Single prompt with notes for man and reference count

README.md

@@ -48,38 +48,15 @@ five to nine work best.
 | CFG | 1, no negative prompt |
 | VAE | [Texture-Fix VAE](https://huggingface.co/madebyollin/texture-fix-vae-for-qwen-image-2.1) recommended |
 
-Prompts for the two setups RefRes was trained on. For another count, change only the last image number (*Images 2 to N*) — with one reference that is *Images 2 to 2*, exactly as in our 1-reference tests.
-
 <details>
-<summary>Prompt · woman · 5 references (images 2–6)</summary>
+<summary>Prompt (woman, 5 references)</summary>
 
 ```text
 Restore image 1, a photo of a woman, into a sharp, clear, high-resolution photograph with crisp fine detail. Images 2 to 6 are other photos of the same woman; use them only as identity reference to recover her true facial features and fine details. Keep image 1's pose, expression, framing, clothing, background and colors unchanged. Remove every trace of low resolution and degradation: pixelation, soft or blurry upscaling, blur, all kinds of noise and film grain, JPEG and WebP compression artifacts, color banding, as well as any overlaid text, stickers, emoji or watermarks. The result must look natively high resolution: sharp, clean and detailed, with no grain, no noise and no low-resolution softness.
 ```
-</details>
-
-<details>
-<summary>Prompt · woman · 9 references (images 2–10)</summary>
-
-```text
-Restore image 1, a photo of a woman, into a sharp, clear, high-resolution photograph with crisp fine detail. Images 2 to 10 are other photos of the same woman; use them only as identity reference to recover her true facial features and fine details. Keep image 1's pose, expression, framing, clothing, background and colors unchanged. Remove every trace of low resolution and degradation: pixelation, soft or blurry upscaling, blur, all kinds of noise and film grain, JPEG and WebP compression artifacts, color banding, as well as any overlaid text, stickers, emoji or watermarks. The result must look natively high resolution: sharp, clean and detailed, with no grain, no noise and no low-resolution softness.
-```
-</details>
-
-<details>
-<summary>Prompt · man · 5 references (images 2–6)</summary>
-
-```text
-Restore image 1, a photo of a man, into a sharp, clear, high-resolution photograph with crisp fine detail. Images 2 to 6 are other photos of the same man; use them only as identity reference to recover his true facial features and fine details. Keep image 1's pose, expression, framing, clothing, background and colors unchanged. Remove every trace of low resolution and degradation: pixelation, soft or blurry upscaling, blur, all kinds of noise and film grain, JPEG and WebP compression artifacts, color banding, as well as any overlaid text, stickers, emoji or watermarks. The result must look natively high resolution: sharp, clean and detailed, with no grain, no noise and no low-resolution softness.
-```
-</details>
 
-<details>
-<summary>Prompt · man · 9 references (images 2–10)</summary>
-
-```text
-Restore image 1, a photo of a man, into a sharp, clear, high-resolution photograph with crisp fine detail. Images 2 to 10 are other photos of the same man; use them only as identity reference to recover his true facial features and fine details. Keep image 1's pose, expression, framing, clothing, background and colors unchanged. Remove every trace of low resolution and degradation: pixelation, soft or blurry upscaling, blur, all kinds of noise and film grain, JPEG and WebP compression artifacts, color banding, as well as any overlaid text, stickers, emoji or watermarks. The result must look natively high resolution: sharp, clean and detailed, with no grain, no noise and no low-resolution softness.
-```
+- **For a man:** replace *woman* with *man* and *her* with *his*.
+- **For another number of references:** change only the last image number — *Images 2 to 10* for nine, *Images 2 to 2* for one.
 </details>
 
 ## Choosing the references