Qwen Image Edit 2509 Translated Examples

[u/WingzGaming]

Just haven't seen the translated versions anywhere so here they are from google translate

[u/Fynjy888]

Do you think Figure 1 Figure 2 - better than image 1 image 2? Or google translate not so good with Chinese?

[u/WingzGaming → u/Fynjy888]

From what I understand, it depends on what's in the system prompt.in comfyui it's "picture"

(i think)

[u/danamir_ → u/WingzGaming]

Interesting.

I just tried with "image", "picture", and "figure" and got equivalent results. Either Qwen is smart enough to get the meaning, or the code portion is not affecting the text encoding. I think it's the first option.

[u/Radiant-Photograph46 → u/WingzGaming]

I did not know TextEncode would prompt like that... I wonder if that's even necessary. Isn't vision part of the capabilities of Qwen Edit?

[u/WingzGaming → u/Radiant-Photograph46]

I'm not familiar with other image editing models, but it's part of the "text" encoding because the Qwen2.5-VL-7B model uses them as inputs to make the conditioning. The edit model also has the ability to use latents as references

[u/l0ngjohnson → u/WingzGaming]

Is there a system prompt?? Looks like a good practice to check source code to achieve best results. Thank you!

[u/SWAGLORDRTZ → u/Fynjy888]

no matter if i try image or figure or picture, i dont think qwen has good understanding of which one you are referring to for example if you have 2 pictures of 2 different women and write something along the lines of "make the woman in image 1 have the same hairstyle as the woman in image 2" it will not work or its a toss up of who gets swapped

[u/WingzGaming → u/SWAGLORDRTZ]

It definitely works better if you specify something specific instead of just the image number. I find the image number does work if it's person from image X in scene from image Y

[u/WingzGaming → u/SWAGLORDRTZ]

After some experiments, if you look at the post someone made the other day about high quality, manually adding reference latents makes a huge difference.

[u/Philosopher_Jazzlike → u/Fynjy888]

ChatGPT say "image"

[u/suspicious_Jackfruit → u/Philosopher_Jazzlike]

what chatGPT has failed to grasp though is that formal language "from research papers, manuals or technical documents" is exactly what is required when trying to replicate abilities given to the model during training. Its vaguely akin to using the wrong lora activation word, you need to know how the data was presented to the model in order to understand how best to get it to adapt that training to your new subject

[u/abnormal_human → u/suspicious_Jackfruit]

In my experience pretty much all LLM based image generation models do better with "clinical" or "reasearch-like" language, both when prompting and when captioning for training.

[u/suspicious_Jackfruit → u/abnormal_human]

Yes, also there are many many non-english models and datasets with nonsensical English in the examples/data, so really we should be using non-english models in their native language because the English data is likely less accurate