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Créez une image infographique de [{argument name="body part"default="Œil"}], combinant une photographie réaliste ou un rendu photoréaliste de l'objet avec des superpositions d'annotations techniques placées directement dessus.
Utilisez des dessins au trait et du texte de style encre noire (stylo technique / croquis architectural) sur un fond de studio d'un blanc pur, incluant :
• Des étiquettes de composants clés
• Des contours en coupe ou en vue éclatée
• Des mesures, des dimensions et des marqueurs d'échelle
• Des indications de matériaux et de quantités
• Des flèches indiquant la fonction, la force ou le flux (air, son, puissance, pression)
• Des schémas simples ou des diagrammes en coupe le cas échéant
Placez le titre [PARTIEDUCORPS] à l'intérieur d'une boîte d'annotation technique dessinée à la main dans un coin.
Règles de style et de mise en page :
• L'objet réel reste clairement visible sous les annotations
• Les annotations donnent l'impression d'être esquissées, techniques et architecturales
• Composition nette avec un espace négatif équilibré
• Ambiance éducative, d'exposition de musée / de manuel d'ingénierie
Style visuel :
Esthétique d'illustration technique minimale, lignes noires sur imagerie réaliste, sensation précise mais légèrement dessinée à la main.
Palette de couleurs :
Fond blanc, lignes d'annotation noires et texte uniquement. Pas de couleurs.
Sortie :
1080×1080, ultra-nette, optimisée pour les réseaux sociaux, sans filigrane.
Infographie / Visuel éducatif - Modèle d'invite d'infographie pour les parties du corps
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Un modèle d'invite réutilisable pour Nano Banana Pro, conçu pour créer une image infographique d'une partie du corps spécifique (par défaut, « Œil »). L'invite demande à l'IA de combiner un rendu photoréaliste de l'objet avec des superpositions d'annotations techniques, en utilisant des dessins au trait à l'encre noire, des étiquettes, des mesures et des schémas sur un fond blanc pur, visant une esthétique de manuel d'ingénierie éducatif.
A detailed Japanese prompt for Nano Banana Pro to transform a reference character into a chibi-style robot and generate a technical illustration/infographic. The image features a cutaway view showing the character's clothing and the internal mechanical structure simultaneously, complete with English annotations for the parts.
A prompt for generating a colorful, minimalist exploded view diagram of a modern ergonomic chair. It specifies the style (industrial design, flat yet 3D), composition (vertically separated components), and requires clear labeling of all parts (headrest, casters, etc.) using a clean sans-serif font. This is useful for educational content or product marketing diagrams.
This prompt set is for generating ultra-realistic food photography, including a motion prompt for video generation (Kling AI) and two image prompts: one for a standard, high-detail pizza slice, and another for an exploded infographic view of the pizza layers.
A highly detailed, multi-part prompt designed to generate a technical infographic for an e-commerce product, combining a realistic photograph of the object with hand-sketched, architectural-style annotations, measurements, and schematic diagrams on a pure white background. The example object is a Tudor North Flag watch.
A complex, multi-part prompt designed to generate a technical infographic or blueprint of a product, combining a photorealistic image with dense, engineering-style annotations, labels, measurements, and structural callouts, all strictly in English, against a pure white background.
A detailed multi-part prompt for generating two distinct images and a motion sequence related to a taco. The first image is a high-end commercial photograph of the taco, and the second is a hyper-realistic exploded-view infographic of its ingredients with specific annotation design requirements. The motion prompt describes a smooth separation of ingredients for video generation.
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Data collected and processed: IP addresses, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data
Data collected and processed: IP addresses, Device characteristics, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Authentication-derived identifiers, Browsing and interaction data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Authentication-derived identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Non-precise location data, Precise location data
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Authentication-derived identifiers, Browsing and interaction data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
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