scene-actor-extraction/scripts/make_gallery.py

#!/usr/bin/env python3
"""make_gallery.py — fetch actor images for a movie and build gallery.json.

Fetches the cast from TMDB, downloads actor profile images, runs the C++
embed_faces binary (SCRFD + ArcFace, same models as scene_analyze) to produce
embeddings, then writes gallery.json.

Requirements:
    pip install requests Pillow

Usage:
    # By IMDB movie ID (most natural — resolves to TMDB automatically):
    python scripts/make_gallery.py \\
        --tmdb-key YOUR_KEY \\
        --imdb-id tt0137523 \\
        --output gallery.json

    # Or directly with a TMDB movie ID:
    python scripts/make_gallery.py \\
        --tmdb-key YOUR_KEY \\
        --movie-id 550 \\
        --output gallery.json

    # Additional options:
    #   --embed-bin build/embed_faces   path to embed_faces binary
    #   --models-dir models/            directory with ONNX models
    #   --max-actors 20                 how many cast members to include
    #   --images-per-actor 3            profile images to download per actor
    #   --image-dir /tmp/gallery_imgs   where to cache downloaded images

Get a free TMDB API key at: https://www.themoviedb.org/settings/api
"""

import argparse
import json
import os
import subprocess
import sys
import tempfile
import time
from pathlib import Path

import io

import requests
from PIL import Image

TMDB_BASE = "https://api.themoviedb.org/3"
TMDB_IMG  = "https://image.tmdb.org/t/p/original"

# ── TMDB helpers ──────────────────────────────────────────────────────────────

def tmdb_get(path: str, token: str, **params) -> dict:
    url = TMDB_BASE + path
    if token.startswith("eyJ"):
        headers = {"Authorization": f"Bearer {token}", "Accept": "application/json"}
        r = requests.get(url, params=params, headers=headers, timeout=10)
    else:
        params["api_key"] = token
        r = requests.get(url, params=params, headers={"Accept": "application/json"}, timeout=10)
    r.raise_for_status()
    return r.json()


def tmdb_id_from_imdb(imdb_id: str, key: str) -> int:
    data = tmdb_get(f"/find/{imdb_id}", key, external_source="imdb_id")
    results = data.get("movie_results", [])
    if not results:
        raise ValueError(f"No TMDB movie found for IMDB ID {imdb_id}")
    return results[0]["id"]


def fetch_cast(movie_id: int, key: str, max_actors: int) -> list[dict]:
    """Return list of {id, name, imdb_id, profile_images: [...url...]}."""
    credits = tmdb_get(f"/movie/{movie_id}/credits", key)
    cast = credits.get("cast", [])[:max_actors]

    actors = []
    for member in cast:
        person_id = member["id"]

        # Get IMDB ID for this person
        ext = tmdb_get(f"/person/{person_id}/external_ids", key)
        imdb_id = ext.get("imdb_id") or f"tmdb_{person_id}"

        # Get profile images (sorted by vote_average desc by TMDB)
        images_data = tmdb_get(f"/person/{person_id}/images", key)
        profiles = images_data.get("profiles", [])
        image_urls = [TMDB_IMG + p["file_path"] for p in profiles if p.get("file_path")]

        if not image_urls:
            print(f"  [warn] no images for {member['name']}, skipping", file=sys.stderr)
            continue

        actors.append({
            "id":            person_id,
            "name":          member["name"],
            "imdb_id":       imdb_id,
            "profile_images": image_urls,
        })
        time.sleep(0.05)  # be polite to TMDB

    return actors


# ── Image download ────────────────────────────────────────────────────────────

def download_images(actor: dict, dest_dir: Path, n: int) -> list[Path]:
    """Download up to n profile images for an actor into dest_dir."""
    dest_dir.mkdir(parents=True, exist_ok=True)
    paths = []
    for i, url in enumerate(actor["profile_images"][:n]):
        out = dest_dir / f"{i:02d}.jpg"
        if out.exists() and out.stat().st_size > 1024:
            paths.append(out)
            continue
        try:
            r = requests.get(url, timeout=15)
            r.raise_for_status()
            Image.open(io.BytesIO(r.content)).convert("RGB").save(out, "JPEG")
            paths.append(out)
        except Exception as e:
            print(f"  [warn] download failed: {url}: {e}", file=sys.stderr)
    return paths


# ── Embedding via embed_faces binary ─────────────────────────────────────────

def embed_images(image_paths: list[Path], embed_bin: str,
                 detector: str, arcface: str) -> list[dict | None]:
    """
    Call the C++ embed_faces binary on a list of images.
    Returns a list of result dicts (or None if no face / error) per image.
    """
    if not image_paths:
        return []

    cmd = [
        embed_bin,
        "--detector", detector,
        "--arcface", arcface,
    ] + [str(p) for p in image_paths]

    try:
        proc = subprocess.run(cmd, capture_output=True, text=True, check=True)
    except subprocess.CalledProcessError as e:
        print(f"[error] embed_faces failed:\n{e.stderr}", file=sys.stderr)
        return [None] * len(image_paths)

    try:
        results = json.loads(proc.stdout)
    except json.JSONDecodeError as e:
        print(f"[error] embed_faces output is not valid JSON: {e}", file=sys.stderr)
        return [None] * len(image_paths)

    return results


# ── Gallery assembly ─────────────────────────────────────────────────────────

def build_gallery(movie_id: int, key: str, embed_bin: str,
                  detector: str, arcface: str,
                  max_actors: int, images_per_actor: int,
                  image_root: Path) -> dict:
    """Fetch cast, download images, embed, return gallery dict."""
    print(f"Fetching cast for TMDB movie {movie_id}…", file=sys.stderr)
    actors = fetch_cast(movie_id, key, max_actors)
    print(f"Found {len(actors)} actors with images", file=sys.stderr)

    gallery_actors = []

    for actor in actors:
        safe_name = actor["name"].replace(" ", "_")
        actor_dir = image_root / f"{actor['imdb_id']}_{safe_name}"

        print(f"\n{actor['name']} ({actor['imdb_id']})", file=sys.stderr)
        image_paths = download_images(actor, actor_dir, images_per_actor)
        if not image_paths:
            print("  no images downloaded, skipping", file=sys.stderr)
            continue

        print(f"  embedding {len(image_paths)} image(s)…", file=sys.stderr)
        results = embed_images(image_paths, embed_bin, detector, arcface)

        embeddings    = []
        source_images = []
        for path, res in zip(image_paths, results):
            if res is None or res.get("embedding") is None:
                reason = res.get("error", "unknown") if res else "binary error"
                print(f"  [skip] {path.name}: {reason}", file=sys.stderr)
                continue
            embeddings.append(res["embedding"])
            source_images.append(path.name)
            print(f"  [ok]   {path.name}  conf={res.get('confidence', 0):.2f}",
                  file=sys.stderr)

        if not embeddings:
            print("  no valid embeddings, skipping actor", file=sys.stderr)
            continue

        gallery_actors.append({
            "imdb_id":      actor["imdb_id"],
            "name":         actor["name"],
            "source_images": source_images,
            "embeddings":   embeddings,
        })
        print(f"  → {len(embeddings)} embedding(s) stored", file=sys.stderr)

    return {"actors": gallery_actors}


# ── Entry point ───────────────────────────────────────────────────────────────

def main():
    parser = argparse.ArgumentParser(
        description="Fetch TMDB cast images and build gallery.json via embed_faces")
    parser.add_argument("--tmdb-key",  required=True,
                        help="TMDB Bearer token (API Read Access Token from themoviedb.org/settings/api)")
    group = parser.add_mutually_exclusive_group(required=True)
    group.add_argument("--imdb-id",
                        help="IMDB movie ID, e.g. tt0137523 — looked up via TMDB automatically")
    group.add_argument("--movie-id",  type=int,
                        help="TMDB movie ID (alternative to --imdb-id)")
    parser.add_argument("--output",          required=True,  help="Output gallery.json path")
    parser.add_argument("--embed-bin",       default="build/embed_faces",
                        help="Path to embed_faces binary (default: build/embed_faces)")
    parser.add_argument("--models-dir",      default="models",
                        help="Directory containing ONNX models (default: models/)")
    parser.add_argument("--arcface",         default=None,
                        help="Path to ArcFace ONNX model (overrides --models-dir selection)")
    parser.add_argument("--max-actors",      type=int, default=20,
                        help="Maximum number of cast members to include (default: 20)")
    parser.add_argument("--images-per-actor",type=int, default=3,
                        help="Profile images to download per actor (default: 3)")
    parser.add_argument("--image-dir",       default=None,
                        help="Where to store downloaded images (default: <output_dir>/images)")
    parser.add_argument("--keep-images",     action="store_true",
                        help="Do not delete downloaded images after embedding")
    args = parser.parse_args()

    # Resolve paths
    embed_bin  = str(Path(args.embed_bin).resolve())
    models_dir = Path(args.models_dir)
    detector   = str(models_dir / "scrfd_500m_bnkps.onnx")
    arcface    = args.arcface if args.arcface else str(models_dir / "arcface_w600k_r50.onnx")
    output     = Path(args.output)
    image_root = Path(args.image_dir) if args.image_dir else output.parent / "images"

    # Validate
    if not Path(embed_bin).is_file():
        sys.exit(f"embed_faces binary not found: {embed_bin}\n"
                 f"Build it first: cmake --build build --target embed_faces")
    for model, name in [(detector, "SCRFD"), (arcface, "ArcFace")]:
        if not Path(model).is_file():
            sys.exit(f"{name} model not found: {model}\n"
                     f"Run: bash scripts/download_models.sh")

    # Resolve movie ID
    movie_id = args.movie_id
    if movie_id is None:
        print(f"Resolving IMDB ID {args.imdb_id} → TMDB…", file=sys.stderr)
        movie_id = tmdb_id_from_imdb(args.imdb_id, args.tmdb_key)
        print(f"TMDB movie ID: {movie_id}", file=sys.stderr)

    # Build gallery
    gallery = build_gallery(
        movie_id      = movie_id,
        key           = args.tmdb_key,
        embed_bin     = embed_bin,
        detector      = detector,
        arcface       = arcface,
        max_actors    = args.max_actors,
        images_per_actor = args.images_per_actor,
        image_root    = image_root,
    )

    n_actors     = len(gallery["actors"])
    n_embeddings = sum(len(a["embeddings"]) for a in gallery["actors"])
    print(f"\nGallery: {n_actors} actors, {n_embeddings} total embeddings",
          file=sys.stderr)

    if n_actors == 0:
        sys.exit("No actors could be processed — check models and images.")

    output.parent.mkdir(parents=True, exist_ok=True)
    output.write_text(json.dumps(gallery, indent=2) + "\n")
    print(f"Saved: {output}", file=sys.stderr)


if __name__ == "__main__":
    main()