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This invention discloses a method for generating crystal image samples based on a diffusion model, comprising: generating a standard comparison image based on a reaction flask photograph; obtaining crystal identification features based on the shape and color of the crystal; detecting the presence of the crystal by using the crystal identification features and the standard comparison image; and generating a crystal image based on the crystal presence result. The crystal image generation is performed using a diffusion model. This invention, through an AI method based on a diffusion model, can generate crystal growth images under different conditions within seconds, without requiring long waiting times for experimental results or physical experiments. It can generate high-quality crystal growth samples, suitable for materials research and educational visualization. The shape, color, transparency, and other parameters of the crystal can be adjusted to match experimental data of specific chemical systems. It utilizes AI to generate large-scale, high-quality crystal growth image datasets, assisting the application of deep learning in materials science.