Workflow
可灵 2.1 首尾帧藏师傅外挂教程:两张图→大片,附万能提示词
歸藏的AI工具箱·2025-08-22 09:10

Core Viewpoint - The article emphasizes the capabilities of the Keling 2.1 model in generating first and last frame videos, particularly focusing on image generation and prompt creation, which are crucial for producing high-quality content [1][7]. Summary by Sections Image Acquisition Methods - Three primary methods for obtaining suitable images for first and last frame video generation are discussed: same prompt card drawing, modified prompt card drawing, and using image editing models like FLUX Kontext [8]. - Using the same prompt for card drawing often yields highly similar images, making it ideal for showcase-type videos [9]. - Modifying prompt card drawing allows for the movement or disappearance of main characters or objects by changing parts of the prompt after generating the initial image [12]. - Image editing models enable precise control over images through natural language, allowing for various effects to be added [15]. Prompt Generation for First and Last Frame Videos - The prompts used for generating first and last frame videos are entirely AI-generated, leveraging the enhanced understanding and adherence capabilities of the Keling 2.1 model [27]. - A structured approach to prompt creation is outlined, focusing on analyzing differences between the starting and ending frames and selecting appropriate transition strategies [28][29]. - The article details how to construct specific changes in the visuals, including object transformations, environmental changes, and stylistic variations [37]. Value Creation and Narrative Enhancement - The article suggests that the true value lies in solidifying the process into a template for future projects, enhancing productivity significantly [39]. - It emphasizes the importance of elevating effects into narratives, transforming the approach from mere visual transitions to storytelling, which can significantly increase the perceived value of the videos produced [41].