Lora and Workflow Usage:
1. This is a **High_Noise** model. It should only be used in the high-noise channel, not the low-noise channel.
2. A Lora weight of **1.0** is recommended.
3. The sampler's `boundary` is set to 0.9. This is the signal-to-noise ratio for the MOE sampler in I2V cases, so you don't need to change it. For the sampler and scheduler, I recommend `uni_pc+beta` or `res_2s+bong_tangent`.
4. **A local decoding module is provided.** Go to https://github.com/liangtongt/TT-tools and download `TT_lmg_Loc.exe` to any folder on your computer. Download the grayscale image from the online workflow and save it to the same folder. Then, just drag the grayscale image and drop it onto the `TT_lmg_Loc.exe` file to decode it. You'll get the video that was generated online, and the locally decoded version won't have a watermark.
Prompt Structure:
ymq,[Shot type, Composition],surround camera movement, the camera circles 360° from the front to the back of the subject,[Description of the main appearance],[The environmental description of the subject in the image],The camera pans from her front to her back,[Transform scene description],[Image tone and atmosphere description]
Prompt Example:
ymq, medium shot, central composition, surround camera movement, the camera circles 360° from the front to the back of the subject, showing a classical woman with her hair coiled into a bun and a graceful figure. She is wearing a light cyan halter-neck tight dress with ink-wash bamboo patterns. She stands still on a stone bridge. The camera pans from her front to her back, surrounded by stone Bridges and buildings from the water towns of Jiangnan. The tone of the picture is cold and clear, presenting a hazy and poetic atmosphere of the misty rain in Jiangnan
It's important to note that for the `[Transform scene description]` part of the prompt, the description should be related to the original background but not exactly the same. Otherwise, wan2.2 might just turn the character around from front to back instead of creating an orbiting camera shot. For example, if the original character is standing in a Chinese-style courtyard with flowers and trees, the transformed scene could be described as "surrounded by gardens and Chinese architecture." By facing different scenes, the wan2.2 model can smoothly switch the environment, which is what achieves the orbiting camera effect from the character's front to their back.
Lora and Workflow Usage:
1. This is a **High_Noise** model. It should only be used in the high-noise channel, not the low-noise channel.
2. A Lora weight of **1.0** is recommended.
3. The sampler's `boundary` is set to 0.9. This is the signal-to-noise ratio for the MOE sampler in I2V cases, so you don't need to change it. For the sampler and scheduler, I recommend `uni_pc+beta` or `res_2s+bong_tangent`.
4. **A local decoding module is provided.** Go to https://github.com/liangtongt/TT-tools and download `TT_lmg_Loc.exe` to any folder on your computer. Download the grayscale image from the online workflow and save it to the same folder. Then, just drag the grayscale image and drop it onto the `TT_lmg_Loc.exe` file to decode it. You'll get the video that was generated online, and the locally decoded version won't have a watermark.
Prompt Structure:
ymq,[Shot type, Composition],surround camera movement, the camera circles 360° from the front to the back of the subject,[Description of the main appearance],[The environmental description of the subject in the image],The camera pans from her front to her back,[Transform scene description],[Image tone and atmosphere description]
Prompt Example:
ymq, medium shot, central composition, surround camera movement, the camera circles 360° from the front to the back of the subject, showing a classical woman with her hair coiled into a bun and a graceful figure. She is wearing a light cyan halter-neck tight dress with ink-wash bamboo patterns. She stands still on a stone bridge. The camera pans from her front to her back, surrounded by stone Bridges and buildings from the water towns of Jiangnan. The tone of the picture is cold and clear, presenting a hazy and poetic atmosphere of the misty rain in Jiangnan
It's important to note that for the `[Transform scene description]` part of the prompt, the description should be related to the original background but not exactly the same. Otherwise, wan2.2 might just turn the character around from front to back instead of creating an orbiting camera shot. For example, if the original character is standing in a Chinese-style courtyard with flowers and trees, the transformed scene could be described as "surrounded by gardens and Chinese architecture." By facing different scenes, the wan2.2 model can smoothly switch the environment, which is what achieves the orbiting camera effect from the character's front to their back.