Musica, vecchietti con sprite, nuove scene del paese e generatore degli sfondi
Lavoro della sessione precedente: colonna sonora (titolo, paese, ricordi) con muto e volume, vecchietta e vecchietto sulla panchina, scene di Pieve, oratorio, Via de' Medici, Villa Adami, salita, campeggio, Bosco ai Frati e viale dei cipressi, panorama dell'introduzione, tools/genera.py per gli sfondi dalle foto. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01UdeKd62opy9PKgpQXtVctF
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Claude Opus 5.5
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#!/usr/bin/env python3
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"""Trasforma le foto del gioco con Images Edit; --dry-run non usa rete né scrive file."""
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from __future__ import annotations
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import argparse
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import base64
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import hashlib
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import html
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import io
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import json
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import os
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from pathlib import Path
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import sys
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import tempfile
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import time
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from datetime import datetime, timezone
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from urllib.parse import quote
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ROOT = Path(__file__).resolve().parents[1]
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EXTENSIONS = {'.jpg', '.jpeg', '.png', '.webp'}
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SIZE = (1536, 864)
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DEFAULT_PROMPT = """Use case: style-transfer.
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Create a clean background for La Leggenda del Regolo, a point-and-click adventure
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set in San Piero a Sieve, Mugello, Tuscany, in late May 2007.
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The input photograph is the architectural and composition reference.
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Transform it into early-1990s (1993) VGA adventure pixel art: carefully placed
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pixel clusters, limited warm palette of about 64 colors, crisp edges, no blur,
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no smooth gradients, no photographic texture, no anti-aliasing.
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Preserve the actual architecture, perspective, relative building positions,
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historic details, openings, road layout and ground slope. Do not mirror the view.
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Warm late-May afternoon light, consistent across the game's outdoor scenes.
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Output one opaque 1536x864 image, 16:9, full bleed, no frame or letterboxing.
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For a non-16:9 source, extend the framing conservatively without stretching
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buildings or cropping essential architecture. Do not invent landmarks.
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Keep existing foreground ground readable for walking without flattening slopes
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or moving roads. Remove people and vehicles to leave an empty background; game
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characters will be rendered separately. Remove readable lettering from signs.
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No new characters, animals, text, logos, UI, inventory, cursor or watermark.
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"""
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def positive(value):
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number = int(value)
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if number <= 0:
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raise argparse.ArgumentTypeError('deve essere maggiore di zero')
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return number
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def atomic_write(path, data):
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path.parent.mkdir(parents=True, exist_ok=True)
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with tempfile.NamedTemporaryFile(dir=path.parent, delete=False) as stream:
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temporary = Path(stream.name)
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stream.write(data)
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try:
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temporary.replace(path)
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finally:
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temporary.unlink(missing_ok=True)
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def save_log(path, records):
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atomic_write(path, (json.dumps(records, indent=2, ensure_ascii=False) + '\n').encode())
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def read_log(path):
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if not path.exists():
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return {}
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records = json.loads(path.read_text(encoding='utf-8'))
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if not isinstance(records, dict):
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raise ValueError(f'Registro non valido: {path}')
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return records
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def photos_in(folder):
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if not folder.is_dir():
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raise ValueError(f'Cartella originali non trovata: {folder}')
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photos = sorted((p for p in folder.iterdir() if p.is_file() and
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p.suffix.lower() in EXTENSIONS), key=lambda p: p.name.casefold())
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names = set()
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for photo in photos:
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key = photo.stem.casefold()
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if key in names:
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raise ValueError(f'Nome duplicato: {photo.stem}. Rinominare le foto con lo stesso nome base.')
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names.add(key)
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return photos
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def prompt_for(photo, folder):
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common = folder / 'base.txt'
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custom = folder / f'{photo.stem}.txt'
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text = common.read_text(encoding='utf-8') if common.exists() else DEFAULT_PROMPT
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if custom.exists():
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text += '\n\nSCENE-SPECIFIC INSTRUCTIONS:\n' + custom.read_text(encoding='utf-8')
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if not text.strip() or len(text) > 32000:
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raise ValueError(f'Prompt vuoto o troppo lungo per {photo.name}')
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return text
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def validate_image(path, expected_size=None):
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from PIL import Image
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with Image.open(path) as image:
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image.load()
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if expected_size and (image.size != expected_size or image.format != 'PNG'):
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raise ValueError(f'PNG {expected_size[0]}x{expected_size[1]} atteso: {path}')
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def normalize_response(raw, destination):
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from PIL import Image
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with Image.open(raw) as image:
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image.load()
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if abs(image.width / image.height - 16 / 9) > 0.02:
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raise ValueError('Risposta non 16:9: conservata in .responses; serve revisione, nessun ritaglio automatico.')
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image = image.convert('RGB')
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if image.size != SIZE:
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image = image.resize(SIZE, Image.Resampling.NEAREST)
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data = io.BytesIO()
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image.save(data, format='PNG')
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atomic_write(destination, data.getvalue())
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def gallery(photos, output, records):
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def link(path):
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return html.escape(quote(os.path.relpath(path, output), safe='/'), quote=True)
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cards = []
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for photo in photos:
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result = output / f'{photo.stem}.png'
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state = records.get(photo.name, {}).get('status', 'da generare')
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if result.exists() and state != 'completed':
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state = 'file presente (verificare)'
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after = (f'<img loading="lazy" src="{link(result)}" alt="{html.escape(photo.stem)} — risultato">'
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if result.exists() else '<p class="pending">Non ancora generata</p>')
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cards.append(f'<section><h2>{html.escape(photo.stem)}</h2><p>{html.escape(state)}</p>'
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f'<div class="pair"><figure><img loading="lazy" src="{link(photo)}" '
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f'alt="{html.escape(photo.stem)} — originale"><figcaption>Fotografia originale</figcaption>'
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f'</figure><figure>{after}<figcaption>Pixel art · 1536×864</figcaption></figure></div></section>')
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page = '''<!doctype html><html lang="it"><meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<title>La Leggenda del Regolo — confronto sfondi</title>
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<style>body{font:16px system-ui;background:#182027;color:#f6ebd8;margin:2rem auto;padding:0 1rem;max-width:1400px}
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.pair{display:grid;grid-template-columns:1fr 1fr;gap:1rem}figure{margin:0;background:#26323b;padding:1rem}
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img{width:100%;height:360px;object-fit:contain}figure+figure img{image-rendering:pixelated}
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figcaption{padding-top:.5rem}.pending{height:328px;display:grid;place-items:center}
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section{margin:2rem 0}a{color:#f4c47f}@media(max-width:700px){.pair{grid-template-columns:1fr}img{height:auto}}</style>
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<h1>La Leggenda del Regolo — sfondi dalle fotografie</h1>
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<p>San Piero a Sieve · originali e risultati. Le immagini mancanti sono indicate senza anteprime simulate.</p>
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''' + '\n'.join(cards) + '</html>\n'
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atomic_write(output / 'index.html', page.encode())
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def run(args):
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photos = photos_in(args.input_dir)
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if args.input_dir.resolve() == args.output_dir.resolve():
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raise ValueError('Originali e risultati devono avere cartelle diverse.')
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log_path = args.output_dir / 'registro.json'
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records = read_log(log_path)
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if args.gallery_only:
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gallery(photos, args.output_dir, records)
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print(f'Confronto: {args.output_dir / "index.html"}')
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return 0
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pending = [p for p in photos if not (args.output_dir / f'{p.stem}.png').exists()]
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limit = 1 if args.test else args.limit
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selected = pending[:limit] if limit else pending
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prompts = {p.name: prompt_for(p, args.prompt_dir) for p in selected}
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cached = {p.name for p in selected if (args.output_dir / '.responses' / f'{p.stem}.png').exists()}
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api_count = len(selected) - len(cached)
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print(f'Foto trovate: {len(photos)}; PNG già presenti: {len(photos) - len(pending)}')
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print(f'Da elaborare: {len(selected)}; da cache: {len(cached)}; immagini da inviare all’API: {api_count}')
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print(f'Modello: {args.model}; formato: 1536x864; qualità: {args.quality}')
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for photo in selected:
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print(f' {photo.name} -> {args.output_dir / (photo.stem + ".png")} '
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f'[{"cache locale" if photo.name in cached else "Images Edit"}]')
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if args.dry_run:
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print('DRY RUN: nessuna chiamata API e nessun file scritto.')
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return 0
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# Validate all existing results and selected sources before any paid request.
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for photo in photos:
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result = args.output_dir / f'{photo.stem}.png'
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if result.exists():
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validate_image(result, SIZE)
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for photo in selected:
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validate_image(photo)
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client = None
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if api_count:
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if not os.environ.get('OPENAI_API_KEY'):
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raise ValueError('Imposta OPENAI_API_KEY nell’ambiente. Non inserirla nel codice o nei prompt.')
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try:
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import openai
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except ImportError as exc:
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raise ValueError('Installa le dipendenze: python3 -m pip install -r requirements.txt') from exc
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print(f'Possibili costi: {api_count} immagini, fino a {api_count * args.attempts} richieste con i retry.')
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print('Un timeout può avvenire dopo l’elaborazione: un retry potrebbe comportare un altro addebito.')
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try:
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answer = input('Per procedere scrivi GENERA: ')
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except EOFError:
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answer = ''
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if answer.strip() != 'GENERA':
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print('Annullato: nessuna chiamata API.')
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return 0
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client = openai.OpenAI(timeout=args.timeout, max_retries=0)
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failures = 0
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try:
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for photo in selected:
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target = args.output_dir / f'{photo.stem}.png'
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raw = args.output_dir / '.responses' / f'{photo.stem}.png'
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previous = records.get(photo.name, {})
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record = dict(previous) if raw.exists() else {
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'source': str(photo.resolve()), 'output': str(target.resolve()),
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'source_sha256': hashlib.sha256(photo.read_bytes()).hexdigest(),
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'prompt': prompts[photo.name], 'model': args.model,
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'size': '1536x864', 'quality': args.quality, 'attempts': 0,
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}
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records[photo.name] = record
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try:
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if not raw.exists():
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for attempt in range(args.attempts):
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record.update(status='processing', attempts=record['attempts'] + 1,
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updated_at=datetime.now(timezone.utc).isoformat())
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save_log(log_path, records)
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try:
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from PIL import Image, ImageOps
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# Honor EXIF rotation and supply PNG regardless of source format.
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with Image.open(photo) as source:
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upload = io.BytesIO()
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ImageOps.exif_transpose(source).convert('RGB').save(upload, format='PNG')
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if upload.tell() >= 50 * 1024 * 1024:
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raise ValueError('Immagine convertita oltre il limite di 50 MB.')
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response = client.images.edit(
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model=args.model, image=(photo.stem + '.png', upload.getvalue(), 'image/png'),
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prompt=prompts[photo.name], size='1536x864', quality=args.quality,
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output_format='png', n=1,
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)
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if not response.data or not response.data[0].b64_json:
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raise ValueError('Risposta senza immagine base64.')
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# Persist before post-processing, so local errors never require regeneration.
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atomic_write(raw, base64.b64decode(response.data[0].b64_json, validate=True))
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record['request_id'] = getattr(response, '_request_id', None)
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usage = getattr(response, 'usage', None)
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if usage is not None:
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record['usage'] = usage.model_dump(mode='json')
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break
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except (openai.APIConnectionError, openai.APIStatusError) as exc:
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status = getattr(exc, 'status_code', None)
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transient = status is None or status in (408, 409, 429) or status >= 500
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record['last_api_error'] = {'type': type(exc).__name__, 'status_code': status}
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save_log(log_path, records)
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if not transient or attempt + 1 == args.attempts:
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raise
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delay = min(2 ** (attempt + 1), 60)
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print(f' {photo.name}: {type(exc).__name__}, nuovo tentativo tra {delay}s.')
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time.sleep(delay)
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normalize_response(raw, target)
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record.update(status='completed', updated_at=datetime.now(timezone.utc).isoformat())
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record.pop('error', None)
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print(f' Completata: {target}')
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except Exception as exc:
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failures += 1
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# Do not log SDK exception bodies, headers, credentials or base64 payloads.
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message = str(exc) if isinstance(exc, (ValueError, OSError)) else type(exc).__name__
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record.update(status='error', error=message, updated_at=datetime.now(timezone.utc).isoformat())
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print(f' Errore {photo.name}: {message}', file=sys.stderr)
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finally:
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save_log(log_path, records)
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gallery(photos, args.output_dir, records)
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gallery(photos, args.output_dir, records)
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finally:
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if client is not None:
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client.close()
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return 1 if failures else 0
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def main(argv=None):
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument('--input-dir', type=Path, default=ROOT / 'assets/raw/foto')
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parser.add_argument('--output-dir', type=Path, default=ROOT / 'assets/generated')
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parser.add_argument('--prompt-dir', type=Path, default=ROOT / 'prompts/backgrounds')
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parser.add_argument('--model', default='gpt-image-2')
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parser.add_argument('--quality', choices=['low', 'medium', 'high', 'auto'], default='high')
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parser.add_argument('--timeout', type=positive, default=180)
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parser.add_argument('--attempts', type=positive, default=3, help='numero massimo di richieste per foto')
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limit = parser.add_mutually_exclusive_group()
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limit.add_argument('--test', action='store_true', help='prima foto non ancora completata')
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limit.add_argument('--limit', type=positive)
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mode = parser.add_mutually_exclusive_group()
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mode.add_argument('--dry-run', action='store_true')
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mode.add_argument('--gallery-only', action='store_true', help='scrive solo il confronto HTML, senza API')
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args = parser.parse_args(argv)
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try:
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return run(args)
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except (ValueError, OSError, ImportError) as exc:
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print(f'Errore: {exc}', file=sys.stderr)
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return 1
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except KeyboardInterrupt:
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print('\nInterrotto. I risultati già salvati verranno riutilizzati.', file=sys.stderr)
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return 130
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if __name__ == '__main__':
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sys.exit(main())
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