTION

            How do I remove background from an image like this?
            Asked 2022-Jan-12 at 17:44

            I want to remove the background, and draw the outline of the box shown in the image(there are multiple such images with a similar background) . I tried multiple methods in OpenCV, however I am unable to determine the combination of features which can help remove background for this image. Some of the approaches tried out were:

            • Edge Detection - Since the background itself has edges of its own, using edge detection on its own(such as Canny and Sobel) didnt seem to give good results.
            • Channel Filtering / Thresholding - Both the background and foreground have a similar white color, so I was unable to find a correct threshold to filter the foreground.
            • Contour Detection - Since the background itself has a lot of contours, just using the largest contour area, as is often used for background removal, also didnt work.

            I would be open to tools in Computer Vision or of Deep Learning (in Python) to solve this particular problem.

            ...

            ANSWER

            Answered 2022-Jan-07 at 01:57
            The Concept

            This is one of the cases where it is really useful to fine-tune the kernels of which you are using to dilate and erode the canny edges detected from the images. Here is an example, where the dilation kernel is np.ones((4, 2)) and the erosion kernel is np.ones((13, 7)):

            The Code

            Source https://stackoverflow.com/questions/70556110

            QUESTION

            After updating Gradle to 7.0.2, Element type “manifest” must be followed by either attribute specifications, “>” or “/>” error
            Asked 2021-Dec-29 at 11:19

            So today I updated Android Studio to:

            ...

            ANSWER

            Answered 2021-Jul-30 at 07:00

            Encountered the same problem. Update Huawei services. Please take care. Remember to keep your dependencies on the most up-to-date version. This problem is happening on Merged-Manifest.

            Source https://stackoverflow.com/questions/68575710

            QUESTION

            Combining Object Detection with Text to Speech Code
            Asked 2021-Dec-28 at 16:46

            I am trying to write an object detection + text-to-speech code to detect objects and produce a voice output on the raspberry pi 4. However, as of right now, I am trying to write a simple python script that incorporates both elements into a single .py file and preferably as a function. I will then run this script on the raspberry pi. I want to give credit to Murtaza's Workshop "Object Detection OpenCV Python | Easy and Fast (2020)" and https://pypi.org/project/pyttsx3/ for the Text to speech documentation for pyttsx3. I have attached the code below. I have tried running the program and I always keep getting errors with the Text to speech code (commented lines 33-36 for reference). I believe it is some looping error but I just can't seem to get the program to run continuously. For instance, if I run the code without the TTS part, it works fine. Otherwise, it runs for perhaps 3-5 seconds and suddenly stops. I am a beginner but highly passionate in computer vision, and any help is appreciated!

            ...

            ANSWER

            Answered 2021-Dec-28 at 16:46

            I installed pyttsx3 using the two commands in the terminal on the Raspberry Pi:

            1. sudo apt update && sudo apt install espeak ffmpeg libespeak1
            2. pip install pyttsx3

            I followed the video youtube.com/watch?v=AWhDDl-7Iis&ab_channel=AiPhile to install pyttsx3. My functional code should also be listed above. My question should be resolved but hopefully useful to anyone looking to write a similar program. I have made minor tweaks to my code.

            Source https://stackoverflow.com/questions/70129247

            QUESTION

            Android Huawei image segmentation not working on release build
            Asked 2021-Dec-27 at 09:39

            I'm using Huawei image segmentation for background removal from images. This code work perfectly fine on debug build but it does not work on a release build. I don't understand what could be the case.

            Code:

            ...

            ANSWER

            Answered 2021-Dec-27 at 08:50

            Stuff like this usually happens when you have ProGuard enabled but not correctly configured. Make sure to add appropriate rules to proguard-rules.pro file to prevent it from obfuscating relevant classes.

            Information about this is usually provided by the library developers. After a quick search I came up with this example. Sources seem to be documented well enough, so that it should not be a problem to find the correct settings.

            Keep in mind that you probably need to add rules for more than one library.

            Source https://stackoverflow.com/questions/70492455

            QUESTION

            How to get post categories from an object in array
            Asked 2021-Dec-16 at 09:19

            Im trying to filter posts by categories from this array

            ...

            ANSWER

            Answered 2021-Dec-16 at 09:19

            You are getting the undefined error because for few of the cases the post_categories array is empty and if u try accessing the 0th element it will throw an error. So add a null check for the array length and for id something like below

            Source https://stackoverflow.com/questions/70361187

            QUESTION

            How do you create a new AVAsset video that consists of only frames from given `CMTimeRange`s of another video?
            Asked 2021-Dec-12 at 17:03

            Apple's sample code Identifying Trajectories in Video contains the following delegate callback:

            ...

            ANSWER

            Answered 2021-Dec-12 at 17:03

            By the time you identify a trajectory in captured video frames or from frames decoded from a file you may not have the initial frames in memory any more, so the easiest way to create your file containing only trajectories is to keep the original file on hand, and then insert its trajectory snippets into an AVComposition which you then export using AVAssetExportSession.

            This sample captures frames from the camera, encodes them to a file whilst analysing them for trajectories and after 20 seconds, it closes the file and then creates the new file containing only trajectory snippets.

            If you're interested in detecting trajectories in a pre-existing file, it's not too hard to rewire this code.

            Source https://stackoverflow.com/questions/70134980

            QUESTION

            How do you implement React-native-gesture-handler with React Navigation 6.x Native Stack Navigator (RN>0.6)?
            Asked 2021-Nov-30 at 08:25

            So, I am building a prototype android app as an internship project for a startup in React Native v0.66. I was new to RN but not React when I set up the project. My choice for navigation fell upon React Navigation 6.x and their Native Stack Navigator because it performs better than the regular Stack Navigator, although is not as customizable according to docs.

            Now I want to use react-native-gesture-handler in my project. According to their docs,

            "If you are using a native navigation library like wix/react-native-navigation you need to follow a different setup for your Android app to work properly. The reason is that both native navigation libraries and Gesture Handler library need to use their own special subclasses of ReactRootView.

            Instead of changing Java code you will need to wrap every screen component using gestureHandlerRootHOC on the JS side. This can be done for example at the stage when you register your screens."

            I suppose this includes React Navigation-Native Stack Navigator as well? There is code example of how to implement RNGH with wix/react-native-navigation, but none, anywhere, for my case:

            ...

            ANSWER

            Answered 2021-Nov-30 at 08:25

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

            Vulnerabilities

            No vulnerabilities reported

            Install Vision

            You can download it from GitHub.
            You can use Vision like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Vision component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

            Support

            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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