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qwen /qwen-edit-multiangle:cf245ffa

Input schema

The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.

Field Type Default value Description
image
string
Image file uploaded to Cog (jpeg, png, gif, or webp).
prompt
string
Optional text instruction appended after the camera directive.
rotate_degrees
integer
0

Min: -90

Max: 90

Camera rotation in degrees. Positive rotates left, negative rotates right.
move_forward
integer
0

Max: 10

Move the camera forward (zoom in). Higher values push toward a close-up framing.
vertical_tilt
integer
0

Min: -1

Max: 1

Vertical camera tilt. -1 = bird's-eye, 0 = level, 1 = worm's-eye.
use_wide_angle
boolean
False
Switch to a wide-angle lens instruction.
aspect_ratio
None
match_input_image
Aspect ratio for the generated image
go_fast
boolean
True
If num_inference_steps is omitted, true runs the 4-step fast preset and false runs the 40-step detailed preset.
num_inference_steps
integer

Min: 1

Max: 40

Explicit denoising step count (1-40). Leave blank to use the go_fast presets (4 or 40 steps).
lora_weights
string
dx8152/Qwen-Edit-2509-Multiple-angles
LoRA weights to apply. Pass a Hugging Face repo slug like 'dx8152/Qwen-Edit-2509-Multiple-angles' or a direct .safetensors/zip/tar URL (for example, 'https://huggingface.co/flymy-ai/qwen-image-lora/resolve/main/pytorch_lora_weights.safetensors', 'https://example.com/lora_weights.tar.gz', or 'https://example.com/lora_weights.zip').
lora_scale
number
1.25

Max: 4

Strength applied to the selected LoRA.
true_guidance_scale
number
1

Max: 10

True classifier-free guidance scale passed to the pipeline.
seed
integer
Random seed. Set for reproducible generation.
output_format
None
webp
Format of the output images.
output_quality
integer
95

Max: 100

Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs.
disable_safety_checker
boolean
False
Disable safety checker for generated images.

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{'items': {'format': 'uri', 'type': 'string'},
 'title': 'Output',
 'type': 'array'}