I've been tasked to solve a ML/DL problem.
But due to the processing limitations of my system the progress of developing the program further has come to a halt. It is a requirement of my program that it uses a GUI for the layman user, which I've already designed and implemented.
Now due to system limitations, I was wondering if I could somehow connect this python GUI instance on my local machine to Google Colab. The user could then use the GUI interface to upload files to google colab and upon pressing the submit button google colab would import these files. It would then do the ML/DL processing on these files and return some output back to the GUI interface for the user.
Any ideas of how I would achieve this?
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I'm building a prototype for a bin packing app.
The front-end runs on the browser. Where it takes a picture and sends it to the back-end to extract the "board outline" from the image and then responds to front-end with a svg of it.
To finally add some shapes and pack in the bin.
I'm working with rust both back-end and front-end through wasm.
The back-end is polyglot, I use rust-ffi to encrust some java and pyhton code. I'm reciclyng the bin packing algorithm from a java code. And the image conversion is being done by the owners of the project with python.
The point is that the whole front-end runs in the browser and these guys at some point in their process need the user to click on the image and for that they display a dialog with the native windows of the operating system.
Initially this prototype will not be deployed in a network, but everything will be deployed on the same host as the client, so ultimately it will not be a catastrophic problem.
The question is that it totally impairs the usability of the project so I want to know if it is possible to somehow integrate the popup window of the python process in a browser dialog?
Note:
The python program was made with opencv
I have a Google Colab Notebook that is using psycopg2 to connect with a free Heroku PostgreSQL instance. I'd like to share the notebook with some colleagues for educational purposes to view and run the code.
There is nothing sensitive related to the account / database but would still like to hide the credentials used to make the initial connection without restricting their access.
My work around was creating a Python module that contained a function who performed the initial connection with credentials. I converted the module into a binary .pyc, uploaded it to Google Drive, downloaded the binary into the Notebook's contents via shell command then used it as an import.
It obviously isn't secure but provides the obfuscation layer I was looking for.
I have tried several ways ,but not able to resolve the problem .can we customize browsing functionality in colab?
I am using uploaded = files.upload() for browse button functionality in colab, but I want whenever user click browse direct dialogue box for given path should open rather than choose files option.
The situation that you discuss is possible if you build your own customized application. But google collab is a proprietary application of google and it has a certain set of operations to do tasks smoothly. Apart from that as you say
"user click browse direct dialogue box for given path should open rather than choose files option"
how it is possible that google colab now what you want to upload. That's why google colab gives you the facility to upload the file as per your requirement. It makes the application more robust and easy to use.
As per Google colab documentation, it is not possible.
I was trying to figure out if it is possible to run a python script (watchdog) to monitor when a file is inserted into a folder that is hosted by the OneDrive platform. I work in a company and we want to monitor a folder that is shared with everyone. And I think that a program that is able to monitor OneDrive Side is better than installing the same program for all clients of this OneDrive Clound application. Because I can't guarantee that local changes will be loaded and shared with everyone, and some users could make the mistake of stopping the monitoring program.
I am working on a module where I need to automate an application in an Android Device using Python. But here is a challenge that I am facing is that the application has visualization part which is a Machine movement. To move the machine, I need to give the inputs from another external application which has fields like North,East,Elevation etc. These values are taken from that external application and Machine gets moved in the android device.
My thoughts are like to use module
import subprocess
Can some one suggest me if my idea is correct or any other procedures to ahead....I got struck.
Till now no coding has been done and I need to project to convince the team first. We shouldn't use any APIs of the external application.