社交媒体帖子 - Edge-Aware ASCII Art Conversion
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Original author textThis public page preserves the author's original prompt. Review the preview and any published evaluation, then copy the text or open it as a draft. Choose the model, references and current cost in the creation workspace before generating.
Apply an ASCII-art rendering effect to the reference image, where the ASCII character density and placement is driven by the underlying tonal contrast and edges of the photo, like a true edge-aware ASCII-art conversion. Dense character clusters follow the natural contours, silhouette lines, and high-detail areas (such as hair strands, fabric folds, and background structure), while flatter, low-contrast areas (such as smooth skin) stay comparatively clean with minimal or no texture. The effect should look like the ASCII characters are tracing the actual shapes and edges present in the photo, not a uniform overlay pasted on top of everything equally. Use a {argument name="terminal color" default="classic green-on-black"} or grayscale terminal character set (@ # % & * + . :), medium overall density, with the original photo still legible underneath.
Adjust the model, settings and references before generating.
Use prompt →Prefill first, then confirm generation and the current cost.
GPT evaluation
GPT-6.1-sol
AI evaluation for creative referenceModel: GPT-6.1-sol Overall score: 7.9 / 10 Prompt quality: 8.7 / 10 Image quality: 8.4 / 10 Prompt–image alignment: 6.7 / 10 示例图具备较强的时尚人像视觉冲击力,但ASCII效果偏稀疏描边而非中等密度的边缘感知转换,建议强化字符层级与细节覆盖后上线。
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