myDrive | Node.js and mongoDB Google Drive Clone | Runtime Evironment library

 by   subnub JavaScript Version: Current License: GPL-3.0

kandi X-RAY | myDrive Summary

kandi X-RAY | myDrive Summary

myDrive is a JavaScript library typically used in Telecommunications, Media, Media, Entertainment, Server, Runtime Evironment, Nodejs, MongoDB, Docker applications. myDrive has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has medium support. You can download it from GitHub.

MyDrive is an Open Source cloud file storage server (Similar To Google Drive). Host myDrive on your own server or trusted platform and then access myDrive through your web browser. MyDrive uses mongoDB to store file/folder metadata, and supports multiple databases to store the file chunks, such as Amazon S3, the Filesystem, or just MongoDB. MyDrive is built using Node.js, and Typescript. The service now even supports Docker images!. Go to the main myDrive website for more infomation, screenshots, and more.

            kandi-support Support

              myDrive has a medium active ecosystem.
              It has 2917 star(s) with 389 fork(s). There are 60 watchers for this library.
              It had no major release in the last 6 months.
              There are 25 open issues and 22 have been closed. On average issues are closed in 77 days. There are 3 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of myDrive is current.

            kandi-Quality Quality

              myDrive has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              myDrive is licensed under the GPL-3.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

            kandi-Reuse Reuse

              myDrive releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed myDrive and discovered the below as its top functions. This is intended to give you an instant insight into myDrive implemented functionality, and help decide if they suit your requirements.
            • Detects a file for the specified document .
            • Calculate the MD5 hash .
            • This function is used to detect conflicts within a browser . It s used to detect the browser conflicts .
            • Detect SVG conflicts .
            • Replace the current node with the correct position of a given node
            • Run the UI of the diag given script tag .
            • Make an inline SVG image
            • function call when tree is loaded
            • Make a text layer text for the given parameters .
            • Watch mutations and observe
            Get all kandi verified functions for this library.

            myDrive Key Features

            No Key Features are available at this moment for myDrive.

            myDrive Examples and Code Snippets

            No Code Snippets are available at this moment for myDrive.

            Community Discussions


            How can I change background color to red of an image using Python
            Asked 2022-Apr-10 at 11:58

            I have the following code that works great but it doesn't fill all background. I played with numbers but it either makes all image red or not changing the background.
            How can I change the background color of the image?

            Picture i want to change its background]:



            Answered 2022-Apr-09 at 21:47

            I thought we can simply use cv2.floodFill, and fill the white background with red color.
            The issue is that the image is not clean enough - there are JPEG artifacts, and rough edges.

            Using cv2.inRange may bring us closer, but assuming there are some white tulips (that we don't want to turn into red), we may have to use floodFill for filling only the background.

            I came up with the following stages:

            • Convert from RGB to HSV color space.
            • Apply threshold on the saturation channel - the white background is almost zero in HSV color space.
            • Apply opening morphological operation for removing artifacts.
            • Apply floodFill, on the threshold image - fill the background with the value 128.
              The background is going to be 128.
              Black pixels inside the area of the tulips is going to be 0.
              Most of the tulips area stays white.
            • Set all pixels where threshold equals 128 to red.

            Code sample:



            tensorflow, How get value from Tensor
            Asked 2022-Mar-29 at 12:07

            I upload the data in BatchDataset using the image_dataset_from_directory method



            Answered 2022-Mar-29 at 12:07

            You can try using tf.py_function to integrate PIL operations in graph mode. Here is an example with a batch size of 1 to keep it simple (you can change the batch size afterwards):




            Error Training Custom COCO Dataset with Detectron2
            Asked 2022-Mar-29 at 11:17

            I'm trying to train a custom COCO-format dataset with Detectron2 on PyTorch. My datasets are json files with the aforementioned COCO-format, with each item in the "annotations" section looking like this:

            The code for setting up Detectron2 and registering the training & validation datasets are as follows:



            Answered 2022-Mar-29 at 11:17

            It's difficult to give a concrete answer without looking at the full annotation file, but a KeyError exception is raised when trying to access a key that is not in a dictionary. From the error message you've posted, this key seems to be 'segmentation'.

            This is not in your code snippet, but before even getting into network training, have you done any exploration/inspections using the registered datasets? Doing some basic exploration or inspections would expose any problems with your dataset so you can fix them early in your development process (as opposed to letting the trainer catch them, in which case the error messages could get long and confounding).

            In any case, for your specific issue, you can take the registered training dataset and check if all annotations have the 'segmentation' field. A simple code snippet to do this below.



            splitting the data into training and testing in federated learning
            Asked 2022-Mar-10 at 13:35

            I am new in federated learning I am currently experimenting with a model by following the official TFF documentation. But I am stuck with an issue and hope I find some explanation here.

            I am using my own dataset, the data are distributed in multiple files, each file is a single client (as I am planning to structure the model). and the dependant and independent variables have been defined.

            Now, my question is how can I split the data into training and testing sets in each client(file) in federated learning? like what we -normally- do in the centralized ML models The following code is what I have implemented so far: note my code is inspired by the official documentation and this post which is almost similar to my application, but it aims to split the clients as training and testing clients itself while my aim is to split the data inside these clients.



            Answered 2022-Mar-10 at 13:35

            See this tutorial. You should be able to create two datasets (train and test) based on the clients and their data:



            Get google drive file ID from google colab
            Asked 2022-Mar-09 at 13:01

            I'm trying in google colab to get the file ID of a file stored on my google drive.

            When the file is created by a function inside google colab, I get a file ID in the form of "local-xxx" instead of the actual file ID. When the file is manually uploaded to google drive, I get the correct ID.

            Could you please help me fix this? Posting my code below



            Answered 2022-Mar-09 at 13:01

            You might want to check out this answer to a related question.

            It contains the implementation of a workaround based on the following observation (from another answer in the same thread):

            Note: If you are using this in some type of script that is creating new files/folders and quickly reading the '' afterwards, be aware that it can take many seconds for the "real" file id to be generated. If you read the value of '' and it starts with 'local', this means that it has not yet generated an actual file id. In my opinion, the best way to deal with this is to create an asynchronous loop that sleeps between checks, and then returns the file id once it no longer starts with 'local'.

            ps. I would rather post this as a comment, but I don't have enough rep points yet ;-)



            How to clean non Arabic letters from a text file in python?
            Asked 2022-Mar-06 at 20:25

            UPDATE- Very new to python, How to clean the text from everything but Arabic letters. I used regex function but without success.

            This is my code



            Answered 2021-Sep-30 at 00:11

            As far as I understood you. You want just to clean non-arabic chars (so chars like 1 @ ? gonna not be deleted).

            If you want another char to be deleted just add it to charsotdelete.

            If you have any questions let me know.



            Efficient way to delete image of the same size
            Asked 2022-Feb-23 at 09:17

            I have many images in a folder and I am want to delete images of the same size. My code below, using PIL, works but I want to know if there is a more efficient way to achieve this.



            Answered 2022-Feb-23 at 09:16

            You can keep a dictionary of sizes and delete any images that have a size that have already been seen. That way you don't need a nested loop, and don't have to create Image objects for the same file multiple times.



            Error : Input to reshape is a tensor with 327680 values, but the requested shape requires a multiple of 25088
            Asked 2022-Feb-15 at 09:17

            I am facing an error while running my model.

            Input to reshape is a tensor with 327680 values, but the requested shape requires a multiple of 25088

            I am using (256 * 256) images. I am reading the images from drive in google colab. Can anyone tell me how to get rid of this error?

            my colab code:



            Answered 2022-Feb-15 at 09:17

            The problem is the default shape used for the VGG19 model. You can try replacing the input shape and applying a Flatten layer just before the output layer. Here is a working example:



            How Can I Increase My CNN Model's Accuracy
            Asked 2022-Feb-12 at 00:10

            I built a cnn model that classifies facial moods as happy , sad, energetic and neutral faces. I used Vgg16 pre-trained model and freezed all layers. After 50 epoch of training my model's test accuracy is 0.65 validatation loss is about 0.8 .

            My train data folder has 16000(4x4000) , validation data folder has 2000(4x500) and Test data folder has 4000(4x1000) rgb images.

            1)What is your suggestion to increase the model accuracy?

            2)I have tried to do some prediction with my model , predicted class is always same. What can cause the problem?

            What I Have Tried So Far ?

            1. Add dropout layer (0.5)
            2. Add Dense (256, relu) before last layer
            3. Shuff the train and validation datas.
            4. Decrease the learning rate to 1e-5

            But I could not the increase validation and test accuracy.

            My Codes



            Answered 2022-Feb-12 at 00:10

            Well a few things. For training set you say you have 16,0000 images. However with a batch size of 32 and steps_per_epoch= 100 then for any given epoch you are only training on 3,200 images. Similarly you have 2000 validation images, but with a batch size of 32 and validation_steps = 5 you are only validating on 5 X 32 = 160 images. Now Vgg is an OK model but I don't use it because it is very large which increases the training time significantly and there are other models out there for transfer learning that are smaller and even more accurate. I suggest you try using EfficientNetB3. Use the code



            Colab: (0) UNIMPLEMENTED: DNN library is not found
            Asked 2022-Feb-08 at 19:27

            I have pretrained model for object detection (Google Colab + TensorFlow) inside Google Colab and I run it two-three times per week for new images I have and everything was fine for the last year till this week. Now when I try to run model I have this message:



            Answered 2022-Feb-07 at 09:19

            It happened the same to me last friday. I think it has something to do with Cuda instalation in Google Colab but I don't know exactly the reason


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


            No vulnerabilities reported

            Install myDrive

            Windows users will usually need both the microsoft visual build tools, and python 2. These are required to build the sharp module:.
            Node.js (15 Recommended)
            MongoDB (Unless using a service like Atlas)
            Visual Tools:
            Python 2:


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