A script using pyscenedetect to detect scene cuts in mp4 video files within any directory, and split scenes to separate files. Uses adaptive detection method.

pyscenedetect.sh

#!/usr/bin/env bash
#
# extract_scenes.sh
#
# Batch-detect scene cuts in a directory (and all its subdirectories) of
# .mp4 files using PySceneDetect, and save the results (split clips + scene
# list CSVs) to an output directory.
#
# Requirements:
#   pip install scenedetect[opencv]
#   ffmpeg must be installed and on PATH (used by scenedetect for splitting)
#
# Usage:
#   ./extract_scenes.sh <input_dir> <output_dir> [detector] [threshold]
#
# Arguments:
#   input_dir   Directory to search recursively for .mp4 files (required)
#   output_dir  Directory where results will be written (required)
#   detector    Scene detector to use: content, threshold, adaptive (default: adaptive)
#   threshold   Detector sensitivity threshold (default: 4.0)
#
# Output:
#   The input directory's subfolder structure is mirrored under output_dir.
#   For each input video "sub/path/name.mp4", creates:
#     <output_dir>/sub/path/name/name-Scene-001.mp4, name-Scene-002.mp4, ...
#     <output_dir>/sub/path/name/name-Scenes.csv (detected scene cut timecodes)
#
# Example:
#   ./extract_scenes.sh ./videos ./scenes content 30

set -euo pipefail

# ---- Argument parsing -------------------------------------------------

if [[ $# -lt 2 ]]; then
  echo "Usage: $0 <input_dir> <output_dir> [detector] [threshold]" >&2
  echo "  detector:  content | threshold | adaptive   (default: adaptive)" >&2
  echo "  threshold: numeric sensitivity value          (default: 4.0)" >&2
  exit 1
fi

INPUT_DIR="$1"
OUTPUT_DIR="$2"
DETECTOR="${3:-adaptive}"
THRESHOLD="${4:-4.0}"

# ---- Sanity checks ------------------------------------------------------

if [[ ! -d "$INPUT_DIR" ]]; then
  echo "Error: input directory '$INPUT_DIR' does not exist." >&2
  exit 1
fi

if ! command -v scenedetect >/dev/null 2>&1; then
  echo "Error: 'scenedetect' command not found." >&2
  echo "Install it with: pip install scenedetect[opencv]" >&2
  exit 1
fi

if ! command -v ffmpeg >/dev/null 2>&1; then
  echo "Error: 'ffmpeg' not found on PATH. Install ffmpeg to enable video splitting." >&2
  exit 1
fi

case "$DETECTOR" in
  content|threshold|adaptive) ;;
  *)
    echo "Error: unknown detector '$DETECTOR'. Use content, threshold, or adaptive." >&2
    exit 1
    ;;
esac

mkdir -p "$OUTPUT_DIR"

# ---- Collect input files (recursively, including subdirectories) --------

mp4_files=()
while IFS= read -r -d '' f; do
  base="$(basename "$f")"
  if [[ "$base" == ._* ]]; then
    continue
  fi
  mp4_files+=("$f")
done < <(find "$INPUT_DIR" -type f -iname '*.mp4' -print0 | sort -z)

if [[ ${#mp4_files[@]} -eq 0 ]]; then
  echo "No .mp4 files found in '$INPUT_DIR' or its subdirectories." >&2
  exit 1
fi

echo "Found ${#mp4_files[@]} .mp4 file(s) in '$INPUT_DIR' (including subdirectories)."
echo "Detector: $DETECTOR   Threshold: $THRESHOLD"
echo "Output directory: $OUTPUT_DIR"
echo "-----------------------------------------------------"

fail_count=0

# ---- Process each file ---------------------------------------------------

for filepath in "${mp4_files[@]}"; do
  filename="$(basename "$filepath")"
  name="${filename%.*}"

  # Preserve the input's relative subdirectory structure in the output dir,
  # so files with the same name in different subfolders don't collide.
  rel_dir="$(dirname "$filepath")"
  rel_dir="${rel_dir#"$INPUT_DIR"}"
  rel_dir="${rel_dir#/}"

  video_out_dir="$OUTPUT_DIR/$rel_dir/$name"
  mkdir -p "$video_out_dir"

  echo ""
  echo "Processing: ${rel_dir:+$rel_dir/}$filename"
  echo "  -> $video_out_dir"

  if scenedetect \
      -i "$filepath" \
      -o "$video_out_dir" \
      detect-"$DETECTOR" -t "$THRESHOLD" \
      list-scenes \
      split-video ; then
    echo "  Done: $filename"
  else
    echo "  FAILED: $filename" >&2
    fail_count=$((fail_count + 1))
  fi
done

echo ""
echo "-----------------------------------------------------"
if [[ $fail_count -gt 0 ]]; then
  echo "Completed with $fail_count failure(s). See messages above."
  exit 1
else
  echo "All videos processed successfully. Results in '$OUTPUT_DIR'."
fi

The adaptive detection method with a threshold of 4.0 works especially well for scene detection in highly dynamic video content containing CGI, such as sci-fi like Star Trek TNG.