image sizing

app.py

@@ -7,10 +7,12 @@ import sys
 from typing import Any, Mapping, Sequence, Union
 
 import gradio as gr
+import numpy as np
 import spaces
 import torch
 import yaml
 from huggingface_hub import hf_hub_download
+from PIL import Image
 
 import folder_paths
 from nodes import NODE_CLASS_MAPPINGS
@@ -56,6 +58,7 @@ hf_hub_download(
 # ReActor has its own special snowflake installation
 os.system("cd custom_nodes/ComfyUI-ReActor && python install.py")
 
+
 def import_custom_nodes() -> None:
     """Find all custom nodes in the custom_nodes folder and add those node objects to NODE_CLASS_MAPPINGS
 
@@ -204,14 +207,16 @@ def add_extra_model_paths() -> None:
 add_comfyui_directory_to_sys_path()
 add_extra_model_paths()
 
+
 @spaces.GPU(duration=60)
 def advance_blur(input_image):
     with torch.inference_mode():
+        image_file_name = os.path.splitext(os.path.basename(input_image))[0]
         loaded_input_image = loadimage.load_image(
             image=input_image,
         )
 
-        image_size =  getimagesize.execute(
+        image_size = getimagesize.execute(
             image=get_value_at_index(loaded_input_image, 0),
         )
         original_width = get_value_at_index(image_size, 0)
@@ -258,14 +263,14 @@ def advance_blur(input_image):
             image=get_value_at_index(upscaled_image, 0),
         )
 
-        saved_image = local_save.process_images(
-            prefix="advance_blur",
-            file_format="JPEG",
-            images=get_value_at_index(final_image, 0),
+        img = Image.fromarray(
+            np.clip(
+                255.0 & get_value_at_index(final_image, 0).cpu().numpy(), 0, 255
+            ).astype(np.uint8)
         )
-
-        saved_path = f"output/{saved_image['ui']['images'][0]['filename']}"
-        return saved_path
+        outpath = f"output/{image_file_name}-advance-blurred.jpg"
+        img.save(outpath, quality=80, dpi=(72, 72))
+        return outpath
 
 
 if __name__ == "__main__":

custom_nodes/comfyui-saveasjpeg/README.md

@@ -0,0 +1,53 @@
+# ComfyUI-Saveasjpeg
+Save a picture as jpeg file in Comfy + Workflow loading
+
+## Warning: 
+
+I'm a novice at best at coding and some of the code is pretty hacky, so this can definitely break.
+
+Also, jpeg only supports files up to 16383 x 16383.
+
+### Known issues:
+
+Import of jpegfiles breaks if import a workflow that has }Prompt:{ in a Node that has dynamic wildcards disabled.
+
+
+Node doesn't resize on Save - image is in there, just needs to be resized to be visible.
+
+## Description:
+
+This adds a custom node to save a picture as a jpeg File and also adds a script to Comfy to drag and drop generated jpegfiles into the UI to load the workflow.
+
+I've added a compression slider and a lossy/lossless option. The compression slider is a bit misleading.
+
+In lossless mode, it only affects the "effort" taken to compress where 100 is the smallest possible size and 1 is the biggest possible size, it's a tradeoff for saving speed.
+
+In lossy mode, that's the other way around, where 100 is the biggest possible size with the least compression and 1 is the smallest possible size with maximum compression. 
+
+On default it's set to lossy with a compression of 80, below are examples for that.
+
+ 
+
+## Installation: 
+
+Use git clone https://github.com/aureagle/ComfyUI-Saveasjpeg in your ComfyUI custom nodes directory
+
+## Examples: 
+
+Lossless with compression set to 100, 17069KB
+https://postimg.cc/2bPkkFN9
+
+Lossless with compression set to 10, 17059KB
+https://postimg.cc/bZTwxt1d
+
+
+Lossy with compression set to 100 , 5384 KB
+https://postimg.cc/WFDpcYCJ
+
+
+Lossy with compression set to 10, 174 KB
+https://postimg.cc/VSkLDkFg
+
+
+Lossy with compression set to 80 ( Default ) , 935 KB
+https://postimg.cc/3yfr6QST

custom_nodes/comfyui-saveasjpeg/Save_as_jpeg.py

@@ -0,0 +1,103 @@
+import numpy as np
+from PIL import Image
+import folder_paths
+import os
+import json
+
+# by Kaharos94
+# https://github.com/Kaharos94/ComfyUI-Saveasjpeg
+# comfyUI node to save an image in jpeg format
+
+class Save_as_jpeg:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+        self.type = "output"
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": 
+                    {"images": ("IMAGE", ),
+                    "filename_prefix": ("STRING", {"default": "ComfyUI"}),
+                    "savePrompt":(["yes","no"],),
+                    "compression":("INT", {"default": 80, "min": 1, "max": 100, "step": 1},)},
+                "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO", "mode":"lossy" },
+                }
+
+    RETURN_TYPES = ()
+    FUNCTION = "Save_as_jpeg"
+
+    OUTPUT_NODE = True
+
+    CATEGORY = "image"
+
+    def Save_as_jpeg(self, savePrompt, compression, images, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None , mode="lossy"):
+        def map_filename(filename):
+            prefix_len = len(os.path.basename(filename_prefix))
+            prefix = filename[:prefix_len + 1]
+            try:
+                digits = int(filename[prefix_len + 1:].split('_')[0])
+            except:
+                digits = 0
+            return (digits, prefix)
+
+        def compute_vars(input):
+            input = input.replace("%width%", str(images[0].shape[1]))
+            input = input.replace("%height%", str(images[0].shape[0]))
+            return input
+
+        filename_prefix = compute_vars(filename_prefix)
+
+        subfolder = os.path.dirname(os.path.normpath(filename_prefix))
+        filename = os.path.basename(os.path.normpath(filename_prefix))
+
+        full_output_folder = os.path.join(self.output_dir, subfolder)
+
+        if os.path.commonpath((self.output_dir, os.path.abspath(full_output_folder))) != self.output_dir:
+            print("Saving image outside the output folder is not allowed.")
+            return {}
+
+        try:
+            counter = max(filter(lambda a: a[1][:-1] == filename and a[1][-1] == "_", map(map_filename, os.listdir(full_output_folder))))[0] + 1
+        except ValueError:
+            counter = 1
+        except FileNotFoundError:
+            os.makedirs(full_output_folder, exist_ok=True)
+            counter = 1
+
+        results = list()
+        for image in images:
+            i = 255. * image.cpu().numpy()
+            img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
+            workflowmetadata = str()
+            promptstr = str()
+            imgexif = img.getexif() #get the (empty) Exif data of the generated Picture
+            
+
+            if prompt is not None:
+                promptstr="".join(json.dumps(prompt)) #prepare prompt String
+                if savePrompt == "yes":
+                    imgexif[0x010f] ="Prompt:"+ promptstr #Add PromptString to EXIF position 0x010f (Exif.Image.Make)
+            if extra_pnginfo is not None:
+                for x in extra_pnginfo:
+                    workflowmetadata += "".join(json.dumps(extra_pnginfo[x]))
+            if savePrompt == "yes":
+                imgexif[0x010e] = "Workflow:"+ workflowmetadata #Add Workflowstring to EXIF position 0x010e (Exif.Image.ImageDescription)
+            file = f"{filename}_{counter:05}_.jpeg"
+            if mode =="lossless":
+                boolloss = True
+            if mode =="lossy":
+                boolloss = False
+            
+
+            img.save(os.path.join(full_output_folder, file), method=6 , exif= imgexif, lossless=boolloss , quality=compression) #Save as jpeg - options to be determined
+            results.append({
+                "filename": file,
+                "subfolder": subfolder,
+                "type": self.type
+            });
+            counter += 1
+
+        return { "ui": { "images": results } }
+NODE_CLASS_MAPPINGS = {
+    "Save_as_jpeg": Save_as_jpeg
+}

custom_nodes/comfyui-saveasjpeg/__init__.py

@@ -0,0 +1,31 @@
+import shutil
+import folder_paths
+import os, sys, subprocess
+import filecmp
+
+
+
+print("### Loading: Save as Jpeg")
+
+comfy_path = os.path.dirname(folder_paths.__file__)
+
+def setup_js():
+   jpeg_path = os.path.dirname(__file__)
+   js_dest_path = os.path.join(comfy_path, "web", "extensions", "jpeginfo")
+   js_src_path = os.path.join(jpeg_path, "jpeginfo", "jpeginfo.js")
+     
+   ## Creating folder if it's not present, then Copy. 
+   print("Copying JS files for Workflow loading")
+   if (os.path.isdir(js_dest_path)==False):
+     os.mkdir(js_dest_path)
+     shutil.copy(js_src_path, js_dest_path)
+   else:
+     shutil.copy(js_src_path, js_dest_path)
+           
+
+                     
+setup_js()
+
+from .Save_as_jpeg import NODE_CLASS_MAPPINGS
+
+__all__ = ['NODE_CLASS_MAPPINGS']

custom_nodes/comfyui-saveasjpeg/jpeginfo/jpeginfo.js

@@ -0,0 +1,73 @@
+import { app } from "/scripts/app.js";
+app.registerExtension({
+	name: "kaharos.jpegsave",
+setup(app,file){
+
+async function getjpegExifData(jpegFile) {
+	const reader = new FileReader();
+	reader.readAsArrayBuffer(jpegFile);
+  
+	return new Promise((resolve, reject) => {
+	  reader.onloadend = function() {
+		const buffer = reader.result;
+		const view = new DataView(buffer);
+		let offset = 0;
+  
+		// Search for the "EXIF" tag
+		while (offset < view.byteLength - 4) {
+		  if (view.getUint32(offset, true) === 0x46495845 /* "EXIF" in big-endian */) {
+			const exifOffset = offset + 6; 
+			const exifData = buffer.slice(exifOffset);
+			const exifString = new TextDecoder().decode(exifData).replaceAll(String.fromCharCode(0), ''); //Remove Null Terminators from string
+			let exifJsonString = exifString.slice(exifString.indexOf("Workflow")); //find beginning of Workflow Exif Tag
+			let promptregex="(?<!\{)}Prompt:{(?![\w\s]*[\}])"; //Regex to split }Prompt:{ // Hacky as fuck - theoretically if somebody has a text encode with dynamic prompts turned off, they could enter }Prompt:{ which breaks this
+			let exifJsonStringMap = new Map([
+			
+			["workflow",exifJsonString.slice(9,exifJsonString.search(promptregex)+1)], // Remove "Workflow:" keyword in front of the JSON workflow data passed
+			["prompt",exifJsonString.substring((exifJsonString.search(promptregex)+8))] //Find and remove "Prompt:" keyword in front of the JSON prompt data
+
+			]);
+			let fullJson=Object.fromEntries(exifJsonStringMap); //object to pass back
+			
+			resolve(fullJson);
+			
+		  }
+  
+		  offset++;
+		}
+  
+		reject(new Error('EXIF metadata not found'));
+}})};
+	
+
+
+const handleFile = app.handleFile;
+app.handleFile = async function(file) { // Add the 'file' parameter to the function definition
+	if (file.type === "image/jpeg") {
+		
+		const jpegInfo =await getjpegExifData(file);
+		if (jpegInfo) {
+			if (jpegInfo.workflow) {
+				if(app.load_workflow_with_components) {
+					app.load_workflow_with_components(jpegInfo.workflow);
+				}
+				else
+					this.loadGraphData(JSON.parse(jpegInfo.workflow));
+			}
+		}
+	} else {
+		return handleFile.apply(this, arguments);
+	}
+}
+
+
+
+
+
+
+
+
+
+
+
+},});