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Added image resizing related nodes and a single image prediction node

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HowToSD
2025-03-08 03:38:52 -08:00
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docs/reference/node_reference.md
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| [Pt Le](pt_le.md) | Tests whether elements in the first PyTorch tensor are less than or equal to the corresponding elements in the second tensor. |
| [Pt Lt](pt_lt.md) | Tests whether elements in the first PyTorch tensor are less than the corresponding elements in the second tensor. |
| [Pt Ne](pt_ne.md) | Tests whether two PyTorch tensors are not equal element-wise. |
## PyTorch wrapper - Image processing
| Node | Description |
| --- | --- |
| [Pt Crop](pt_crop.md) | Crops a PyTorch tensor to the specified size. The input tensor must have a shape of (c, h, w) or (b, c, h, w). |
| [Pt From Image](pt_from_image.md) | Casts an Image tensor as a PyTorch tensor. |
| [Pt From Image Transpose](pt_from_image_transpose.md) | Casts an image tensor to a PyTorch tensor and transposes it from (H, W, C) to (C, H, W). For rank-4 inputs, the batch axis remains unchanged. |
| [Pt Interpolate By Scale Factor](pt_interpolate_by_scale_factor.md) | Resizes a PyTorch tensor using interpolation by scale factor. The input tensor must have a shape of (c, h, w) or (b, c, h, w). |
| [Pt Interpolate To Size](pt_interpolate_to_size.md) | Resizes a PyTorch tensor using interpolation. The input tensor must have a shape of (c, h, w) or (b, c, h, w). |
| [Pt Pad](pt_pad.md) | Pads a PyTorch tensor to the specified size. Padded area will be black. The input tensor must have a shape of (c, h, w) or (b, c, h, w). |
| [Pt To Image](pt_to_image.md) | Casts a PyTorch tensor as an Image tensor. |
| [Pt To Image Transpose](pt_to_image_transpose.md) | Casts a PyTorch tensor as an Image tensor and transposes it from (C, H, W) to (H, W, C). For rank-4 inputs, the batch axis remains unchanged. |
## PyTorch wrapper - Indexing and Slicing Operations
| Node | Description |
| --- | --- |
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| [Pt Arange](pt_arange.md) | Creates a PyTorch tensor using `torch.arange` with the specified start, end, and step values. |
| [Pt Bool Create](pt_bool_create.md) | Creates a PyTorch tensor of dtype bool from True or False values entered as a list in the text field. |
| [Pt Float Create](pt_float_create.md) | Creates a PyTorch tensor with 32-bit floating point precision |
| [Pt From Image](pt_from_image.md) | Casts an Image tensor as a PyTorch tensor. |
| [Pt From Latent](pt_from_latent.md) | Casts a latent tensor as a PyTorch tensor. |
| [Pt From Numpy](pt_from_numpy.md) | Converts a NumPy ndarray to a PyTorch tensor while preserving its data type. |
| [Pt Full](pt_full.md) | Creates a PyTorch tensor filled with a specified value using the size entered in the text field. |
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## PyTorch wrapper - Tensor data conversion
| Node | Description |
| --- | --- |
| [Pt To Image](pt_to_image.md) | Casts a PyTorch tensor as an Image tensor. |
| [Pt To Latent](pt_to_latent.md) | Casts a PyTorch tensor as a latent tensor. |
| [Pt To Numpy](pt_to_numpy.md) | Converts PyTorch tensor to NumPy ndarray. |
| [Pt To Rgb Tensors](pt_to_rgb_tensors.md) | Splits a PyTorch tensor into R, G, and B tensors. |
| [Pto Adam](pto_adam.md) | Converts PyTorch tensor to NumPy ndarray. |
## PyTorch wrapper - Training
| Node | Description |
| --- | --- |
| [Pt Data Loader](pt_data_loader.md) | Loads data from a dataset node and creates a PyTorch DataLoader. |
| [Pt Evaluate Classification Model](pt_evaluate_classification_model.md) | Performs inference on test data and computes evaluation metrics. |
| [Pt Load Model](pt_load_model.md) | A wrapper class for saving a PyTorch model. |
| [Pt Predict Classification Model](pt_predict_classification_model.md) | Performs inference on input data. |
| [Pt Train Classification Model](pt_train_classification_model.md) | Trains a classification model using a given dataset, optimizer, and number of epochs. |
| [Ptn Conv Model](ptn_conv_model.md) | A convolutional model consisting of multiple convolutional layers. |
| [Ptn Linear Model](ptn_linear_model.md) | A linear model consisting of dense layers. |
| [Pto Adam](pto_adam.md) | Instantiates the Adam optimizer. |
| [Ptv Dataset](ptv_dataset.md) | A Torchvision Dataset class wrapper. |
| [Ptv Dataset Loader](ptv_dataset_loader.md) | A node to combine the dataset and data loader into a single node. |
| [Ptv Image Folder Dataset](ptv_image_folder_dataset.md) | A Torchvision ImageFolder Dataset class wrapper. |
docs/reference/pt_crop.md
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# Pt Crop
Crops a PyTorch tensor to the specified size. The input tensor must have a shape of (c, h, w) or (b, c, h, w).
In ComfyUI Analysis, the tensor data type is "TENSOR," while in ComfyUI, the type "IMAGE" is used. To pass image data from ComfyUI to a ComfyUI Analysis node (e.g., this interpolation node), first use the "Pt From Image" node to convert it to a tensor, then transpose the axes from (b, h, w, c) to (b, c, h, w) before passing it to this node.
This transposition can be performed using the "Pt Permute" node with (0, 2, 3, 1). To convert the output back to an image, apply "Pt Permute" with (0, 3, 1, 2) and then use the "Pt To Image" node.
## Input
| Name | Data type |
|---|---|
| tens | Tensor |
| height | Int |
| width | Int |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Image processing
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pt_from_image.md
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| Tensor |
<HR>
Category: PyTorch wrapper - Tensor creation
Category: PyTorch wrapper - Image processing
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pt_from_image_transpose.md
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# Pt From Image Transpose
Casts an image tensor to a PyTorch tensor and transposes it from (H, W, C) to (C, H, W). For rank-4 inputs, the batch axis remains unchanged.
## Input
| Name | Data type |
|---|---|
| image | Image |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Image processing
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pt_interpolate_by_scale_factor.md
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# Pt Interpolate By Scale Factor
Resizes a PyTorch tensor using interpolation by scale factor. The input tensor must have a shape of (c, h, w) or (b, c, h, w).
In ComfyUI Analysis, the tensor data type is "TENSOR," while in ComfyUI, the type "IMAGE" is used. To pass image data from ComfyUI to a ComfyUI Analysis node (e.g., this interpolation node), first use the "Pt From Image" node to convert it to a tensor, then transpose the axes from (b, h, w, c) to (b, c, h, w) before passing it to this node.
This transposition can be performed using the "Pt Permute" node with (0, 2, 3, 1). To convert the output back to an image, apply "Pt Permute" with (0, 3, 1, 2) and then use the "Pt To Image" node.
## Input
| Name | Data type |
|---|---|
| tens | Tensor |
| scale_factor | Float |
| mode | |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Image processing
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pt_interpolate_to_size.md
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# Pt Interpolate To Size
Resizes a PyTorch tensor using interpolation. The input tensor must have a shape of (c, h, w) or (b, c, h, w).
In ComfyUI Analysis, the tensor data type is "TENSOR," while in ComfyUI, the type "IMAGE" is used. To pass image data from ComfyUI to a ComfyUI Analysis node (e.g., this interpolation node), first use the "Pt From Image" node to convert it to a tensor, then transpose the axes from (b, h, w, c) to (b, c, h, w) before passing it to this node.
This transposition can be performed using the "Pt Permute" node with (0, 2, 3, 1). To convert the output back to an image, apply "Pt Permute" with (0, 3, 1, 2) and then use the "Pt To Image" node.
## Input
| Name | Data type |
|---|---|
| tens | Tensor |
| height | Int |
| width | Int |
| mode | |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Image processing
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pt_pad.md
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# Pt Pad
Pads a PyTorch tensor to the specified size. Padded area will be black. The input tensor must have a shape of (c, h, w) or (b, c, h, w).
In ComfyUI Analysis, the tensor data type is "TENSOR," while in ComfyUI, the type "IMAGE" is used. To pass image data from ComfyUI to a ComfyUI Analysis node (e.g., this interpolation node), first use the "Pt From Image" node to convert it to a tensor, then transpose the axes from (b, h, w, c) to (b, c, h, w) before passing it to this node.
This transposition can be performed using the "Pt Permute" node with (0, 2, 3, 1). To convert the output back to an image, apply "Pt Permute" with (0, 3, 1, 2) and then use the "Pt To Image" node.
## Input
| Name | Data type |
|---|---|
| tens | Tensor |
| height | Int |
| width | Int |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Image processing
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pt_predict_classification_model.md
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# Pt Predict Classification Model
Performs inference on input data.
## Input
| Name | Data type |
|---|---|
| model | Ptmodel |
| inputs | Tensor |
| class_id_to_name_map | Pydict |
| use_gpu | Boolean |
## Output
| Data type |
|---|
| String |
| Int |
| Float |
<HR>
Category: PyTorch wrapper - Training
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pt_to_image.md
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| Image |
<HR>
Category: PyTorch wrapper - Tensor data conversion
Category: PyTorch wrapper - Image processing
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pt_to_image_transpose.md
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# Pt To Image Transpose
Casts a PyTorch tensor as an Image tensor and transposes it from (C, H, W) to (H, W, C). For rank-4 inputs, the batch axis remains unchanged.
## Input
| Name | Data type |
|---|---|
| tens | Tensor |
## Output
| Data type |
|---|
| Image |
<HR>
Category: PyTorch wrapper - Image processing
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pto_adam.md
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# Pto Adam
Converts PyTorch tensor to NumPy ndarray.
Instantiates the Adam optimizer.
## Input
| Name | Data type |
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| Ptoptimizer |
<HR>
Category: PyTorch wrapper - Tensor data conversion
Category: PyTorch wrapper - Training
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.