Added Pt To Image, Pt To Latent, Pt From Image, Pt To Image nodes.

__init__.py

@@ -116,8 +116,12 @@ from .modules.pandas_wrapper.pandas_vertical_concat import PandasVerticalConcat
 from .modules.pandas_wrapper.pandas_vertical_split import PandasVerticalSplit
 from .modules.pandas_wrapper.pandas_xs import PandasXs
 from .modules.pytorch_wrapper.pt_float_create import PtFloatCreate
+from .modules.pytorch_wrapper.pt_from_image import PtFromImage
+from .modules.pytorch_wrapper.pt_from_latent import PtFromLatent
 from .modules.pytorch_wrapper.pt_from_numpy import PtFromNumpy
 from .modules.pytorch_wrapper.pt_int_create import PtIntCreate
+from .modules.pytorch_wrapper.pt_to_image import PtToImage
+from .modules.pytorch_wrapper.pt_to_latent import PtToLatent
 from .modules.pytorch_wrapper.pt_to_numpy import PtToNumpy
 from .modules.seaborn_wrapper.sns_bar import SNSBar
 from .modules.seaborn_wrapper.sns_histogram import SNSHistogram
@@ -245,8 +249,12 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
     "PandasVerticalSplit": PandasVerticalSplit,
     "PandasXs": PandasXs,
     "PtFloatCreate": PtFloatCreate,
+    "PtFromImage": PtFromImage,
+    "PtFromLatent": PtFromLatent,
     "PtFromNumpy": PtFromNumpy,
     "PtIntCreate": PtIntCreate,
+    "PtToImage": PtToImage,
+    "PtToLatent": PtToLatent,
     "PtToNumpy": PtToNumpy,
     "PyKvFloatCreate": PyKvFloatCreate,
     "PyKvIntCreate": PyKvIntCreate,
@@ -377,8 +385,12 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
     "PandasVerticalSplit": "Pandas Vertical Split",
     "PandasXs": "Pandas Xs",
     "PtFloatCreate": "Pt Float Create",
+    "PtFromImage": "Pt From Image",
+    "PtFromLatent": "Pt From Latent",
     "PtFromNumpy": "Pt From Numpy",
     "PtIntCreate": "Pt Int Create",
+    "PtToImage": "Pt To Image",
+    "PtToLatent": "Pt To Latent",
     "PtToNumpy": "Pt To Numpy",
     "PyKvFloatCreate": "Py Kv Float Create",
     "PyKvIntCreate": "Py Kv Int Create",

docs/reference/node_reference.md

@@ -132,8 +132,12 @@
 | Node | Description |
 | --- | --- |
 | [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 Int Create](pt_int_create.md) | Creates a PyTorch tensor with 32-bit integer  |
+| [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. |
 ## Python wrapper
 | Node | Description |

docs/reference/pt_from_image.md

@@ -0,0 +1,17 @@
+# Pt From Image
+Casts an Image tensor as a PyTorch tensor.
+
+## Input
+| Name | Data type |
+|---|---|
+| image | Image |
+
+## Output
+| Data type |
+|---|
+| Tensor |
+
+<HR>
+Category: PyTorch wrapper
+
+ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.

docs/reference/pt_from_latent.md

@@ -0,0 +1,17 @@
+# Pt From Latent
+Casts a latent tensor as a PyTorch tensor.
+
+## Input
+| Name | Data type |
+|---|---|
+| latent | Latent |
+
+## Output
+| Data type |
+|---|
+| Tensor |
+
+<HR>
+Category: PyTorch wrapper
+
+ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.

docs/reference/pt_to_image.md

@@ -0,0 +1,17 @@
+# Pt To Image
+Casts a PyTorch tensor as an Image tensor.
+
+## Input
+| Name | Data type |
+|---|---|
+| tens | Tensor |
+
+## Output
+| Data type |
+|---|
+| Image |
+
+<HR>
+Category: PyTorch wrapper
+
+ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.

docs/reference/pt_to_latent.md

@@ -0,0 +1,17 @@
+# Pt To Latent
+Casts a PyTorch tensor as a latent tensor.
+
+## Input
+| Name | Data type |
+|---|---|
+| tens | Tensor |
+
+## Output
+| Data type |
+|---|
+| Latent |
+
+<HR>
+Category: PyTorch wrapper
+
+ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.

modules/pytorch_wrapper/pt_from_image.py

@@ -0,0 +1,40 @@
+from typing import Any, Dict
+import torch
+
+
+class PtFromImage:
+    """
+    Casts an Image tensor as a PyTorch tensor.
+
+    category: PyTorch wrapper
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return {
+            "required": {
+                "image": ("IMAGE", {}),
+            }
+        }
+
+    RETURN_TYPES: tuple = ("TENSOR",)
+    FUNCTION: str = "f"
+    CATEGORY: str = "PyTorch wrapper"
+
+    def f(self, image: torch.Tensor) -> tuple:
+        """
+        Casts an Image tensor as a PyTorch tensor.
+
+        Args:
+            image (torch.Tensor): Image tensor
+
+        Returns:
+            tuple: A tuple containing the PyTorch tensor.
+        """
+        return (image,)

modules/pytorch_wrapper/pt_from_latent.py

@@ -0,0 +1,40 @@
+from typing import Any, Dict
+import torch
+
+
+class PtFromLatent:
+    """
+    Casts a latent tensor as a PyTorch tensor.
+
+    category: PyTorch wrapper
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return {
+            "required": {
+                "latent": ("LATENT", {}),
+            }
+        }
+
+    RETURN_TYPES: tuple = ("TENSOR",)
+    FUNCTION: str = "f"
+    CATEGORY: str = "PyTorch wrapper"
+
+    def f(self, latent: torch.Tensor) -> tuple:
+        """
+        Casts a latent tensor as a PyTorch tensor.
+
+        Args:
+            latent (torch.Tensor): Latent tensor
+
+        Returns:
+            tuple: A tuple containing the PyTorch tensor.
+        """
+        return (latent,)

modules/pytorch_wrapper/pt_to_image.py

@@ -0,0 +1,40 @@
+from typing import Any, Dict
+import torch
+
+
+class PtToImage:
+    """
+    Casts a PyTorch tensor as an Image tensor.
+
+    category: PyTorch wrapper
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return {
+            "required": {
+                "tens": ("TENSOR", {}),
+            }
+        }
+
+    RETURN_TYPES: tuple = ("IMAGE",)
+    FUNCTION: str = "f"
+    CATEGORY: str = "PyTorch wrapper"
+
+    def f(self, tens: torch.Tensor) -> tuple:
+        """
+        Casts a PyTorch tensor as an Image tensor.
+
+        Args:
+            tens (torch.Tensor): PyTorch Tensor
+
+        Returns:
+            tuple: A tuple containing the image tensor.
+        """
+        return (tens,)

modules/pytorch_wrapper/pt_to_latent.py

@@ -0,0 +1,40 @@
+from typing import Any, Dict
+import torch
+
+
+class PtToLatent:
+    """
+    Casts a PyTorch tensor as a latent tensor.
+
+    category: PyTorch wrapper
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return {
+            "required": {
+                "tens": ("TENSOR", {}),
+            }
+        }
+
+    RETURN_TYPES: tuple = ("LATENT",)
+    FUNCTION: str = "f"
+    CATEGORY: str = "PyTorch wrapper"
+
+    def f(self, tens: torch.Tensor) -> tuple:
+        """
+        Casts a PyTorch tensor as a latent tensor.
+
+        Args:
+            tens (torch.Tensor): PyTorch Tensor
+
+        Returns:
+            tuple: A tuple containing the latent tensor.
+        """
+        return (tens,)

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "data-analysis"
 description = "Data analysis custom modules for ComfyUI - Use Pandas & Matplotlib within ComfyUI"
-version = "1.3.0"
+version = "1.3.2"
 license = {file = "LICENSE"}
 
 [project.urls]