feat: extract boundary points and combine points node

blender/avatar_main_output.py

@@ -1,6 +1,6 @@
 import platform
 import blender_node
-from mesh_utils import assign_texture, open_in_blender as open_blender, export_gltf
+from mesh_utils import upload_avatar_file, open_in_blender as open_blender, export_gltf
 import folder_paths
 
 global_blender_path = ''
@@ -47,14 +47,16 @@ class AvatarMainOutput(blender_node.ObjectOps):
         }),
         "model_type": (["AVA","GLB", "GLTF_EMBEDDED"],),
         "write_mode": (["Overwrite", "Increment"],),
-
+        "upload_to_cloud": ("BOOLEAN", {
+            "default": False
+        }),
         "SHAPE_FLOW": ("SHAPE_FLOW",),
     }
 
     OUTPUT_NODE = True
     RETURN_TYPES = ()
 
-    def blender_process(self, bpy, BPY_OBJ=None, BPY_OBJS=None, open_in_blender=False, auto_save=False, blender_path_override='', filename='', model_type='', write_mode='', SHAPE_FLOW=''):
+    def blender_process(self, bpy, BPY_OBJ=None, BPY_OBJS=None, open_in_blender=False, auto_save=False, blender_path_override='', filename='', model_type='', write_mode='', upload_to_cloud=False, SHAPE_FLOW=''):
         if open_in_blender:
             p = blender_path_override if blender_path_override else global_blender_path
             output_file = self.output_dir + '/tmp.blend'
@@ -72,4 +74,23 @@ class AvatarMainOutput(blender_node.ObjectOps):
         import global_bpy
         global_bpy.set_should_reset_scene(True)
 
-        return {"ui": {"gltfFilename": {filepath.replace(f"{self.output_dir}/", "")}, "SHAPE_FLOW": {SHAPE_FLOW}, "auto_save": {'true' if auto_save else 'false'},}}
+        outputs = {
+            "gltfFilename": [filepath.replace(f"{self.output_dir}/", "")],
+            "files": [{
+                "filename": filepath.replace(f"{self.output_dir}/", ""),
+                "content_type": "model/gltf+json",
+            },],
+            "SHAPE_FLOW": {SHAPE_FLOW}, 
+            "auto_save": {'true' if auto_save else 'false'}, 
+        }
+        if upload_to_cloud:
+            avatarId = upload_avatar_file(outputs)
+            return {
+                "ui": {
+                    **outputs,
+                    "avatarId": [avatarId],
+                },
+            }
+        return {
+            "ui": outputs
+        }

blender/blender_node.py

@@ -260,7 +260,8 @@ def create_primitive_shape_class(cls, path, name=None, name_prefix=''):
 
 
 def assign_and_return(BPY_OBJ, name, value):
-    BPY_OBJ[name] = value
+    setattr(BPY_OBJ, name, value)
+    # BPY_OBJ[name] = value
     # print(BPY_OBJ,name, BPY_OBJ[name])
     return None
 

blender/mesh_utils.py

@@ -1,6 +1,9 @@
 import atexit
 import subprocess
 import os
+import folder_paths
+import requests
+import json
 
 def genreate_mesh_from_texture(bpy, image):
     import torch
@@ -245,4 +248,39 @@ def export_gltf(output_dir, bpy_objects, filename, model_type, write_mode, metad
             os.replace(filepath, new_filepath)
             filepath = new_filepath
 
-    return filepath
+    return filepath
+
+def get_avatar_file(output):
+    avatar_filename = output["gltfFilename"][0]
+    with open(
+        f"{folder_paths.get_output_directory()}/{avatar_filename}", "rb"
+    ) as f:
+        return f.read()
+
+def upload_avatar_file(output):
+    file = get_avatar_file(output)
+    response = requests.get("https://labs.avatech.ai/api/share")
+    labData = response.json()
+    modelId = labData["modelId"]
+
+    # upload model
+    headers = {
+        "x-amz-acl": "public-read",
+        "Content-Type": "model/gltf-binary",
+        "Content-Length": str(len(file)),
+    }
+    requests.put(labData["url"], headers=headers, data=file)
+
+    # send notification
+    webhook_url = os.getenv("DISCORD_WEBHOOK_URL")
+    data = {
+        "username": "Avabot",
+        "avatar_url": "https://avatech-avatar-dev1.nyc3.cdn.digitaloceanspaces.com/avatechai.png",
+        "content": "[API Call] New register!",
+    }
+    headers = {
+        "Content-Type": "application/json",
+    }
+    response = requests.post(webhook_url, headers=headers, data=json.dumps(data))
+
+    return modelId

js/CombinePointsDialog.js

@@ -0,0 +1,137 @@
+import { combinePointsNode, samPrompts } from "./state.js";
+import { van } from "./van.js";
+const { div, dialog, form, button, h3, input, span } = van.tags;
+
+van.derive(() => {
+  if (
+    combinePointsNode.val != undefined &&
+    combinePointsNode.val.type === "Combine Points"
+  ) {
+    const inputNames =
+      combinePointsNode.val.inputs?.map((x) => x.name).slice(1) || [];
+    const record = Object.keys(samPrompts.val);
+
+    const missingDiff = record.filter((x) => !inputNames.includes(x));
+
+    if (missingDiff.length > 0) {
+      missingDiff.forEach((x) => {
+        combinePointsNode.val.addInput(x, "POINTS");
+      });
+      combinePointsNode.val.graph.change();
+    }
+  }
+});
+
+export function CombinePointsDialog() {
+  const showAddLayer = van.state(false);
+
+  return div(
+    {
+      class: () =>
+        "absolute z-[100] top-0 left-0 flex justify-center w-full h-full ",
+    },
+    () =>
+      dialog(
+        { id: "combine_points_dialog", class: "modal" },
+        div(
+          { class: "modal-box text-base-content" },
+          form(
+            {
+              class: "gap-2 flex flex-col",
+              method: "dialog",
+              onsubmit: (e) => {
+                e.preventDefault();
+                combine_points_dialog.close();
+              },
+            },
+            button(
+              {
+                type: "button",
+                class: "btn btn-sm btn-circle btn-ghost absolute right-2 top-2",
+                onclick: (e) => {
+                  e.stopPropagation();
+                  combine_points_dialog.close();
+                },
+              },
+              "✕"
+            ),
+            h3({ class: "font-bold text-lg text-base-content" }, "Edit points"),
+            () =>
+              div(
+                { class: "flex flex-col gap-2 mb-2" },
+                ...Object.keys(samPrompts.val).map((key) => {
+                  return span(key);
+                })
+              ),
+
+            () =>
+              showAddLayer.val
+                ? div(
+                    {
+                      class:
+                        "flex flex-row justify-center items-center border rounded-md pr-2",
+                    },
+                    input({
+                      type: "text",
+                      placeholder: "Type here",
+                      id: "layerName",
+                      class:
+                        "input input-ghost w-full focus:ring-0 focus:border-none focus:outline-none",
+                      autofocus: true,
+                    }),
+                    button(
+                      {
+                        onclick: (e) => {
+                          e.stopPropagation();
+                          e.preventDefault();
+                          showAddLayer.val = false;
+                        },
+                      },
+                      span({
+                        class: "iconify text-2xl",
+                        "data-icon": "iconoir:cancel",
+                      })
+                    ),
+                    button(
+                      {
+                        onclick: (e) => {
+                          e.stopPropagation();
+                          e.preventDefault();
+                          showAddLayer.val = false;
+                          const inputText =
+                            document.getElementById("layerName").value;
+                          samPrompts.val = {
+                            ...samPrompts.val,
+                            [inputText]: [],
+                          };
+                        },
+                      },
+                      span({
+                        class: "iconify text-2xl",
+                        "data-icon": "mdi:tick",
+                      })
+                    )
+                  )
+                : button(
+                    {
+                      class: "btn btn-outline btn",
+                      onclick: (e) => {
+                        e.stopPropagation();
+                        e.preventDefault();
+                        showAddLayer.val = true;
+                      },
+                    },
+                    "Add new layer"
+                  ),
+            button(
+              {
+                type: "submit",
+                class: "btn btn-sm  btn-ghost place-self-end",
+              },
+              "Confirm"
+            )
+          )
+        )
+      )
+  );
+}

js/Container.js

@@ -1,18 +1,20 @@
-import { LayerEditor } from './LayerEditor.js';
+import { LayerEditor } from "./LayerEditor.js";
-import { ShapeFlowEditor } from './ShapeFlowEditor.js';
+import { ShapeFlowEditor } from "./ShapeFlowEditor.js";
-import { van } from './van.js';
+import { van } from "./van.js";
-import { AvatarPreview } from './AvatarPreview.js';
+import { AvatarPreview } from "./AvatarPreview.js";
-import { Loading } from './Loading.js';
+import { Loading } from "./Loading.js";
-import { Alert } from './Alert.js';
+import { Alert } from "./Alert.js";
-import { AppHeader } from './AppHeader.js';
+import { AppHeader } from "./AppHeader.js";
+import { CombinePointsDialog } from "./CombinePointsDialog.js";
 const { button, iframe, div, img } = van.tags;
 
 export function Container() {
   return div(
     {
-      class: 'fixed left-0 top-0 w-full h-full z-[1000] pointer-events-none',
+      class: "fixed left-0 top-0 w-full h-full z-[1000] pointer-events-none",
-      id: 'avatech-editor',
+      id: "avatech-editor",
     },
+    CombinePointsDialog(),
     ShapeFlowEditor(),
     LayerEditor(),
     AvatarPreview(),

js/index.js

@@ -5,6 +5,7 @@ import {
   imageUrl,
   imagePrompts,
   targetNode,
+  combinePointsNode,
   fileName,
   embeddings,
   imagePromptsMulti,
@@ -389,6 +390,16 @@ const ext = {
           widget: btn,
         };
       },
+      COMBINE_POINTS(node, inputName, inputData, app) {
+        const btn = node.addWidget("button", "Edit points", "", () => {
+          console.log("Edit points");
+          combine_points_dialog.showModal();
+          combinePointsNode.val = node;
+        });
+        return {
+          widget: btn,
+        };
+      },
       BLENDSHAPES_CONFIG(node, inputName, inputData, app) {
         const btn = node.addWidget("button", "Edit Shape Flow", "", () => {
           targetNode.val = node;
@@ -675,6 +686,18 @@ const ext = {
         nodeData.input.required.sam = ["SAM_PROMPTS"];
         // nodeData.input.required.upload = ['IMAGEUPLOAD'];
         // nodeData.input.required.prompts_points = ["IMAGEUPLOAD"];
+        addMenuHandler(nodeType, function (_, options) {
+          options.unshift({
+            content: "Open In Points Editor (Local)",
+            callback: () => {
+              showMyImageEditor(this);
+            },
+          });
+        });
+        break;
+      case "Combine Points":
+        nodeData.input.required.sam = ["COMBINE_POINTS"];
+
         addMenuHandler(nodeType, function (_, options) {
           options.unshift({
             content: "Open In Points Editor (Local)",
@@ -746,11 +769,19 @@ function injectUIComponentToComfyuimenu() {
     if (!filename.toLowerCase().endsWith(".json")) {
       filename += ".json";
     }
-    app.graphToPrompt().then(p=>{
+    app.graphToPrompt().then((p) => {
-      console.log('fkfk');
       let json = JSON.stringify(p.output, null, 2); // convert the data to a JSON string
-      json = json.replace(/"seed": (\d+)/g, `"seed": "SEED"`).replace(/"image": "(?!.*mask.*\.png).*"/g, '"image": "reference_image_avatech"').replace(/"embedding_id": ".*"/g, '"embedding_id": "embedding_id_avatech"');
+      json = json
-      const blob = new Blob([json], {type: "application/json"});
+        .replace(/"seed": (\d+)/g, `"seed": "SEED"`)
+        .replace(
+          /"image": "(?!.*mask.*\.png).*"/g,
+          '"image": "reference_image_avatech"'
+        )
+        .replace(
+          /"embedding_id": ".*"/g,
+          '"embedding_id": "embedding_id_avatech"'
+        );
+      const blob = new Blob([json], { type: "application/json" });
       const url = URL.createObjectURL(blob);
       a.href = url;
       a.download = filename;

js/state.js

@@ -63,7 +63,6 @@ export const imagePrompts = van.state([]);
 
 export const allImagePrompts = van.state([{}]);
 
-
 /** @type {State<Record<string, Point[]>>} */
 export const imagePromptsMulti = van.state({});
 
@@ -76,3 +75,7 @@ export const targetNode = van.state();
 export const imageSize = van.state({ width: 0, height: 0, samScale: 0 });
 export const embeddings = van.state();
 export const embeddingID = van.state("Test");
+
+/** @type {State<LGraphNode>} */
+export const combinePointsNode = van.state();
+export const samPrompts = van.state({});

js/tw-styles.css

@@ -995,6 +995,64 @@ html{
     }
   }
 
+  .btn-outline:hover{
+    --tw-border-opacity: 1;
+    border-color: var(--fallback-bc,oklch(var(--bc)/var(--tw-border-opacity)));
+    --tw-bg-opacity: 1;
+    background-color: var(--fallback-bc,oklch(var(--bc)/var(--tw-bg-opacity)));
+    --tw-text-opacity: 1;
+    color: var(--fallback-b1,oklch(var(--b1)/var(--tw-text-opacity)));
+  }
+
+  .btn-outline.btn-primary:hover{
+    --tw-text-opacity: 1;
+    color: var(--fallback-pc,oklch(var(--pc)/var(--tw-text-opacity)));
+    background-color: color-mix(in oklab, var(--fallback-p,oklch(var(--p)/1)) 90%, black);
+    border-color: color-mix(in oklab, var(--fallback-p,oklch(var(--p)/1)) 90%, black);
+  }
+
+  .btn-outline.btn-secondary:hover{
+    --tw-text-opacity: 1;
+    color: var(--fallback-sc,oklch(var(--sc)/var(--tw-text-opacity)));
+    background-color: color-mix(in oklab, var(--fallback-s,oklch(var(--s)/1)) 90%, black);
+    border-color: color-mix(in oklab, var(--fallback-s,oklch(var(--s)/1)) 90%, black);
+  }
+
+  .btn-outline.btn-accent:hover{
+    --tw-text-opacity: 1;
+    color: var(--fallback-ac,oklch(var(--ac)/var(--tw-text-opacity)));
+    background-color: color-mix(in oklab, var(--fallback-a,oklch(var(--a)/1)) 90%, black);
+    border-color: color-mix(in oklab, var(--fallback-a,oklch(var(--a)/1)) 90%, black);
+  }
+
+  .btn-outline.btn-success:hover{
+    --tw-text-opacity: 1;
+    color: var(--fallback-suc,oklch(var(--suc)/var(--tw-text-opacity)));
+    background-color: color-mix(in oklab, var(--fallback-su,oklch(var(--su)/1)) 90%, black);
+    border-color: color-mix(in oklab, var(--fallback-su,oklch(var(--su)/1)) 90%, black);
+  }
+
+  .btn-outline.btn-info:hover{
+    --tw-text-opacity: 1;
+    color: var(--fallback-inc,oklch(var(--inc)/var(--tw-text-opacity)));
+    background-color: color-mix(in oklab, var(--fallback-in,oklch(var(--in)/1)) 90%, black);
+    border-color: color-mix(in oklab, var(--fallback-in,oklch(var(--in)/1)) 90%, black);
+  }
+
+  .btn-outline.btn-warning:hover{
+    --tw-text-opacity: 1;
+    color: var(--fallback-wac,oklch(var(--wac)/var(--tw-text-opacity)));
+    background-color: color-mix(in oklab, var(--fallback-wa,oklch(var(--wa)/1)) 90%, black);
+    border-color: color-mix(in oklab, var(--fallback-wa,oklch(var(--wa)/1)) 90%, black);
+  }
+
+  .btn-outline.btn-error:hover{
+    --tw-text-opacity: 1;
+    color: var(--fallback-erc,oklch(var(--erc)/var(--tw-text-opacity)));
+    background-color: color-mix(in oklab, var(--fallback-er,oklch(var(--er)/1)) 90%, black);
+    border-color: color-mix(in oklab, var(--fallback-er,oklch(var(--er)/1)) 90%, black);
+  }
+
   .btn-disabled:hover,
     .btn[disabled]:hover,
     .btn:disabled:hover{
@@ -1382,6 +1440,109 @@ html{
   background-color: var(--fallback-bc,oklch(var(--bc)/0.2));
 }
 
+.btn-outline{
+  border-color: currentColor;
+  background-color: transparent;
+  --tw-text-opacity: 1;
+  color: var(--fallback-bc,oklch(var(--bc)/var(--tw-text-opacity)));
+  --tw-shadow: 0 0 #0000;
+  --tw-shadow-colored: 0 0 #0000;
+  box-shadow: var(--tw-ring-offset-shadow, 0 0 #0000), var(--tw-ring-shadow, 0 0 #0000), var(--tw-shadow);
+}
+
+.btn-outline.btn-active{
+  --tw-border-opacity: 1;
+  border-color: var(--fallback-bc,oklch(var(--bc)/var(--tw-border-opacity)));
+  --tw-bg-opacity: 1;
+  background-color: var(--fallback-bc,oklch(var(--bc)/var(--tw-bg-opacity)));
+  --tw-text-opacity: 1;
+  color: var(--fallback-b1,oklch(var(--b1)/var(--tw-text-opacity)));
+}
+
+.btn-outline.btn-primary{
+  --tw-text-opacity: 1;
+  color: var(--fallback-p,oklch(var(--p)/var(--tw-text-opacity)));
+}
+
+.btn-outline.btn-primary.btn-active{
+  --tw-text-opacity: 1;
+  color: var(--fallback-pc,oklch(var(--pc)/var(--tw-text-opacity)));
+  background-color: color-mix(in oklab, var(--fallback-p,oklch(var(--p)/1)) 90%, black);
+  border-color: color-mix(in oklab, var(--fallback-p,oklch(var(--p)/1)) 90%, black);
+}
+
+.btn-outline.btn-secondary{
+  --tw-text-opacity: 1;
+  color: var(--fallback-s,oklch(var(--s)/var(--tw-text-opacity)));
+}
+
+.btn-outline.btn-secondary.btn-active{
+  --tw-text-opacity: 1;
+  color: var(--fallback-sc,oklch(var(--sc)/var(--tw-text-opacity)));
+  background-color: color-mix(in oklab, var(--fallback-s,oklch(var(--s)/1)) 90%, black);
+  border-color: color-mix(in oklab, var(--fallback-s,oklch(var(--s)/1)) 90%, black);
+}
+
+.btn-outline.btn-accent{
+  --tw-text-opacity: 1;
+  color: var(--fallback-a,oklch(var(--a)/var(--tw-text-opacity)));
+}
+
+.btn-outline.btn-accent.btn-active{
+  --tw-text-opacity: 1;
+  color: var(--fallback-ac,oklch(var(--ac)/var(--tw-text-opacity)));
+  background-color: color-mix(in oklab, var(--fallback-a,oklch(var(--a)/1)) 90%, black);
+  border-color: color-mix(in oklab, var(--fallback-a,oklch(var(--a)/1)) 90%, black);
+}
+
+.btn-outline.btn-success{
+  --tw-text-opacity: 1;
+  color: var(--fallback-su,oklch(var(--su)/var(--tw-text-opacity)));
+}
+
+.btn-outline.btn-success.btn-active{
+  --tw-text-opacity: 1;
+  color: var(--fallback-suc,oklch(var(--suc)/var(--tw-text-opacity)));
+  background-color: color-mix(in oklab, var(--fallback-su,oklch(var(--su)/1)) 90%, black);
+  border-color: color-mix(in oklab, var(--fallback-su,oklch(var(--su)/1)) 90%, black);
+}
+
+.btn-outline.btn-info{
+  --tw-text-opacity: 1;
+  color: var(--fallback-in,oklch(var(--in)/var(--tw-text-opacity)));
+}
+
+.btn-outline.btn-info.btn-active{
+  --tw-text-opacity: 1;
+  color: var(--fallback-inc,oklch(var(--inc)/var(--tw-text-opacity)));
+  background-color: color-mix(in oklab, var(--fallback-in,oklch(var(--in)/1)) 90%, black);
+  border-color: color-mix(in oklab, var(--fallback-in,oklch(var(--in)/1)) 90%, black);
+}
+
+.btn-outline.btn-warning{
+  --tw-text-opacity: 1;
+  color: var(--fallback-wa,oklch(var(--wa)/var(--tw-text-opacity)));
+}
+
+.btn-outline.btn-warning.btn-active{
+  --tw-text-opacity: 1;
+  color: var(--fallback-wac,oklch(var(--wac)/var(--tw-text-opacity)));
+  background-color: color-mix(in oklab, var(--fallback-wa,oklch(var(--wa)/1)) 90%, black);
+  border-color: color-mix(in oklab, var(--fallback-wa,oklch(var(--wa)/1)) 90%, black);
+}
+
+.btn-outline.btn-error{
+  --tw-text-opacity: 1;
+  color: var(--fallback-er,oklch(var(--er)/var(--tw-text-opacity)));
+}
+
+.btn-outline.btn-error.btn-active{
+  --tw-text-opacity: 1;
+  color: var(--fallback-erc,oklch(var(--erc)/var(--tw-text-opacity)));
+  background-color: color-mix(in oklab, var(--fallback-er,oklch(var(--er)/1)) 90%, black);
+  border-color: color-mix(in oklab, var(--fallback-er,oklch(var(--er)/1)) 90%, black);
+}
+
 .btn.btn-disabled,
   .btn[disabled],
   .btn:disabled{
@@ -1554,6 +1715,18 @@ details.collapse summary::-webkit-details-marker{
   outline-color: var(--fallback-bc,oklch(var(--bc)/0.2));
 }
 
+.input-ghost{
+  --tw-bg-opacity: 0.05;
+}
+
+.input-ghost:focus,
+    .input-ghost:focus-within{
+  --tw-bg-opacity: 1;
+  --tw-text-opacity: 1;
+  color: var(--fallback-bc,oklch(var(--bc)/var(--tw-text-opacity)));
+  box-shadow: none;
+}
+
 .input-disabled,
   .input:disabled,
   .input[disabled]{
@@ -2174,10 +2347,6 @@ details.collapse summary::-webkit-details-marker{
   left: 50%;
 }
 
-.left-28{
-  left: 7rem;
-}
-
 .left-4{
   left: 1rem;
 }
@@ -2268,10 +2437,6 @@ details.collapse summary::-webkit-details-marker{
   margin-top: 0.5rem;
 }
 
-.mt-4{
-  margin-top: 1rem;
-}
-
 .mt-8{
   margin-top: 2rem;
 }
@@ -2702,6 +2867,10 @@ details.collapse summary::-webkit-details-marker{
   padding-bottom: 0.5rem;
 }
 
+.pr-2{
+  padding-right: 0.5rem;
+}
+
 .text-start{
   text-align: start;
 }
@@ -3026,11 +3195,21 @@ img[src] {
   color: rgb(239 68 68 / var(--tw-text-opacity));
 }
 
+.focus\:border-none:focus{
+  border-style: none;
+}
+
 .focus\:outline-none:focus{
   outline: 2px solid transparent;
   outline-offset: 2px;
 }
 
+.focus\:ring-0:focus{
+  --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
+  --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(0px + var(--tw-ring-offset-width)) var(--tw-ring-color);
+  box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
+}
+
 @media (min-width: 640px){
   .sm\:flex{
     display: flex;

requirements.txt

@@ -3,7 +3,7 @@ numpy
 opencv-python
 opencv-contrib-python
 einops
-bpy
+bpy==3.6.0
 segment-anything
 tqdm
 python-dotenv

routes.py

@@ -2,6 +2,7 @@ from aiohttp import web
 from segment_anything import sam_model_registry, SamPredictor
 from PIL import Image, ImageOps
 from dotenv import load_dotenv
+from blender.mesh_utils import upload_avatar_file
 import os
 import requests
 import folder_paths
@@ -205,45 +206,6 @@ def post_prompt(json_data):
         return web.json_response({"error": "no prompt", "node_errors": []}, status=400)
 
 
-def get_avatar_file(outputs):
-    for node_id, output in outputs.items():
-        if "gltfFilename" in output:
-            avatar_filename = output["gltfFilename"][0]
-            with open(
-                f"{folder_paths.get_output_directory()}/{avatar_filename}", "rb"
-            ) as f:
-                return f.read()
-
-
-def upload_avatar_file(outputs):
-    file = get_avatar_file(outputs)
-    response = requests.get("https://labs.avatech.ai/api/share")
-    labData = response.json()
-    modelId = labData["modelId"]
-
-    # upload model
-    headers = {
-        "x-amz-acl": "public-read",
-        "Content-Type": "model/gltf-binary",
-        "Content-Length": str(len(file)),
-    }
-    requests.put(labData["url"], headers=headers, data=file)
-
-    # send notification
-    webhook_url = os.getenv("DISCORD_WEBHOOK_URL")
-    data = {
-        "username": "Avabot",
-        "avatar_url": "https://avatech-avatar-dev1.nyc3.cdn.digitaloceanspaces.com/avatechai.png",
-        "content": "[API Call] New register!",
-    }
-    headers = {
-        "Content-Type": "application/json",
-    }
-    response = requests.post(webhook_url, headers=headers, data=json.dumps(data))
-
-    return modelId
-
-
 def randomSeed(num_digits=15):
     range_start = 10 ** (num_digits - 1)
     range_end = (10**num_digits) - 1
@@ -292,7 +254,7 @@ async def post_prompt_block(request):
         if key.startswith("mask_"):
             mask_name = image_name + "_" + key.replace("mask_", "") + image_ext
             mask_path = save_image(value, save_name=mask_name)
-            workflow = workflow.replace(key, mask_path)
+            workflow = workflow.replace(f'"{key}"', f'"{mask_path}"')
 
     workflow = workflow.replace("embedding_id_avatech", image_path)
     workflow = workflow.replace("SEED", str(randomSeed()))
@@ -319,10 +281,12 @@ async def post_prompt_block(request):
         if history:
             # file = get_avatar_file(history[prompt_id]["outputs"])
             # return web.Response(body=file)
-
+            outputs = history[prompt_id]["outputs"]
-            modelId = upload_avatar_file(history[prompt_id]["outputs"])
+            for node_id, output in outputs.items():
-            print("model id", modelId)
+                if "gltfFilename" in output:
-            return web.json_response({"id": modelId}, status=200)
+                    modelId = upload_avatar_file(output)
+                    print("model id", modelId)
+                    return web.json_response({"id": modelId}, status=200)
         time.sleep(0.5)
 
 

sam/combine_points.py

@@ -0,0 +1,26 @@
+
+class CombinePoints:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+            },
+        }
+
+    RETURN_TYPES = ("SAM_PROMPTS",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "image"
+
+    # OUTPUT_NODE = True
+
+    def run(self, *args, **kwargs):
+        print("args", args)
+        print("kwargs", kwargs)
+        return ([])
+
+
+NODE_CLASS_MAPPINGS = {"Combine Points": CombinePoints}
+
+NODE_DISPLAY_NAME_MAPPINGS = {"Combine Points": "Combine Points"}

sam/extract_boundary_points.py

@@ -0,0 +1,66 @@
+import cv2
+import numpy as np
+import torch
+
+
+class ExtractBoundaryPoints:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "n_points": ("INT", {"default": -1, "min": -1, "max": 100}),
+            },
+        }
+
+    RETURN_TYPES = ("POINTS", "IMAGE")
+
+    FUNCTION = "run"
+
+    CATEGORY = "image"
+
+    def find_main_contour(self, image, n_points):
+        image = np.copy(image[0].numpy())
+        gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+        gray = (gray * 255).astype(np.uint8)
+        # Find contours
+        contours, _ = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+        if len(contours) == 0:
+            raise Exception(
+                "No contours found. Please ensure that the image has the correct segments (e.g. when you click on the mouth, it should display a proper blue area over the mouth region)."
+            )
+
+        # Get the largest contour
+        areas = [cv2.contourArea(contour) for contour in contours]
+
+        max_area_index = areas.index(max(areas))
+        largest_contour = contours[max_area_index]
+        if n_points > 0:
+            divided_by = int(largest_contour.shape[0] / n_points)
+            divided_by = min(divided_by, largest_contour.shape[0])
+            largest_contour = largest_contour[::divided_by].astype(int)
+        contours = [largest_contour]
+
+        if not image.flags["C_CONTIGUOUS"]:
+            image = np.ascontiguousarray(image)
+        cv2.drawContours(image, contours, -1, (0, 255, 0), 3)
+
+        points = []
+        for point in largest_contour:
+            points.append(
+                {"x": point[0][0], "y": point[0][1], "label": 1, "isAuto": True}
+            )
+
+        return image, points
+
+    def run(self, image, n_points):
+        contour_image, points = self.find_main_contour(image, n_points)
+        contour_image = torch.from_numpy(np.expand_dims(contour_image, axis=0))
+        print(points)
+        return (points, contour_image)
+
+
+NODE_CLASS_MAPPINGS = {"Extract Boundary Points": ExtractBoundaryPoints}
+
+NODE_DISPLAY_NAME_MAPPINGS = {"Extract Boundary Points": "Extract Boundary Points"}