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zust-ai /zust-diffusion:dc029d0d
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 |
|---|---|---|---|
| is_heartbeat |
boolean
|
False
|
Check if Server Alive
|
| with_detail |
boolean
|
False
|
Detailed Output
|
| pipe_type |
string
|
zust_xl
|
SAM, photoshift, zust_fashion, zust_xl, upscale, enhance, cleanup
|
| photoshift_cleanup_background |
boolean
|
True
|
PhotoShift (Clean source image subject)
|
| photoshift_scene |
string
|
{"image_url": "https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/ps/perfume_scene2.png"}
|
Photoshift subject image
|
| photoshift_subject |
string
|
[{"left": 0, "top": 0, "scale": 0.0009765625, "image_url": "https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/ps/perfume_raw2.png"}]
|
Photoshift subject image?
|
| photoshift_noise |
number
|
0.65
|
Add noise to masked area
|
| photoshift_reference |
number
|
0.35
|
IP-Adapter reference scale
|
| photoshift_prompt_strength |
number
|
1
|
BLIP Caption strength
|
| tags |
string
|
|
Product Tags (jewellery, topdown)
|
| width |
integer
|
1024
|
Width
|
| height |
integer
|
1024
|
height
|
| prompt |
string
|
a handbag on a sofa in a sunlit living room with a bookshelf, plush rug, and a framed painting on the wall
|
Prompt
|
| negative_prompt |
string
|
|
Negative Prompt
|
| subjects |
string
|
[{"left": 0, "top": 0, "scale": 0.0009765625, "image_url": "https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/zust_product/handbag_square.png"}]
|
Subject positions & URLs
|
| is_premium |
boolean
|
False
|
Is this a pro user?
|
| fashion_subject |
string
|
{"left": 0, "top": 0, "scale": 0.0009765625, "image_url": "https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/zust_fashion/fashion_sq.png"}
|
Subject positions & URLs
|
| fashion_mask |
string
|
{"left": 0, "top": 0, "scale": 0.0009765625, "image_url": "https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/zust_fashion/fashion_sq_mask.png"}
|
Fashihon pose
|
| enhance_subject |
string
|
[{"left": 0, "top": 0, "scale": 0.0009765625, "image_url": "https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/enhance/enhance_sub.png"}]
|
Subject data (this shouldn't change)
|
| enhance_scene |
string
|
{"left": 0, "top": 0, "scale": 0.0009765625, "image_url": "https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/enhance/scene_to_be_enhanced.png"}
|
Scene to be enhanced
|
| enhance_reference |
number
|
0.25
|
IP-Adapter strength of scene. If 0 no Reference
|
| enhance_noise |
number
|
0.5
|
Noise to be added in the scene
|
| enhance_prompt |
string
|
|
Enhanced Prompt
|
| enhance_negative_prompt |
string
|
|
Negative Prompt
|
| upscale_url |
string
|
{"image_url": "https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/ps/perfume_scene2.png"}
|
Upscale the Image
|
| upscale_by |
integer
|
2
|
Upscaling factor
|
| sam_url |
string
|
{"image_url": "https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/ps/perfume_scene2.png"}
|
Get SAM Embeddings
|
| pikeya |
string
|
|
Request Type
|
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'}