feat: added image_from_url node

.gitignore

@@ -0,0 +1,2 @@
+db.json
+__pycache__

__init__.py

@@ -1,3 +1,19 @@
-from .lora_info import NODE_CLASS_MAPPINGS,WEB_DIRECTORY,NODE_DISPLAY_NAME_MAPPINGS
+from .lora_info import LoraInfo
+from .image_from_url import ImageFromURL
+
+# A dictionary that contains all nodes you want to export with their names
+# NOTE: names should be globally unique
+NODE_CLASS_MAPPINGS = {
+    "LoraInfo": LoraInfo,
+    "ImageFromURL": ImageFromURL
+}
+
+# A dictionary that contains the friendly/humanly readable titles for the nodes
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "LoraInfo": "Lora Info",
+    "ImageFromURL": "Image From URL"
+}
+
+WEB_DIRECTORY = "./js"
 
 __all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS", "WEB_DIRECTORY"]

image_from_url.py

@@ -0,0 +1,30 @@
+from PIL import Image, ImageOps
+import requests
+import torch
+import numpy
+
+class ImageFromURL:
+    def __init__(self):
+        pass
+    
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "url": ("STRING", {"multiline": False})
+            },
+        }
+
+    RETURN_NAMES = ("image",)
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "fetch_image"
+    OUTPUT_NODE = True
+    CATEGORY = "jitcoder"
+
+    def fetch_image(self, url):
+        image = Image.open(requests.get(url, stream=True).raw)
+        image = ImageOps.exif_transpose(image)
+        image = image.convert("RGB")
+        image = numpy.array(image).astype(numpy.float32) / 255.0
+        image = torch.from_numpy(image)[None,]
+        return (image,)

js/index.js

@@ -56,3 +56,42 @@ app.registerExtension({
     }
   },
 });
+
+
+app.registerExtension({
+  name: "ImageFromURL",
+  async beforeRegisterNodeDef(nodeType, nodeData, app) {
+    if (nodeData.name === "ImageFromURL") {
+
+      const onNodeCreated = nodeType.prototype.onNodeCreated;
+      nodeType.prototype.onNodeCreated = function () {
+        onNodeCreated ? onNodeCreated.apply(this, []) : undefined;
+
+        const [urlWidget] = this.widgets;
+        let originalDescriptor = Object.getOwnPropertyDescriptor(urlWidget, 'value');
+
+        Object.defineProperty(urlWidget, 'value', {
+          get() {
+            const ret = originalDescriptor.get?.call(urlWidget) || originalDescriptor.value || '';
+            return ret
+          },
+          set(value) {
+            if (originalDescriptor.set) {
+              originalDescriptor.set.call(urlWidget, value);
+            } else {
+              originalDescriptor.value = value;
+            }
+            
+            const body = new FormData();
+            body.append('url',value);
+            api
+              .fetchApi("/fetch_image", { method: "POST", body, })
+              .then((resp) => {
+
+              })
+          }
+        });
+      }
+    }
+  },
+});

lora_info.py

@@ -3,7 +3,6 @@ import hashlib
 import requests
 import json
 import server
-from server import PromptServer
 from aiohttp import web
 import os
 
@@ -114,9 +113,6 @@ async def fetch_lora_info(request):
 
     return web.json_response({"output": output, "triggerWords": triggerWords, "examplePrompt": examplePrompt, "baseModel": baseModel})
 
-dictionary_of_stuff = {"something":"A text message"}
-PromptServer.instance.send_sync("my-message-handle", dictionary_of_stuff)
-
 class LoraInfo:
     def __init__(self):
         pass
@@ -139,15 +135,4 @@ class LoraInfo:
         (output, triggerWords, examplePrompt, baseModel) = get_lora_info(lora_name)
         return {"ui": {"text": (output,), "model": (baseModel,)}, "result": (triggerWords, examplePrompt)}
 
-# A dictionary that contains all nodes you want to export with their names
-# NOTE: names should be globally unique
-NODE_CLASS_MAPPINGS = {
-    "LoraInfo": LoraInfo,
-}
 
-# A dictionary that contains the friendly/humanly readable titles for the nodes
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "LoraInfo": "Lora Info",
-}
-
-WEB_DIRECTORY = "./js"

readme.md

@@ -1,3 +1,27 @@
+# Contains 2 Nodes
+- Lora Info
+- Image From URL
+
+Apologies for shoving another node into this repo, I'll eventually create a new repo for the Image From URL 
+
+## Installation
+
+#### Method 1. 
+Open ComfyUI Manager, search for "lorainfo", or "jitcoder", click install
+
+#### Method 2.
+
+Inside ComfyUI/custom-nodes
+
+```sh
+git clone https://github.com/jitcoder/lora-info.git
+```
+
+#### Method 3.
+
+Download this repo as a zip and extract in the custom-nodes directory.
+
+
 ## Lora Info
 
 Shows Lora Base Model, Trigger Words and Examples
@@ -9,15 +33,10 @@ Special thanks to:
 
 ![image](preview.png)
 
-## Installation
 
-Inside ComfyUI/custom-nodes
+## Image From URL
 
-```sh
-git clone https://github.com/jitcoder/lora-info.git
-```
-
-Or download this repo as a zip and extract in the custom-nodes directory.
-
-Restart ComfyUI
+Loads an image from the URL and makes it available for use in your workflow. This is especially useful if you intend on 
+sharing your workflows and want to make it easier for users to use them instead of having to download images separately.
 
+![image](image-from-url.png)