KeighBee HF staff commited on
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1 Parent(s): 6172196

changed inputs and outputs for model, and changed names

Browse files
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README.md CHANGED
@@ -20,9 +20,9 @@ DepthPro is a monocular depth estimation model. This means that it is trained to
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  | Variant | Size (MB) |
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  | ------------------------------------------------------- | ---------: |
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  |[DepthPro](DepthPro.mlpackage)| 1900 |
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- |[DepthPro: Pruned 10% Sparsity, Quantized Linear Symmetric](DepthPro-pruned10-Qlinear.mlpackage)| 1100 |
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  |[DepthPro Normalized Inverse Depth](DepthProNormalizedInverseDepth.mlpackage)| 1290 |
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- |[DepthPro Normalized Inverse Depth: Pruned 10% Sparsity, Quantized Linear Symmetric](DepthPro-pruned10-Qlinear.mlpackage)| 745 |
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  ## Model Inputs and Outputs
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@@ -30,22 +30,22 @@ DepthPro is a monocular depth estimation model. This means that it is trained to
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  #### Inputs
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- - `pixel_values`: 1536x1536 3 color image.
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  #### Outputs
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- - `normalized_inverse_depth` 1536x1536 monochrome image.
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  ### DepthPro Models
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  #### Inputs
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- - `pixel_values`: 1536x1536 3 color image.
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- - `original_widths`: 1x1x1x1 Tensor containing the original width of the image before resizing.
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  #### Outputs
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- - `depth_meters`: 1x1x1536x1536 Tensor containing depth in meters.
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  ## Download
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  | Variant | Size (MB) |
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  | ------------------------------------------------------- | ---------: |
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  |[DepthPro](DepthPro.mlpackage)| 1900 |
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+ |[DepthPro: Pruned 10% Sparsity, Quantized Linear Symmetric](DepthProPruned10QuantizedLinear.mlpackage)| 1100 |
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  |[DepthPro Normalized Inverse Depth](DepthProNormalizedInverseDepth.mlpackage)| 1290 |
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+ |[DepthPro Normalized Inverse Depth: Pruned 10% Sparsity, Quantized Linear Symmetric](DepthProNormalizedInverseDepthPruned10QuantizedLinear.mlpackage)| 745 |
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  ## Model Inputs and Outputs
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  #### Inputs
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+ - `image`: 1536x1536 3 color image.
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  #### Outputs
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+ - `normalizedInverseDepth` 1536x1536 monochrome image.
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  ### DepthPro Models
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  #### Inputs
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+ - `image`: 1536x1536 3 color image.
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+ - `originalWidth`: 1x1x1x1 Tensor containing the original width of the image before resizing.
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  #### Outputs
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+ - `depthMeters`: 1x1x1536x1536 Tensor containing depth in meters.
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  ## Download
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