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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
|
Input image (JPEG, PNG, WebP). The model estimates camera intrinsics and gravity direction from this single image.
|
|
| camera_model |
None
|
pinhole
|
Camera model to fit. 'pinhole' for standard lenses, 'simple_radial' or 'radial' for barrel/pincushion distortion, 'simple_divisional' for fisheye lenses.
|
| use_distorted_weights |
boolean
|
False
|
Use the 'distorted' pretrained weights instead of 'pinhole'. Enable this for images with visible lens distortion (fisheye, wide-angle). The distorted weights were trained on distorted images and produce better results when distortion parameters are being estimated.
|
| focal_length_prior |
number
|
0
|
Optional known focal length in pixels. If provided, the optimizer uses this as a strong prior, improving gravity estimation accuracy. Set to 0 to disable.
|
| return_visualization |
boolean
|
True
|
Generate a visualization image showing the predicted geometric fields (up-vectors, latitude, confidence maps) overlaid on the input.
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'properties': {'calibration_json': {'format': 'uri',
'title': 'Calibration Json',
'type': 'string'},
'visualization': {'format': 'uri',
'title': 'Visualization',
'type': 'string'}},
'required': ['calibration_json', 'visualization'],
'title': 'Output',
'type': 'object'}