oximedia-cli 0.1.8

//! Scene detection, shot classification, and storyboard generation.
//!
//! Provides scene-related commands using `oximedia-scene` and `oximedia-shots` crates.

use anyhow::{Context, Result};
use clap::Subcommand;
use colored::Colorize;
use std::path::PathBuf;

/// Scene command subcommands.
#[derive(Subcommand, Debug)]
pub enum SceneCommand {
    /// Detect scene/shot boundaries in a video
    Detect {
        /// Input video file
        #[arg(short, long)]
        input: PathBuf,

        /// Shot detection threshold (0.0-1.0, lower = more sensitive)
        #[arg(long, default_value = "0.3")]
        threshold: f32,

        /// Output format: text, json
        #[arg(long, default_value = "text")]
        output_format: String,

        /// Enable dissolve detection
        #[arg(long)]
        dissolves: bool,

        /// Enable fade detection
        #[arg(long)]
        fades: bool,
    },

    /// Classify shot types in a video
    Classify {
        /// Input video file
        #[arg(short, long)]
        input: PathBuf,

        /// Output format: text, json
        #[arg(long, default_value = "text")]
        output_format: String,
    },

    /// Generate a storyboard from video shots
    Storyboard {
        /// Input video file
        #[arg(short, long)]
        input: PathBuf,

        /// Output file path for storyboard image
        #[arg(short, long)]
        output: PathBuf,

        /// Number of columns in storyboard grid
        #[arg(long, default_value = "4")]
        cols: usize,

        /// Thumbnail width
        #[arg(long, default_value = "320")]
        width: u32,
    },
}

/// Handle scene command dispatch.
pub async fn handle_scene_command(command: SceneCommand, json_output: bool) -> Result<()> {
    match command {
        SceneCommand::Detect {
            input,
            threshold,
            output_format,
            dissolves,
            fades,
        } => {
            detect_scenes(
                &input,
                threshold,
                if json_output { "json" } else { &output_format },
                dissolves,
                fades,
            )
            .await
        }
        SceneCommand::Classify {
            input,
            output_format,
        } => classify_shots(&input, if json_output { "json" } else { &output_format }).await,
        SceneCommand::Storyboard {
            input,
            output,
            cols,
            width,
        } => generate_storyboard(&input, &output, cols, width).await,
    }
}

/// Detect scene/shot boundaries.
async fn detect_scenes(
    input: &PathBuf,
    threshold: f32,
    output_format: &str,
    dissolves: bool,
    fades: bool,
) -> Result<()> {
    if !input.exists() {
        return Err(anyhow::anyhow!("Input file not found: {}", input.display()));
    }

    // Configure shot detector
    let mut config = oximedia_shots::ShotDetectorConfig::default();
    config.cut_threshold = threshold;
    config.enable_dissolve_detection = dissolves;
    config.enable_fade_detection = fades;

    let _detector = oximedia_shots::ShotDetector::new(config);

    let file_size = std::fs::metadata(input)
        .context("Failed to read file metadata")?
        .len();

    match output_format {
        "json" => {
            let result = serde_json::json!({
                "input": input.display().to_string(),
                "file_size": file_size,
                "threshold": threshold,
                "dissolve_detection": dissolves,
                "fade_detection": fades,
                "status": "pending_frame_decoding",
                "shots": [],
                "scenes": [],
                "message": "Shot detector initialized; awaiting frame decoding pipeline integration",
            });
            let json_str =
                serde_json::to_string_pretty(&result).context("Failed to serialize result")?;
            println!("{}", json_str);
        }
        _ => {
            println!("{}", "Scene Detection".green().bold());
            println!("{}", "=".repeat(60));
            println!("{:20} {}", "Input:", input.display());
            println!("{:20} {} bytes", "File size:", file_size);
            println!("{:20} {}", "Threshold:", threshold);
            println!("{:20} {}", "Dissolve detection:", dissolves);
            println!("{:20} {}", "Fade detection:", fades);
            println!();

            println!("{}", "Detection Configuration".cyan().bold());
            println!("{}", "-".repeat(60));
            println!("  Cut threshold:      {}", threshold);
            println!(
                "  Dissolve detection: {}",
                if dissolves { "enabled" } else { "disabled" }
            );
            println!(
                "  Fade detection:     {}",
                if fades { "enabled" } else { "disabled" }
            );
            println!();

            println!(
                "{}",
                "Note: Frame decoding pipeline not yet integrated.".yellow()
            );
            println!(
                "{}",
                "Shot detector is ready; frame decoding will enable end-to-end detection.".dimmed()
            );
        }
    }

    Ok(())
}

/// Classify shot types in a video.
async fn classify_shots(input: &PathBuf, output_format: &str) -> Result<()> {
    if !input.exists() {
        return Err(anyhow::anyhow!("Input file not found: {}", input.display()));
    }

    let config = oximedia_shots::ShotDetectorConfig {
        enable_classification: true,
        enable_movement_detection: true,
        enable_composition_analysis: true,
        ..oximedia_shots::ShotDetectorConfig::default()
    };
    let _detector = oximedia_shots::ShotDetector::new(config);

    match output_format {
        "json" => {
            let result = serde_json::json!({
                "input": input.display().to_string(),
                "classification": {
                    "shot_types": ["ECU", "CU", "MCU", "MS", "MLS", "LS", "ELS"],
                    "camera_angles": ["high", "eye_level", "low", "birds_eye", "dutch"],
                    "movements": ["pan", "tilt", "zoom", "dolly", "track", "handheld"],
                },
                "status": "pending_frame_decoding",
                "message": "Shot classifier initialized; awaiting frame decoding pipeline integration",
            });
            let json_str =
                serde_json::to_string_pretty(&result).context("Failed to serialize result")?;
            println!("{}", json_str);
        }
        _ => {
            println!("{}", "Shot Classification".green().bold());
            println!("{}", "=".repeat(60));
            println!("{:20} {}", "Input:", input.display());
            println!();

            println!("{}", "Available Shot Types".cyan().bold());
            println!("{}", "-".repeat(60));
            println!("  ECU  - Extreme Close-up (face details)");
            println!("  CU   - Close-up (head and shoulders)");
            println!("  MCU  - Medium Close-up (waist up)");
            println!("  MS   - Medium Shot (knees up)");
            println!("  MLS  - Medium Long Shot (full body with space)");
            println!("  LS   - Long Shot (full body in environment)");
            println!("  ELS  - Extreme Long Shot (establishing)");
            println!();

            println!("{}", "Camera Analysis".cyan().bold());
            println!("{}", "-".repeat(60));
            println!("  Angles:    high, eye-level, low, bird's eye, Dutch");
            println!("  Movements: pan, tilt, zoom, dolly, track, handheld");
            println!();

            println!(
                "{}",
                "Note: Frame decoding pipeline not yet integrated.".yellow()
            );
        }
    }

    Ok(())
}

/// Generate a storyboard from video shots.
async fn generate_storyboard(
    input: &PathBuf,
    output: &PathBuf,
    cols: usize,
    width: u32,
) -> Result<()> {
    if !input.exists() {
        return Err(anyhow::anyhow!("Input file not found: {}", input.display()));
    }

    println!("{}", "Storyboard Generation".green().bold());
    println!("{}", "=".repeat(60));
    println!("{:20} {}", "Input:", input.display());
    println!("{:20} {}", "Output:", output.display());
    println!("{:20} {}", "Columns:", cols);
    println!("{:20} {}px", "Thumbnail width:", width);
    println!();

    println!(
        "{}",
        "Note: Storyboard generation requires frame decoding pipeline.".yellow()
    );
    println!(
        "{}",
        "Shot detector and storyboard renderer are ready; frame decoding will enable output."
            .dimmed()
    );

    Ok(())
}