From 5663ff9e36da98e654d0d23dd3b95e090ebc605a Mon Sep 17 00:00:00 2001
From: Radionic <khpluslt@gmail.com>
Date: Thu, 16 Nov 2023 19:02:29 +0800
Subject: [PATCH] fix: auto segments not shown

---
 js/LayerEditor.js | 19 ++++++++-----------
 js/index.js       | 11 ++++++++---
 2 files changed, 16 insertions(+), 14 deletions(-)

diff --git a/js/LayerEditor.js b/js/LayerEditor.js
index 4eab270..f2e8730 100644
--- a/js/LayerEditor.js
+++ b/js/LayerEditor.js
@@ -42,13 +42,13 @@ const faceLandmarker = await FaceLandmarker.createFromOptions(filesetResolver, {
 const layerMapping = {
   L_eye: {
     useMiddle: false,
-    positiveOffset: 0.1,
+    positiveOffset: 0,
     negativeOffset: 0.5,
     indices: FaceLandmarker.FACE_LANDMARKS_RIGHT_EYE,
   },
   R_eye: {
     useMiddle: false,
-    positiveOffset: 0.1,
+    positiveOffset: 0,
     negativeOffset: 0.5,
     indices: FaceLandmarker.FACE_LANDMARKS_LEFT_EYE,
   },
@@ -84,14 +84,12 @@ const layerMapping = {
   },
 };
 
-async function drawPoints(part) {}
-
-async function autoSegment() {
+export async function autoSegment() {
   const image = document.getElementById("image");
   const landmarks = faceLandmarker.detect(image).faceLandmarks[0];
-  Object.entries(layerMapping).forEach(([key, value]) => {
-    imagePromptsMulti.val[key] = [];
-  });
+  // Object.entries(layerMapping).forEach(([key, value]) => {
+  //   imagePromptsMulti.val[key] = [];
+  // });
 
   Object.entries(layerMapping).forEach(([key, value]) => {
     const positivePoints = [];
@@ -101,7 +99,7 @@ async function autoSegment() {
     // Positive points
     for (const { start, end } of value.indices) {
       const startPoint = landmarks[start];
-      const endPoint = landmarks[end];
+      // const endPoint = landmarks[end];
 
       const startX = startPoint.x * imageSize.val.width;
       const startY = startPoint.y * imageSize.val.height;
@@ -190,6 +188,7 @@ async function autoSegment() {
       ];
     }
   });
+  imagePrompts.val = imagePromptsMulti.val[selectedLayer.val];
   console.log("Done");
 }
 
@@ -435,8 +434,6 @@ export function LayerEditor() {
           const canvas = document.getElementById("mask-canvas");
           canvas.width = e.target.naturalWidth;
           canvas.height = e.target.naturalHeight;
-
-          await autoSegment();
         },
         oncontextmenu: async (e) => {
           e.preventDefault();
diff --git a/js/index.js b/js/index.js
index 2d5ff99..6955d7f 100644
--- a/js/index.js
+++ b/js/index.js
@@ -23,7 +23,7 @@ import { api } from "./api.js";
 import { Container } from "./Container.js";
 import { initModel, loadNpyTensor } from "./onnx.js";
 import "https://code.iconify.design/3/3.1.0/iconify.min.js";
-import { drawSegment, getClicks } from "./LayerEditor.js";
+import { autoSegment, drawSegment, getClicks } from "./LayerEditor.js";
 import { infoDialog } from "./dialog.js";
 
 export const generatedImages = {};
@@ -274,7 +274,11 @@ function getInputWidgetValue(node, inputIndex, widgetName) {
  * @param {LGraphNode} node
  */
 function showMyImageEditor(node) {
-  let [isGeneratedImage, connectedImageFileName] = getInputWidgetValue(node, 0, "image");
+  let [isGeneratedImage, connectedImageFileName] = getInputWidgetValue(
+    node,
+    0,
+    "image"
+  );
   if (!connectedImageFileName) {
     alertDialog.val = {
       text: "Please connect or generate an image first",
@@ -338,8 +342,9 @@ function showMyImageEditor(node) {
             `${id}_${modelType}.npy`
           )}&type=output&subfolder=`
         );
-        loadNpyTensor(embeedingUrl).then((tensor) => {
+        loadNpyTensor(embeedingUrl).then(async (tensor) => {
           embeddings.val = tensor;
+          await autoSegment();
           drawSegment(getClicks());
         });
         targetNode.val = node;