Merge pull request #8974 from bigcat88/v3/nodes/refactor-image-save

[V3] refactoring of the images save nodes

Author: Kosinkadink

comfy_api/v3/ui.py

@@ -4,9 +4,11 @@
 import os
 import random
 from io import BytesIO
+from typing import Type
 
 import av
 import numpy as np
+import torch
 import torchaudio
 from PIL import Image as PILImage
 from PIL.PngImagePlugin import PngInfo
@@ -35,32 +37,161 @@ def type(self) -> FolderType:
         return FolderType(self["type"])
 
 
-class PreviewImage(_UIOutput):
-    def __init__(self, image: Image.Type, animated: bool=False, cls: ComfyNodeV3=None, **kwargs):
-        output_dir = folder_paths.get_temp_directory()
-        prefix_append = "_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for x in range(5))
-        filename_prefix = "ComfyUI" + prefix_append
-
-        full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, output_dir, image[0].shape[1], image[0].shape[0])
-        results = list()
-        for (batch_number, image) in enumerate(image):
-            img = PILImage.fromarray(np.clip(255. * image.cpu().numpy(), 0, 255).astype(np.uint8))
-            metadata = None
-            if not args.disable_metadata and cls is not None:
-                metadata = PngInfo()
-                if cls.hidden.prompt is not None:
-                    metadata.add_text("prompt", json.dumps(cls.hidden.prompt))
-                if cls.hidden.extra_pnginfo is not None:
-                    for x in cls.hidden.extra_pnginfo:
-                        metadata.add_text(x, json.dumps(cls.hidden.extra_pnginfo[x]))
-
+def _get_directory_by_folder_type(folder_type: FolderType) -> str:
+    if folder_type == FolderType.input:
+        return folder_paths.get_input_directory()
+    if folder_type == FolderType.output:
+        return folder_paths.get_output_directory()
+    return folder_paths.get_temp_directory()
+
+
+class ImageSaveHelper:
+    """A helper class with static methods to handle image saving and metadata."""
+
+    @staticmethod
+    def _convert_tensor_to_pil(image_tensor: torch.Tensor) -> PILImage.Image:
+        """Converts a single torch tensor to a PIL Image."""
+        return PILImage.fromarray(np.clip(255.0 * image_tensor.cpu().numpy(), 0, 255).astype(np.uint8))
+
+    @staticmethod
+    def _create_png_metadata(cls: Type[ComfyNodeV3] | None) -> PngInfo | None:
+        """Creates a PngInfo object with prompt and extra_pnginfo."""
+        if args.disable_metadata or cls is None or not cls.hidden:
+            return None
+        metadata = PngInfo()
+        if cls.hidden.prompt:
+            metadata.add_text("prompt", json.dumps(cls.hidden.prompt))
+        if cls.hidden.extra_pnginfo:
+            for x in cls.hidden.extra_pnginfo:
+                metadata.add_text(x, json.dumps(cls.hidden.extra_pnginfo[x]))
+        return metadata
+
+    @staticmethod
+    def _create_animated_png_metadata(cls: Type[ComfyNodeV3] | None) -> PngInfo | None:
+        """Creates a PngInfo object with prompt and extra_pnginfo for animated PNGs (APNG)."""
+        if args.disable_metadata or cls is None or not cls.hidden:
+            return None
+        metadata = PngInfo()
+        if cls.hidden.prompt:
+            metadata.add(
+                b"comf",
+                "prompt".encode("latin-1", "strict")
+                + b"\0"
+                + json.dumps(cls.hidden.prompt).encode("latin-1", "strict"),
+                after_idat=True,
+            )
+        if cls.hidden.extra_pnginfo:
+            for x in cls.hidden.extra_pnginfo:
+                metadata.add(
+                    b"comf",
+                    x.encode("latin-1", "strict")
+                    + b"\0"
+                    + json.dumps(cls.hidden.extra_pnginfo[x]).encode("latin-1", "strict"),
+                    after_idat=True,
+                )
+        return metadata
+
+    @staticmethod
+    def _create_webp_metadata(pil_image: PILImage.Image, cls: Type[ComfyNodeV3] | None) -> PILImage.Exif:
+        """Creates EXIF metadata bytes for WebP images."""
+        exif_data = pil_image.getexif()
+        if args.disable_metadata or cls is None or cls.hidden is None:
+            return exif_data
+        if cls.hidden.prompt is not None:
+            exif_data[0x0110] = "prompt:{}".format(json.dumps(cls.hidden.prompt))  # EXIF 0x0110 = Model
+        if cls.hidden.extra_pnginfo is not None:
+            inital_exif_tag = 0x010F  # EXIF 0x010f = Make
+            for key, value in cls.hidden.extra_pnginfo.items():
+                exif_data[inital_exif_tag] = "{}:{}".format(key, json.dumps(value))
+                inital_exif_tag -= 1
+        return exif_data
+
+    @staticmethod
+    def save_images(
+        images, filename_prefix: str, folder_type: FolderType, cls: Type[ComfyNodeV3] | None, compress_level = 4,
+    ) -> list[SavedResult]:
+        """Saves a batch of images as individual PNG files."""
+        full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(
+            filename_prefix, _get_directory_by_folder_type(folder_type), images[0].shape[1], images[0].shape[0]
+        )
+        results = []
+        metadata = ImageSaveHelper._create_png_metadata(cls)
+        for batch_number, image_tensor in enumerate(images):
+            img = ImageSaveHelper._convert_tensor_to_pil(image_tensor)
             filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
             file = f"{filename_with_batch_num}_{counter:05}_.png"
-            img.save(os.path.join(full_output_folder, file), pnginfo=metadata, compress_level=1)
-            results.append(SavedResult(file, subfolder, FolderType.temp))
+            img.save(os.path.join(full_output_folder, file), pnginfo=metadata, compress_level=compress_level)
+            results.append(SavedResult(file, subfolder, folder_type))
             counter += 1
+        return results
+
+    @staticmethod
+    def save_animated_png(
+        images,
+        filename_prefix: str,
+        folder_type: FolderType,
+        cls: Type[ComfyNodeV3] | None,
+        fps: float,
+        compress_level: int
+    ) -> SavedResult:
+        """Saves a batch of images as a single animated PNG."""
+        full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(
+            filename_prefix, _get_directory_by_folder_type(folder_type), images[0].shape[1], images[0].shape[0]
+        )
+        pil_images = [ImageSaveHelper._convert_tensor_to_pil(img) for img in images]
+        metadata = ImageSaveHelper._create_animated_png_metadata(cls)
+        file = f"{filename}_{counter:05}_.png"
+        save_path = os.path.join(full_output_folder, file)
+        pil_images[0].save(
+            save_path,
+            pnginfo=metadata,
+            compress_level=compress_level,
+            save_all=True,
+            duration=int(1000.0 / fps),
+            append_images=pil_images[1:],
+        )
+        return SavedResult(file, subfolder, folder_type)
+
+    @staticmethod
+    def save_animated_webp(
+        images,
+        filename_prefix: str,
+        folder_type: FolderType,
+        cls: Type[ComfyNodeV3] | None,
+        fps: float,
+        lossless: bool,
+        quality: int,
+        method: int,
+    ) -> SavedResult:
+        """Saves a batch of images as a single animated WebP."""
+        full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(
+            filename_prefix, _get_directory_by_folder_type(folder_type), images[0].shape[1], images[0].shape[0]
+        )
+        pil_images = [ImageSaveHelper._convert_tensor_to_pil(img) for img in images]
+        pil_exif = ImageSaveHelper._create_webp_metadata(pil_images[0], cls)
+        file = f"{filename}_{counter:05}_.webp"
+        pil_images[0].save(
+            os.path.join(full_output_folder, file),
+            save_all=True,
+            duration=int(1000.0 / fps),
+            append_images=pil_images[1:],
+            exif=pil_exif,
+            lossless=lossless,
+            quality=quality,
+            method=method,
+        )
+        return SavedResult(file, subfolder, folder_type)
 
-        self.values = results
+
+class PreviewImage(_UIOutput):
+    def __init__(self, image: Image.Type, animated: bool=False, cls: ComfyNodeV3=None, **kwargs):
+        self.values = ImageSaveHelper.save_images(
+            image,
+            filename_prefix="ComfyUI_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for _ in range(5)),
+            folder_type=FolderType.temp,
+            cls=cls,
+            compress_level=1,
+        )
         self.animated = animated
 
     def as_dict(self):

comfy_extras/v3/nodes_cfg.py

@@ -31,7 +31,7 @@ def define_schema(cls) -> io.SchemaV3:
                 io.Model.Input("model"),
                 io.Float.Input("strength", default=1.0, min=0.0, max=100.0, step=0.01),
             ],
-            outputs=[io.Model.Output("patched_model", display_name="patched_model")],
+            outputs=[io.Model.Output(display_name="patched_model")],
             is_experimental=True,
         )
 
@@ -61,7 +61,7 @@ def define_schema(cls) -> io.SchemaV3:
             inputs=[
                 io.Model.Input("model"),
             ],
-            outputs=[io.Model.Output("patched_model", display_name="patched_model")],
+            outputs=[io.Model.Output(display_name="patched_model")],
         )
 
     @classmethod

comfy_extras/v3/nodes_controlnet.py

@@ -21,8 +21,8 @@ def define_schema(cls):
                 io.Vae.Input("vae", optional=True),
             ],
             outputs=[
-                io.Conditioning.Output("positive_out", display_name="positive"),
-                io.Conditioning.Output("negative_out", display_name="negative"),
+                io.Conditioning.Output(display_name="positive"),
+                io.Conditioning.Output(display_name="negative"),
             ],
         )
 
@@ -71,7 +71,7 @@ def define_schema(cls):
                 io.Combo.Input("type", options=["auto"] + list(UNION_CONTROLNET_TYPES.keys())),
             ],
             outputs=[
-                io.ControlNet.Output("control_net_out"),
+                io.ControlNet.Output(),
             ],
         )
 
@@ -105,8 +105,8 @@ def define_schema(cls):
                 io.Float.Input("end_percent", default=1.0, min=0.0, max=1.0, step=0.001),
             ],
             outputs=[
-                io.Conditioning.Output("positive_out", display_name="positive"),
-                io.Conditioning.Output("negative_out", display_name="negative"),
+                io.Conditioning.Output(display_name="positive"),
+                io.Conditioning.Output(display_name="negative"),
             ],
         )