Merge branch 'beta' of github.com:cmdr2/stable-diffusion-ui into beta

.github/FUNDING.yml

@@ -1,3 +1,3 @@
 # These are supported funding model platforms
 
-ko_fi: cmdr2_stablediffusion_ui
+ko_fi: easydiffusion

README.md

@@ -13,18 +13,21 @@ Does not require technical knowledge, does not require pre-installed software. 1
 Click the download button for your operating system:
 
 <p float="left">
-  <a href="https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.5.41a/Easy-Diffusion-Windows.exe"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-win.png" width="200" /></a>
+  <a href="https://github.com/cmdr2/stable-diffusion-ui/releases/latest/download/Easy-Diffusion-Linux.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-linux.png" width="200" /></a>
-  <a href="https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.5.41a/Easy-Diffusion-Linux.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-linux.png" width="200" /></a>
+  <a href="https://github.com/cmdr2/stable-diffusion-ui/releases/latest/download/Easy-Diffusion-Mac.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-mac.png" width="200" /></a>
-  <a href="https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.5.41a/Easy-Diffusion-Mac.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-mac.png" width="200" /></a>
+  <a href="https://github.com/cmdr2/stable-diffusion-ui/releases/latest/download/Easy-Diffusion-Windows.exe"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-win.png" width="200" /></a>
 </p>
 
 **Hardware requirements:**
-- **Windows:** NVIDIA graphics card (minimum 2 GB RAM), or run on your CPU.
+- **Windows:** NVIDIA graphics card¹ (minimum 2 GB RAM), or run on your CPU.
-- **Linux:** NVIDIA or AMD graphics card (minimum 2 GB RAM), or run on your CPU.
+- **Linux:** NVIDIA¹ or AMD² graphics card (minimum 2 GB RAM), or run on your CPU.
 - **Mac:** M1 or M2, or run on your CPU.
 - Minimum 8 GB of system RAM.
 - Atleast 25 GB of space on the hard disk.
 
+¹) [CUDA Compute capability](https://en.wikipedia.org/wiki/CUDA#GPUs_supported) level of 3.7 or higher required.
+
+²) ROCm 5.2 support required.
 
 The installer will take care of whatever is needed. If you face any problems, you can join the friendly [Discord community](https://discord.com/invite/u9yhsFmEkB) and ask for assistance.
 

ui/media/js/main.js

@@ -678,6 +678,29 @@ function getAllModelNames(type) {
     return f(modelsOptions[type])
 }
 
+// gets a flattened list of all models of a certain type. e.g. "path/subpath/modelname"
+// use the filter to search for all models having a certain name.
+function getAllModelPathes(type,filter="") {
+    function f(tree, prefix) {
+        if (tree == undefined) {
+            return []
+        }
+        let result = []
+        tree.forEach((e) => {
+            if (typeof e == "object") {
+                result = result.concat(f(e[1], prefix + e[0] + "/"))
+            } else {
+                if (filter=="" || e==filter) {
+                    result.push(prefix + e)
+                }
+            }
+        })
+        return result
+    }
+    return f(modelsOptions[type], "")
+}
+
+
 function onUseAsThumbnailClick(req, img) {
     let scale = 1
     let targetWidth = img.naturalWidth

ui/plugins/ui/lora-prompt-parser.plugin.js

@@ -29,22 +29,13 @@
             let modelWeights = LoRA.map(e => e.lora_alpha_0)
             loraModelField.value = {modelNames: modelNames, modelWeights: modelWeights}
 
-            showToast("Prompt successfully processed", LoRA[0].lora_model_0);
+            showToast("Prompt successfully processed")
 			
         }
             
         //promptField.dispatchEvent(new Event('change'));
     });
     
-    function isModelAvailable(array, searchString) {
-        const foundItem = array.find(function(item) {
-            item = item.toString().toLowerCase();
-            return item === searchString.toLowerCase()
-        });
-
-        return foundItem || "";
-    }
-
     // extract LoRA tags from strings
     function extractLoraTags(prompt) {
         // Define the regular expression for the tags
@@ -55,11 +46,13 @@
 
         // Iterate over the string, finding matches
         for (const match of prompt.matchAll(regex)) {
-            const modelFileName = isModelAvailable(modelsCache.options.lora, match[1].trim())
+            const modelFileName = match[1].trim()
-            if (modelFileName !== "") {
+            const loraPathes = getAllModelPathes("lora", modelFileName)
+            if (loraPathes.length > 0) {
+                const loraPath = loraPathes[0]
                 // Initialize an object to hold a match
                 let loraTag = {
-                    lora_model_0: modelFileName,
+                    lora_model_0: loraPath,
                 }
 				//console.log("Model:" +  modelFileName);