From ff4153667d38d7e64829b14d565c08b442e2ecfc Mon Sep 17 00:00:00 2001
From: yueliang <2567830152@qq.com>
Date: Wed, 9 Oct 2024 18:25:56 +0800
Subject: [PATCH] add auxiliary tool

---
 nodes/imagePath2Tensor.py | 58 +++++++++++++++++++++++++++++++++++++++
 nodes_map.py              |  3 ++
 2 files changed, 61 insertions(+)
 create mode 100644 nodes/imagePath2Tensor.py

diff --git a/nodes/imagePath2Tensor.py b/nodes/imagePath2Tensor.py
new file mode 100644
index 0000000..1bc7249
--- /dev/null
+++ b/nodes/imagePath2Tensor.py
@@ -0,0 +1,58 @@
+import os
+import torch
+from PIL import ImageOps
+import comfy
+from PIL import Image
+import numpy as np
+
+class AnyType(str):
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+any_type = AnyType("*")
+
+class ImagePath2Tensor:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": { 
+                "image_paths": (any_type,),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE","INT")
+    RETURN_NAMES = ("image","image_count")
+    FUNCTION = "image_path_to_tensor"
+    OUTPUT_NODE = True
+    CATEGORY = "🔥FFmpeg/auxiliary tool"
+  
+    def image_path_to_tensor(self, image_paths):
+        try:
+            #['D:\\Cache\\222\\frame_00000121.png', 'D:\\Cache\\222\\frame_00000122.png']
+            images = []
+            for image_path in image_paths:
+                # Open and process the image
+                with Image.open(image_path) as img:
+                    img = ImageOps.exif_transpose(img).convert("RGB")
+                    # Directly convert to torch tensor without numpy intermediate
+                    image_tensor = torch.from_numpy(np.array(np.array(img).astype(np.float32) / 255.0))[None,]
+                    images.append(image_tensor)
+                
+            if len(images) == 0:
+                raise ValueError("No images loaded successfully.")
+            if len(images) == 1:
+                return (images[0], 1)
+
+            elif len(images) > 1:
+                image1 = images[0]
+                for image2 in images[1:]:
+                    if image1.shape[1:] != image2.shape[1:]:
+                        image2 = comfy.utils.common_upscale(image2.movedim(-1, 1), image1.shape[2], image1.shape[1], "bilinear", "center").movedim(1, -1)
+                    image1 = torch.cat((image1, image2), dim=0)
+                return (image1, len(images))
+
+        except Exception as e:
+            raise ValueError(e)
\ No newline at end of file
diff --git a/nodes_map.py b/nodes_map.py
index cf278ac..df0ab4e 100644
--- a/nodes_map.py
+++ b/nodes_map.py
@@ -6,6 +6,7 @@ from .nodes.videoFlip import *
 from .nodes.extractAudio import *
 from .nodes.loadImageFromDir import *
 from .nodes.imageCopy import *
+from .nodes.imagePath2Tensor import *
 
 NODE_CLASS_MAPPINGS = {
     "Video2Frames": Video2Frames,
@@ -16,6 +17,7 @@ NODE_CLASS_MAPPINGS = {
     "ExtractAudio": ExtractAudio,
     "LoadImageFromDir": LoadImageFromDir,
     "ImageCopy": ImageCopy,
+    "ImagePath2Tensor": ImagePath2Tensor,
 }
 
 # A dictionary that contains the friendly/humanly readable titles for the nodes
@@ -28,4 +30,5 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ExtractAudio": "🔥ExtractAudio",
     "LoadImageFromDir": "🔥LoadImageFromDir",
     "ImageCopy": "🔥ImageCopy",
+    "ImagePath2Tensor": "🔥ImagePath2Tensor",
 }