Cdaprod

#!/usr/bin/env bash
set -euo pipefail

# ─── Variables (override via environment) ─────────────────────────────────────
RUNNER_USER="${RUNNER_USER:-$USER}"
RUNNER_NAME="${RUNNER_NAME:-repo-runner-ephemeral}"
RUNNER_LABELS="${RUNNER_LABELS:-repo=default,arch=$(uname -m),role=ci,ephemeral}"
RUNNER_ID="${RUNNER_ID:-default}"   # used in paths and service name
RUNNER_ROOT="${RUNNER_ROOT:-/opt/actions-runner/$RUNNER_ID}"
RUNNER_WORK="${RUNNER_WORK:-/home/$RUNNER_USER/actions-work/$RUNNER_ID}"

Cdaprod

#!/bin/bash
# Enhanced file finder script with fzf integration
# Save to /usr/local/bin/f and make executable with: chmod +x /usr/local/bin/f

# Process arguments
depth=""
num_regex='^[0-9]+$'
extensions=()
copy_to_clipboard=true
max_depth=""

Cdaprod

#!/usr/bin/env bash
# Autostart tiler: Chromium (LEFT -> $URL) + terminal (RIGHT -> tmux attach to "recent" + optional follow-up)
# - If a tmux session exists, attach to the most-recent one by default.
# - Optionally inject a FOLLOWUP_CMD into that tmux session as a new window or split.
# - Falls back to plain shell if no tmux sessions exist.
# - Preserves your original tiling logic.

set -euo pipefail

# ---------------- config ----------------

Cdaprod

Here’s a complete workflow to automatically apply your own protections to files via CI Workflow.

How to Use This Workflow

1. Initial Setup

# Save the script as protect-files.sh
chmod +x protect-files.sh

Cdaprod

##### dce example output #####
## Select a service:
##  1) video-api    
##  2) video-web
## ?# 1
## Connecting to service: video-api
##############################

unalias dce
# V1: Docker Compose Exec with built-in service selectiondce() {

Cdaprod

"""
Move each finished recording to a UNC share.

OBS ▶ Tools ▸ Scripts ▸ + ▸ select this file
---------------------------------------------------------
•   Works with Simple or Advanced output mode.
•   No change to your regular Recording Path is required;
    in fact, keeping it on a local SSD makes the initial write faster.
---------------------------------------------------------
Tested with Python 3.11 + OBS 30.

Cdaprod

Updating Drivers for Ubuntu on Raspberry Pi 5 to support the VideoCore VII GPU

✅ GPU Support Overview

1. Mesa / V3D (OpenGL ES & Vulkan) drivers included, thanks to upstream support merged since Mesa 23.3 .
2. Initial desktop installs (e.g., Ubuntu 24.04/24.10) sometimes exhibit slow graphics, GNOME animation lag, even green-screen artifacts—likely due to incomplete or mismatched Mesa stacks .
3. Community feedback highlights that while OpenGL ES/Vulkan are available, you may need to install or update Mesa packages manually (mesa-vulkan-drivers, etc.) .

To Update Drivers:

Cdaprod

docker run --rm -i -v "$PWD":/w linuxserver/blender:4.4.3 \
  blender --factory-startup -b --python - <<'PY'
import bpy, math, os
vid = "/w/phone_screen.mp4"                 # <<< your vertical video
assert os.path.exists(vid), "Video missing"

# ------------------------------------------------------ build objects
bpy.ops.mesh.primitive_plane_add(size=2)
plane = bpy.context.object

Cdaprod

# /scripts/two_cam_auto_vfx.py
"""
Two-Camera VFX Auto-Rig -- Audio-Sync, Insta360-aware Edition
─────────────────────────────────────────────────────────────────────────────
•  Imports hero + witness plates
•  Automatically aligns them via audio-waveform cross-correlation
•  Auto-detects FPS, resolution & 360⇆rectilinear
•  Injects missing XMP → always pano-aware
•  Tracks witness plate on a seeded grid, iteratively cleans & re-solves
•  Builds   RigRoot ▶ WitnessCam ▶ HeroCam hierarchy

Cdaprod

NDI Stream to MoviePy Professional Video Processing

A comprehensive system for capturing NDI streams, recording them, and processing with MoviePy for professional video production workflows.

📦 Cell 1: Install Dependencies

# Install required packages
!pip install ndi-python opencv-python ipywidgets moviepy numpy pillow
# Note: Ensure NDI SDK/Runtime is installed on your system