Skip to content

Latest commit

 

History

History
50 lines (34 loc) · 2.34 KB

File metadata and controls

50 lines (34 loc) · 2.34 KB

Sunny & Dusty Reaction Bot

This project was an ambitious hobby experiment that blended together Instagram scraping, AI-driven video commentary, and creative overlays.
The core idea was to grab funny or trending clips from meme accounts automatically, then process them through a pipeline that gave the illusion of two cats, Sunny and Dusty, reacting to the videos in their own quirky personalities.


Features

🎥 Video Scraping & Upload

  • Uses Instaloader and Instagrapi to log into an Instagram account (via credentials.txt).
  • Scrapes the latest videos from target meme pages.
  • Uploads finished reaction videos back with generated captions.
  • Relevant files: instascraper.py, uploader.py.

🤖 AI-Powered Scripts

  • Extracts frames and analyzes them with a Hugging Face image captioning model + OCR (Tesseract).
  • Generates witty scripts and captions in the voices of Sunny and Dusty using OpenAI GPT models.
  • Relevant file: brianrot.py.

🗣️ Voice & Sound Overlays

  • Dialogue voiced through Amazon Polly (with separate mappings for each cat).
  • Extra cat sound effects layered at specific timestamps.
  • Relevant files: brianrottts.py, catsoundoverlay.py.

🐾 Visual Overlays

  • Cartoon cat avatars and dynamic subtitles placed in video corners.
  • Synchronization with script lines and emotional tags.
  • Relevant files: emotionoverlay.py, subtitlesoverlay.py.

🎬 Compositing

  • Tools like ImageMagick, Tesseract, and MoviePy stitched everything into a polished “reaction” clip.

Status

At its peak, the pipeline could fully automate a reaction-style video:
from scraping a clip → generating dialogue → producing a finished, captioned, voiced, and watermarked output ready for upload.

Now, however, the project is in a broken, archival state.
Several dependencies have changed or drifted out of sync (OpenAI model calls, AWS Polly authentication, Instagram API behavior).
Hard-coded paths, outdated packages, and fragile chaining mean the workflow no longer runs end-to-end.


Reflection

What remains is a fascinating snapshot of a creative coding experiment — equal parts machine learning demo, video editing hack, and playful internet automation — that served as a passion project rather than a production tool.