Merge pull request #5 from Pranav0-0Aggarwal/main

Pictopy for GSoC 2024

src/helper/projects.js

@@ -2,9 +2,10 @@ import DefaultLogo from '@/images/default.png'
 import AgoraLogo from '@/images/Agora.png'
 import SSSLogo from '@/images/SSS.png'
 import ResonateLogo from '@/images/Resonate.png'
+import PictoPy from '@/images/Pictopy.png'
 
-// data
 
+// data
 const projects = [
   {
     name: 'Agora Blockchain',
@@ -26,6 +27,13 @@ const projects = [
     },
     logo: AgoraLogo,
   },
+  {
+    name: 'Pictopy',
+    description:
+      'PictoPy is a modern desktop app designed to transform the handling of digital photos. It facilitates efficient gallery management with a robust focus on privacy, offering smart tagging capabilities for photos based on objects, faces, or scenes.',
+    link: { href: 'https://github.com/AOSSIE-Org/PictoPy', label: 'PictoPy' },
+    logo: PictoPy,
+  },
   {
     name: 'EduAid',
     description:
@@ -59,4 +67,5 @@ const projects = [
   },
 ]
 
+
 export default projects

src/pages/ideas/2024/Pictopy.mdx

@@ -0,0 +1,36 @@
+import { IdeaLayout } from '@/components/IdeaLayout'
+
+export const meta = {
+  title: 'PictoPy',
+  description:
+    'PictoPy is a privacy focused desktop app designed to transform the handling of digital photos',
+}
+
+export default (props) => <IdeaLayout meta={meta} {...props} />
+
+### Project Duration: 350 hrs
+
+## Overview:
+
+PictoPy is a modern desktop app designed to transform the handling of digital photos. It facilitates efficient gallery management with a robust focus on privacy, offering smart tagging capabilities for photos based on objects, faces, or scenes.
+
+## Expected Outcomes:
+
+- Intuitive and visually appealing UI designed using PyQt5 or Tkinter.
+- Backend logic implementation by leveraging image recognition libraries, including multiprocessing for efficient processing.
+- Efficient utilization of a lightweight relational database for caching essential photo metadata.
+- Streamlined gallery management through smart tagging of objects, faces, or scenes in photos.
+- Offline functionality that ensures user privacy, with no reliance on remote servers for image processing.
+- Cross-platform packaging for broad accessibility on Windows, macOS, and Linux.
+
+## Required Skills:
+
+- UI/UX Designing
+- Python
+- SQLite
+- PyQt5 or Tkinter for UI development
+- Image Recognition Libraries and Models
+
+## Mentors:
+
+`Pranav Aggarwal`