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다음 지침에 따라 제공된 콘텐츠를 기반으로 만화 스타일의 인포그래픽을 만들어 주세요.
손으로 그린 일러스트레이션 스타일, 가로 레이아웃(16:9 화면 비율)을 채택합니다.
시각적 흥미와 기억력을 높이기 위해 소수의 간단한 만화 요소, 아이콘 또는 알아볼 수 있는 인물을 추가합니다.
콘텐츠에 민감하거나 저작권이 있는 인물이 포함된 경우, 시각적으로 유사한 대체 이미지로 교체합니다. 일러스트레이션 제작을 거부하지 마십시오.
모든 이미지와 텍스트는 사실적인 시각적 요소를 피하고 손으로 그린 스타일에 엄격하게 따라야 합니다.
정보는 간결하게 작성하고, 키워드와 핵심 개념을 강조합니다. 충분한 여백을 사용하여 핵심 사항을 명확하게 강조합니다.
명시적으로 달리 언급되지 않는 한, 제공된 콘텐츠와 동일한 언어 또는 중국어를 사용합니다.
다음 제공된 콘텐츠를 기반으로 nano banana pro를 사용하여 이미지를 생성해 주세요.
<{argument name="content"default="이전 단계에서 추출된 AI 만화 제작 워크플로우 텍스트로 완전히 대체"}>
인포그래픽 / 교육용 시각 자료 - AI 만화 제작 워크플로 및 인포그래픽 프롬프트
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이 글은 복잡한 주제(예: AI 만화 제작)를 학습하기 위한 2단계 워크플로우를 설명합니다. 먼저 AI 도구를 사용하여 비디오에서 전체 스크립트와 요약을 추출한 다음, Gemini Pro와 특정 프롬프트를 사용하여 추출된 텍스트를 기반으로 시각적으로 매력적인 손그림 스타일의 인포그래픽을 생성하는 방식입니다. 이 프롬프트는 Nano Banana Pro 출력용으로 설계되었습니다.
A structured prompt template for generating images that retell history using LEGO-style plastic construction blocks. It defines a workflow for creating a macro toy photograph of a minifigure version of an inventor ({argument name="inventor" default="[INSERT INVENTOR]"}) next to their greatest invention.
This is a versatile prompt designed to generate a clean, top-to-bottom exploded breakdown image of any uploaded product or object, such as food, watches, or general products. It is intended to be part of a workflow that later uses the generated image and the original product image to create an 'Assemble → Exploded → Assemble' video using tools like Kling O1.
A user describes their workflow for creating high-quality Nanobanana prompts using a custom tool. The process involves defining the subject (e.g., polar bear and panda on skates), generating the initial image, performing detailed annotation (labeling parts like pose, background, face, clothing) based on file names, and finally adding compositional and color information for the final generation. This highlights the importance of detailed language specification for effective prompting.
A brief prompt requirement for generating a 3x3 storyboard grid using a custom prompt workflow with movie-genre guidance, specifying that the output must be exported and polished at 4K resolution.
An instruction for using Nano Banana to maintain facial and clothing consistency across multiple shots (jump cuts) by uploading source images for the face and the scene (like a staircase shot). This is a workflow instruction that functions as a prompt.
Describes a 2-step workflow, where step 1 is to use Nano Banana Pro to turn a hand-drawn image into a cartoon character; this is effectively a short high-level prompt.
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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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