# Image Synthesis Image synthesis is the base feature of DiffSynth Studio. We can generate images with very high resolution. ### Example: FLUX Example script: [`flux_text_to_image.py`](./flux_text_to_image.py) The original version of FLUX doesn't support classifier-free guidance; however, we believe that this guidance mechanism is an important feature for synthesizing beautiful images. You can enable it using the parameter `cfg_scale`, and the extra guidance scale introduced by FLUX is `embedded_guidance`. |1024*1024 (original)|1024*1024 (classifier-free guidance)|2048*2048 (highres-fix)| |-|-|-| |![image_1024](https://github.com/user-attachments/assets/ce01327f-068f-45f5-aba9-0fa45eb26199)|![image_1024_cfg](https://github.com/user-attachments/assets/6af5b106-0673-4e58-9213-cd9157eef4c0)|![image_2048_highres](https://github.com/user-attachments/assets/a4bb776f-d9f0-4450-968c-c5d090a3ab4c)| ### Example: Stable Diffusion Example script: [`sd_text_to_image.py`](./sd_text_to_image.py) LoRA Training: [`../train/stable_diffusion/`](../train/stable_diffusion/) |512*512|1024*1024|2048*2048|4096*4096| |-|-|-|-| |![512](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/55f679e9-7445-4605-9315-302e93d11370)|![1024](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/6fc84611-8da6-4a1f-8fee-9a34eba3b4a5)|![2048](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/9087a73c-9164-4c58-b2a0-effc694143fb)|![4096](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/edee9e71-fc39-4d1c-9ca9-fa52002c67ac)| ### Example: Stable Diffusion XL Example script: [`sdxl_text_to_image.py`](./sdxl_text_to_image.py) LoRA Training: [`../train/stable_diffusion_xl/`](../train/stable_diffusion_xl/) |1024*1024|2048*2048| |-|-| |![1024](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/67687748-e738-438c-aee5-96096f09ac90)|![2048](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/584186bc-9855-4140-878e-99541f9a757f)| ### Example: Stable Diffusion 3 Example script: [`sd3_text_to_image.py`](./sd3_text_to_image.py) LoRA Training: [`../train/stable_diffusion_3/`](../train/stable_diffusion_3/) |1024*1024|2048*2048| |-|-| |![image_1024](https://github.com/modelscope/DiffSynth-Studio/assets/35051019/4df346db-6f91-420a-b4c1-26e205376098)|![image_2048](https://github.com/modelscope/DiffSynth-Studio/assets/35051019/1386c802-e580-4101-939d-f1596802df9d)| ### Example: Kolors Example script: [`kolors_text_to_image.py`](./kolors_text_to_image.py) LoRA Training: [`../train/kolors/`](../train/kolors/) |1024*1024|2048*2048| |-|-| |![image_1024](https://github.com/modelscope/DiffSynth-Studio/assets/35051019/53ef6f41-da11-4701-8665-9f64392607bf)|![image_2048](https://github.com/modelscope/DiffSynth-Studio/assets/35051019/66bb7a75-fe31-44e5-90eb-d3140ee4686d)| Kolors also support the models trained for SD-XL. For example, ControlNets and LoRAs. See [`kolors_with_sdxl_models.py`](./kolors_with_sdxl_models.py) LoRA: https://civitai.com/models/73305/zyd232s-ink-style |Base model|with LoRA (alpha=0.5)|with LoRA (alpha=1.0)|with LoRA (alpha=1.5)| |-|-|-|-| |![image_0 0](https://github.com/user-attachments/assets/a222eae3-6e0a-4ea6-b301-99e74e2bc11a)|![image_0 5](https://github.com/user-attachments/assets/e429c501-530c-43f6-a30b-9f97996c91a2)|![image_1 0](https://github.com/user-attachments/assets/0ddeed4b-250d-4b5c-a4fa-2db50f63bf1c)|![image_1 5](https://github.com/user-attachments/assets/db35a89d-6325-4422-921e-14fb6ad66c92)| ControlNet: https://huggingface.co/xinsir/controlnet-union-sdxl-1.0 |Reference image|Depth image|with ControlNet|with ControlNet| |-|-|-|-| |![image_0 0](https://github.com/user-attachments/assets/a222eae3-6e0a-4ea6-b301-99e74e2bc11a)|![controlnet_input](https://github.com/user-attachments/assets/d16b2785-bc1f-4184-b170-ae90f1d704c1)|![image_depth_1](https://github.com/user-attachments/assets/90a94780-7b56-4786-8a25-aae118eda171)|![image_depth_2](https://github.com/user-attachments/assets/05eb1309-9c98-49e7-a8ee-f376ceedf18e)| ### Example: Hunyuan-DiT Example script: [`hunyuan_dit_text_to_image.py`](./hunyuan_dit_text_to_image.py) LoRA Training: [`../train/hunyuan_dit/`](../train/hunyuan_dit/) |1024*1024|2048*2048| |-|-| |![image_1024](https://github.com/modelscope/DiffSynth-Studio/assets/35051019/60b022c8-df3f-4541-95ab-bf39f2fa8bb5)|![image_2048](https://github.com/modelscope/DiffSynth-Studio/assets/35051019/87919ea8-d428-4963-8257-da05f3901bbb)| ### Example: Stable Diffusion XL Turbo Example script: [`sdxl_turbo.py`](./sdxl_turbo.py) We highly recommend you to use this model in the WebUI. |"black car"|"red car"| |-|-| |![black_car](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/7fbfd803-68d4-44f3-8713-8c925fec47d0)|![black_car_to_red_car](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/aaf886e4-c33c-4fd8-98e2-29eef117ba00)| ### Example: Prompt Processing If you are not native English user, we provide translation service for you. Our prompter can translate other language to English and refine it using "BeautifulPrompt" models. Please see [`sd_prompt_refining.py`](./sd_prompt_refining.py) for more details. Prompt: "一个漂亮的女孩". The [translation model](https://huggingface.co/Helsinki-NLP/opus-mt-en-zh) will translate it to English. |seed=0|seed=1|seed=2|seed=3| |-|-|-|-| |![0_](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/ebb25ca8-7ce1-4d9e-8081-59a867c70c4d)|![1_](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/a7e79853-3c1a-471a-9c58-c209ec4b76dd)|![2_](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/a292b959-a121-481f-b79c-61cc3346f810)|![3_](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/1c19b54e-5a6f-4d48-960b-a7b2b149bb4c)| Prompt: "一个漂亮的女孩". The [translation model](https://huggingface.co/Helsinki-NLP/opus-mt-en-zh) will translate it to English. Then the [refining model](https://huggingface.co/alibaba-pai/pai-bloom-1b1-text2prompt-sd) will refine the translated prompt for better visual quality. |seed=0|seed=1|seed=2|seed=3| |-|-|-|-| |![0](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/778b1bd9-44e0-46ac-a99c-712b3fc9aaa4)|![1](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/c03479b8-2082-4c6e-8e1c-3582b98686f6)|![2](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/edb33d21-3288-4a55-96ca-a4bfe1b50b00)|![3](https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/7848cfc1-cad5-4848-8373-41d24e98e584)|