diff --git a/__init__.py b/__init__.py
index ebb910f..3564876 100644
--- a/__init__.py
+++ b/__init__.py
@@ -25,9 +25,12 @@ NODE_CLASS_MAPPINGS = {
     "abyz22_bypass":abyz22_bypass,
     "abyz22_smallhead":abyz22_smallhead,
     "abyz22_lamaPreprocessor":abyz22_lamaPreprocessor,
+    "abyz22_lamaInpaint":abyz22_lamaInpaint,
     "abyz22_makecircles":abyz22_makecircles,
     "abyz22_Topipe":abyz22_Topipe,
     "abyz22_Frompipe":abyz22_Frompipe,
+    "abyz22_Editpipe":abyz22_Editpipe,
+    "abyz22_Convertpipe":abyz22_Convertpipe,
 }
 
 # A dictionary that contains the friendly/humanly readable titles for the nodes
@@ -48,7 +51,10 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "abyz22_bypass":"abyz22_bypass",
     "abyz22_smallhead":"abyz22_smallhead",
     "abyz22_lamaPreprocessor":"abyz22_lamaPreprocessor",
+    "abyz22_lamaInpaint":"abyz22_lamaInpaint",
     "abyz22_makecircles":"abyz22_makecircles",
     "abyz22_Topipe":"abyz22_Topipe",
     "abyz22_Frompipe":"abyz22_Frompipe",
+    "abyz22_Editpipe":"abyz22_Editpipe",
+    "abyz22_Convertpipe":"abyz22_Convertpipe",
 }
diff --git a/annotator/lama/__init__.py b/annotator/lama/__init__.py
index 2e00b69..0b6cc6f 100644
--- a/annotator/lama/__init__.py
+++ b/annotator/lama/__init__.py
@@ -65,9 +65,9 @@ class LamaInpainting:
             image_feed = torch.cat([color, mask], dim=2)
 
             image_feed = rearrange(image_feed, 'h w c -> 1 c h w')
-            print('before : ',image_feed.shape)
+            # print('before : ',image_feed.shape)
             result = self.model(image_feed)[0]
-            print('after  : ', result.shape)
+            # print('after  : ', result.shape)
             result = rearrange(result, 'c h w -> h w c')
             result = result * mask + color * (1 - mask)
             result *= 255.0
diff --git a/imgs/sample.json b/imgs/sample.json
index 42eabc4..47f54a0 100644
--- a/imgs/sample.json
+++ b/imgs/sample.json
@@ -1,6 +1,6 @@
 {
-  "last_node_id": 851,
-  "last_link_id": 1354,
+  "last_node_id": 904,
+  "last_link_id": 1547,
   "nodes": [
     {
       "id": 3,
@@ -55,7 +55,7 @@
       "flags": {
         "collapsed": true
       },
-      "order": 244,
+      "order": 257,
       "mode": 2,
       "inputs": [
         {
@@ -131,7 +131,7 @@
         "1": 270
       },
       "flags": {},
-      "order": 313,
+      "order": 328,
       "mode": 2,
       "inputs": [
         {
@@ -156,7 +156,7 @@
         "1": 280
       },
       "flags": {},
-      "order": 265,
+      "order": 274,
       "mode": 2,
       "inputs": [
         {
@@ -183,7 +183,7 @@
         "1": 26
       },
       "flags": {},
-      "order": 242,
+      "order": 255,
       "mode": 2,
       "inputs": [
         {
@@ -221,7 +221,7 @@
         "1": 280
       },
       "flags": {},
-      "order": 262,
+      "order": 271,
       "mode": 2,
       "inputs": [
         {
@@ -236,32 +236,6 @@
       "color": "#232",
       "bgcolor": "#353"
     },
-    {
-      "id": 17,
-      "type": "PreviewImage",
-      "pos": [
-        2550,
-        2450
-      ],
-      "size": {
-        "0": 330,
-        "1": 270
-      },
-      "flags": {},
-      "order": 143,
-      "mode": 2,
-      "inputs": [
-        {
-          "name": "images",
-          "type": "IMAGE",
-          "link": 21,
-          "slot_index": 0
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "PreviewImage"
-      }
-    },
     {
       "id": 18,
       "type": "ImageListToImageBatch",
@@ -276,7 +250,7 @@
       "flags": {
         "collapsed": true
       },
-      "order": 266,
+      "order": 275,
       "mode": 2,
       "inputs": [
         {
@@ -314,7 +288,7 @@
         "1": 30
       },
       "flags": {},
-      "order": 231,
+      "order": 243,
       "mode": 2,
       "inputs": [
         {
@@ -354,7 +328,7 @@
       "flags": {
         "collapsed": false
       },
-      "order": 263,
+      "order": 272,
       "mode": 2,
       "inputs": [
         {
@@ -392,7 +366,7 @@
         "1": 100
       },
       "flags": {},
-      "order": 175,
+      "order": 183,
       "mode": 2,
       "inputs": [
         {
@@ -475,13 +449,13 @@
         "1": 200
       },
       "flags": {},
-      "order": 145,
+      "order": 153,
       "mode": 2,
       "inputs": [
         {
           "name": "image",
           "type": "IMAGE",
-          "link": 38
+          "link": 1463
         }
       ],
       "outputs": [
@@ -525,7 +499,7 @@
         "1": 310
       },
       "flags": {},
-      "order": 233,
+      "order": 241,
       "mode": 2,
       "inputs": [
         {
@@ -617,125 +591,6 @@
       "color": "#223",
       "bgcolor": "#335"
     },
-    {
-      "id": 43,
-      "type": "KSampler (Efficient)",
-      "pos": [
-        1959.482417285754,
-        1188.9997427200396
-      ],
-      "size": {
-        "0": 220,
-        "1": 350
-      },
-      "flags": {},
-      "order": 211,
-      "mode": 2,
-      "inputs": [
-        {
-          "name": "model",
-          "type": "MODEL",
-          "link": 155
-        },
-        {
-          "name": "positive",
-          "type": "CONDITIONING",
-          "link": 44,
-          "slot_index": 1
-        },
-        {
-          "name": "negative",
-          "type": "CONDITIONING",
-          "link": 45,
-          "slot_index": 2
-        },
-        {
-          "name": "latent_image",
-          "type": "LATENT",
-          "link": 46
-        },
-        {
-          "name": "optional_vae",
-          "type": "VAE",
-          "link": 47,
-          "slot_index": 4
-        },
-        {
-          "name": "script",
-          "type": "SCRIPT",
-          "link": null
-        }
-      ],
-      "outputs": [
-        {
-          "name": "MODEL",
-          "type": "MODEL",
-          "links": [],
-          "shape": 3,
-          "slot_index": 0
-        },
-        {
-          "name": "CONDITIONING+",
-          "type": "CONDITIONING",
-          "links": [],
-          "shape": 3,
-          "slot_index": 1
-        },
-        {
-          "name": "CONDITIONING-",
-          "type": "CONDITIONING",
-          "links": [
-            55
-          ],
-          "shape": 3,
-          "slot_index": 2
-        },
-        {
-          "name": "LATENT",
-          "type": "LATENT",
-          "links": [],
-          "shape": 3,
-          "slot_index": 3
-        },
-        {
-          "name": "VAE",
-          "type": "VAE",
-          "links": [
-            56
-          ],
-          "shape": 3,
-          "slot_index": 4
-        },
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            48,
-            51,
-            116
-          ],
-          "shape": 3,
-          "slot_index": 5
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "KSampler (Efficient)"
-      },
-      "widgets_values": [
-        3731842397,
-        null,
-        30,
-        7,
-        "dpmpp_2m",
-        "karras",
-        1,
-        "none",
-        "true"
-      ],
-      "color": "#332922",
-      "bgcolor": "#593930",
-      "shape": 2
-    },
     {
       "id": 44,
       "type": "PreviewImage",
@@ -748,7 +603,7 @@
         "1": 270
       },
       "flags": {},
-      "order": 221,
+      "order": 229,
       "mode": 2,
       "inputs": [
         {
@@ -775,7 +630,7 @@
       "flags": {
         "collapsed": true
       },
-      "order": 268,
+      "order": 270,
       "mode": 2,
       "inputs": [
         {
@@ -812,7 +667,7 @@
         "1": 270
       },
       "flags": {},
-      "order": 304,
+      "order": 314,
       "mode": 2,
       "inputs": [
         {
@@ -839,7 +694,7 @@
       "flags": {
         "collapsed": true
       },
-      "order": 222,
+      "order": 230,
       "mode": 2,
       "inputs": [
         {
@@ -953,7 +808,7 @@
       "flags": {
         "collapsed": false
       },
-      "order": 315,
+      "order": 326,
       "mode": 2,
       "inputs": [
         {
@@ -978,7 +833,7 @@
         "1": 30
       },
       "flags": {},
-      "order": 245,
+      "order": 253,
       "mode": 2,
       "inputs": [
         {
@@ -1014,7 +869,7 @@
         "1": 280
       },
       "flags": {},
-      "order": 287,
+      "order": 295,
       "mode": 2,
       "inputs": [
         {
@@ -1039,7 +894,7 @@
         "1": 26
       },
       "flags": {},
-      "order": 267,
+      "order": 269,
       "mode": 2,
       "inputs": [
         {
@@ -1075,7 +930,7 @@
         "1": 280
       },
       "flags": {},
-      "order": 286,
+      "order": 294,
       "mode": 2,
       "inputs": [
         {
@@ -1088,32 +943,6 @@
         "Node name for S&R": "PreviewImage"
       }
     },
-    {
-      "id": 56,
-      "type": "PreviewImage",
-      "pos": [
-        2529.4824172857584,
-        1258.9997427200396
-      ],
-      "size": {
-        "0": 330,
-        "1": 270
-      },
-      "flags": {},
-      "order": 147,
-      "mode": 2,
-      "inputs": [
-        {
-          "name": "images",
-          "type": "IMAGE",
-          "link": 64,
-          "slot_index": 0
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "PreviewImage"
-      }
-    },
     {
       "id": 59,
       "type": "ControlNetApply",
@@ -1126,7 +955,7 @@
         "1": 100
       },
       "flags": {},
-      "order": 201,
+      "order": 211,
       "mode": 2,
       "inputs": [
         {
@@ -1177,13 +1006,13 @@
       "flags": {
         "collapsed": false
       },
-      "order": 148,
+      "order": 147,
       "mode": 2,
       "inputs": [
         {
           "name": "image",
           "type": "IMAGE",
-          "link": 69
+          "link": 1445
         }
       ],
       "outputs": [
@@ -1251,7 +1080,7 @@
         "1": 100
       },
       "flags": {},
-      "order": 191,
+      "order": 199,
       "mode": 2,
       "inputs": [
         {
@@ -1288,56 +1117,6 @@
         1.25
       ]
     },
-    {
-      "id": 67,
-      "type": "DWPreprocessor",
-      "pos": [
-        1339.482417285755,
-        998.9997427200401
-      ],
-      "size": {
-        "0": 370,
-        "1": 200
-      },
-      "flags": {},
-      "order": 149,
-      "mode": 2,
-      "inputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "link": 74
-        }
-      ],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            73
-          ],
-          "shape": 3,
-          "slot_index": 0
-        },
-        {
-          "name": "POSE_KEYPOINT",
-          "type": "POSE_KEYPOINT",
-          "links": null,
-          "shape": 3
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "DWPreprocessor"
-      },
-      "widgets_values": [
-        "disable",
-        "enable",
-        "disable",
-        512,
-        "yolo_nas_s_fp16.onnx",
-        "dw-ll_ucoco_384_bs5.torchscript.pt"
-      ]
-    },
     {
       "id": 77,
       "type": "ImpactSimpleDetectorSEGS",
@@ -1350,7 +1129,7 @@
         "1": 310
       },
       "flags": {},
-      "order": 172,
+      "order": 187,
       "mode": 2,
       "inputs": [
         {
@@ -1403,45 +1182,6 @@
       "color": "#223",
       "bgcolor": "#335"
     },
-    {
-      "id": 78,
-      "type": "SAMLoader",
-      "pos": [
-        1289.5522760526515,
-        3389.753084595001
-      ],
-      "size": {
-        "0": 280,
-        "1": 82
-      },
-      "flags": {
-        "pinned": false,
-        "collapsed": false
-      },
-      "order": 7,
-      "mode": 2,
-      "outputs": [
-        {
-          "name": "SAM_MODEL",
-          "type": "SAM_MODEL",
-          "links": [
-            82,
-            97
-          ],
-          "shape": 3,
-          "slot_index": 0
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "SAMLoader"
-      },
-      "widgets_values": [
-        "sam_vit_b_01ec64.pth",
-        "AUTO"
-      ],
-      "color": "#223",
-      "bgcolor": "#335"
-    },
     {
       "id": 79,
       "type": "ImpactImageBatchToImageList",
@@ -1456,13 +1196,13 @@
       "flags": {
         "collapsed": true
       },
-      "order": 139,
+      "order": 162,
       "mode": 2,
       "inputs": [
         {
           "name": "image",
           "type": "IMAGE",
-          "link": 84
+          "link": 1514
         }
       ],
       "outputs": [
@@ -1498,7 +1238,7 @@
         "collapsed": true,
         "pinned": false
       },
-      "order": 8,
+      "order": 7,
       "mode": 2,
       "outputs": [
         {
@@ -1532,7 +1272,7 @@
         "1": 30
       },
       "flags": {},
-      "order": 188,
+      "order": 202,
       "mode": 2,
       "inputs": [
         {
@@ -1570,7 +1310,7 @@
       "flags": {
         "pinned": false
       },
-      "order": 9,
+      "order": 8,
       "mode": 2,
       "outputs": [
         {
@@ -1611,7 +1351,7 @@
         "1": 46
       },
       "flags": {},
-      "order": 199,
+      "order": 214,
       "mode": 2,
       "inputs": [
         {
@@ -1652,7 +1392,7 @@
         "1": 30
       },
       "flags": {},
-      "order": 189,
+      "order": 203,
       "mode": 2,
       "inputs": [
         {
@@ -1688,7 +1428,7 @@
         "1": 26
       },
       "flags": {},
-      "order": 208,
+      "order": 224,
       "mode": 2,
       "inputs": [
         {
@@ -1713,127 +1453,6 @@
         "Node name for S&R": "MaskToImage"
       }
     },
-    {
-      "id": 4,
-      "type": "KSampler (Efficient)",
-      "pos": [
-        1990,
-        2380
-      ],
-      "size": {
-        "0": 220,
-        "1": 350
-      },
-      "flags": {},
-      "order": 200,
-      "mode": 2,
-      "inputs": [
-        {
-          "name": "model",
-          "type": "MODEL",
-          "link": 4
-        },
-        {
-          "name": "positive",
-          "type": "CONDITIONING",
-          "link": 5,
-          "slot_index": 1
-        },
-        {
-          "name": "negative",
-          "type": "CONDITIONING",
-          "link": 6,
-          "slot_index": 2
-        },
-        {
-          "name": "latent_image",
-          "type": "LATENT",
-          "link": 7
-        },
-        {
-          "name": "optional_vae",
-          "type": "VAE",
-          "link": 8,
-          "slot_index": 4
-        },
-        {
-          "name": "script",
-          "type": "SCRIPT",
-          "link": null
-        }
-      ],
-      "outputs": [
-        {
-          "name": "MODEL",
-          "type": "MODEL",
-          "links": [
-            136
-          ],
-          "shape": 3,
-          "slot_index": 0
-        },
-        {
-          "name": "CONDITIONING+",
-          "type": "CONDITIONING",
-          "links": [],
-          "shape": 3,
-          "slot_index": 1
-        },
-        {
-          "name": "CONDITIONING-",
-          "type": "CONDITIONING",
-          "links": [
-            138
-          ],
-          "shape": 3,
-          "slot_index": 2
-        },
-        {
-          "name": "LATENT",
-          "type": "LATENT",
-          "links": [],
-          "shape": 3,
-          "slot_index": 3
-        },
-        {
-          "name": "VAE",
-          "type": "VAE",
-          "links": [
-            139
-          ],
-          "shape": 3,
-          "slot_index": 4
-        },
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            9,
-            12,
-            120
-          ],
-          "shape": 3,
-          "slot_index": 5
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "KSampler (Efficient)"
-      },
-      "widgets_values": [
-        3731842397,
-        null,
-        30,
-        7,
-        "dpmpp_2m",
-        "karras",
-        1,
-        "none",
-        "true"
-      ],
-      "color": "#332922",
-      "bgcolor": "#593930",
-      "shape": 2
-    },
     {
       "id": 29,
       "type": "PreviewImage",
@@ -1846,7 +1465,7 @@
         "1": 250
       },
       "flags": {},
-      "order": 301,
+      "order": 317,
       "mode": 2,
       "inputs": [
         {
@@ -1871,7 +1490,7 @@
         "1": 150
       },
       "flags": {},
-      "order": 294,
+      "order": 308,
       "mode": 2,
       "inputs": [
         {
@@ -1924,7 +1543,7 @@
       "flags": {
         "collapsed": false
       },
-      "order": 10,
+      "order": 9,
       "mode": 2,
       "outputs": [
         {
@@ -1958,13 +1577,13 @@
       "flags": {
         "collapsed": false
       },
-      "order": 144,
+      "order": 152,
       "mode": 2,
       "inputs": [
         {
           "name": "image",
           "type": "IMAGE",
-          "link": 26
+          "link": 1461
         }
       ],
       "outputs": [
@@ -1998,13 +1617,13 @@
         "1": 50
       },
       "flags": {},
-      "order": 174,
+      "order": 182,
       "mode": 2,
       "inputs": [
         {
           "name": "conditioning_to",
           "type": "CONDITIONING",
-          "link": 145
+          "link": 1466
         },
         {
           "name": "conditioning_from",
@@ -2039,13 +1658,13 @@
         "1": 50
       },
       "flags": {},
-      "order": 176,
+      "order": 181,
       "mode": 2,
       "inputs": [
         {
           "name": "conditioning_to",
           "type": "CONDITIONING",
-          "link": 157
+          "link": 1447
         },
         {
           "name": "conditioning_from",
@@ -2069,31 +1688,6 @@
         "Node name for S&R": "ConditioningConcat"
       }
     },
-    {
-      "id": 5,
-      "type": "PreviewImage",
-      "pos": [
-        2220,
-        2450
-      ],
-      "size": {
-        "0": 330,
-        "1": 270
-      },
-      "flags": {},
-      "order": 209,
-      "mode": 2,
-      "inputs": [
-        {
-          "name": "images",
-          "type": "IMAGE",
-          "link": 9
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "PreviewImage"
-      }
-    },
     {
       "id": 26,
       "type": "MaskToImage",
@@ -2108,7 +1702,7 @@
       "flags": {
         "collapsed": false
       },
-      "order": 243,
+      "order": 256,
       "mode": 2,
       "inputs": [
         {
@@ -2149,7 +1743,7 @@
       "flags": {
         "collapsed": true
       },
-      "order": 210,
+      "order": 221,
       "mode": 2,
       "inputs": [
         {
@@ -2188,7 +1782,7 @@
         "1": 310
       },
       "flags": {},
-      "order": 220,
+      "order": 232,
       "mode": 2,
       "inputs": [
         {
@@ -2254,7 +1848,7 @@
         "1": 310
       },
       "flags": {},
-      "order": 219,
+      "order": 231,
       "mode": 2,
       "inputs": [
         {
@@ -2322,7 +1916,7 @@
       "flags": {
         "pinned": false
       },
-      "order": 11,
+      "order": 10,
       "mode": 2,
       "outputs": [
         {
@@ -2363,7 +1957,7 @@
         "1": 100
       },
       "flags": {},
-      "order": 190,
+      "order": 200,
       "mode": 2,
       "inputs": [
         {
@@ -2412,7 +2006,7 @@
         "1": 310
       },
       "flags": {},
-      "order": 226,
+      "order": 233,
       "mode": 2,
       "inputs": [
         {
@@ -2466,152 +2060,6 @@
       "color": "#223",
       "bgcolor": "#335"
     },
-    {
-      "id": 129,
-      "type": "KSampler (Efficient)",
-      "pos": [
-        5317.434676070521,
-        2383.827726146227
-      ],
-      "size": {
-        "0": 220,
-        "1": 350
-      },
-      "flags": {},
-      "order": 205,
-      "mode": 2,
-      "inputs": [
-        {
-          "name": "model",
-          "type": "MODEL",
-          "link": 188
-        },
-        {
-          "name": "positive",
-          "type": "CONDITIONING",
-          "link": 189,
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+      4,
+      167,
+      0,
+      "*"
+    ],
+    [
+      1501,
+      900,
+      5,
+      163,
+      0,
+      "*"
+    ],
+    [
+      1503,
+      900,
+      6,
+      155,
+      0,
+      "*"
+    ],
+    [
+      1504,
+      900,
+      7,
+      156,
+      0,
+      "*"
+    ],
+    [
+      1505,
+      160,
+      0,
+      129,
+      0,
+      "MODEL"
+    ],
+    [
+      1506,
+      155,
+      0,
+      165,
+      0,
+      "IMAGE"
+    ],
+    [
+      1507,
+      603,
+      0,
+      652,
+      0,
+      "IMAGE"
+    ],
+    [
+      1508,
+      902,
+      6,
+      603,
+      0,
+      "*"
+    ],
+    [
+      1509,
+      619,
+      0,
+      653,
+      0,
+      "CLIP"
+    ],
+    [
+      1510,
+      603,
+      0,
+      648,
+      0,
+      "IMAGE"
+    ],
+    [
+      1511,
+      604,
+      0,
+      645,
+      0,
+      "MODEL"
+    ],
+    [
+      1513,
+      603,
+      0,
+      596,
+      0,
+      "IMAGE"
+    ],
+    [
+      1514,
+      86,
+      0,
+      79,
+      0,
+      "IMAGE"
+    ],
+    [
+      1515,
+      671,
+      0,
+      903,
+      0,
+      "PIPE"
+    ],
+    [
+      1516,
+      903,
+      6,
+      215,
+      0,
+      "*"
+    ],
+    [
+      1517,
+      903,
+      4,
+      679,
+      0,
+      "*"
+    ],
+    [
+      1518,
+      903,
+      5,
+      214,
+      0,
+      "*"
+    ],
+    [
+      1519,
+      679,
+      0,
+      188,
+      0,
+      "CONDITIONING"
+    ],
+    [
+      1520,
+      679,
+      0,
+      193,
+      0,
+      "CONDITIONING"
+    ],
+    [
+      1521,
+      215,
+      0,
+      180,
+      0,
+      "IMAGE"
+    ],
+    [
+      1522,
+      215,
+      0,
+      184,
+      0,
+      "IMAGE"
+    ],
+    [
+      1523,
+      671,
+      0,
+      904,
+      0,
+      "PIPE"
+    ],
+    [
+      1524,
+      904,
+      1,
+      478,
+      0,
+      "*"
+    ],
+    [
+      1525,
+      904,
+      2,
+      479,
+      0,
+      "*"
+    ],
+    [
+      1526,
+      904,
+      3,
+      480,
+      0,
+      "*"
+    ],
+    [
+      1527,
+      904,
+      4,
+      485,
+      0,
+      "*"
+    ],
+    [
+      1528,
+      904,
+      5,
+      481,
+      0,
+      "*"
+    ],
+    [
+      1531,
+      473,
+      0,
+      466,
+      0,
+      "IMAGE"
+    ],
+    [
+      1533,
+      478,
+      0,
+      449,
+      0,
+      "MODEL"
+    ],
+    [
+      1534,
+      474,
+      0,
+      449,
+      3,
+      "LATENT"
+    ],
+    [
+      1535,
+      904,
+      6,
+      473,
+      0,
+      "*"
+    ],
+    [
+      1536,
+      904,
+      7,
+      474,
+      0,
+      "*"
+    ],
+    [
+      1537,
+      172,
+      0,
+      120,
+      0,
+      "IMAGE"
+    ],
+    [
+      1538,
+      228,
+      0,
+      121,
+      0,
+      "MODEL"
+    ],
+    [
+      1539,
+      174,
+      0,
+      120,
+      2,
+      "VAE"
+    ],
+    [
+      1540,
+      173,
+      0,
+      120,
+      1,
+      "CONDITIONING"
+    ],
+    [
+      1541,
+      229,
+      0,
+      121,
+      2,
+      "CONDITIONING"
+    ],
+    [
+      1542,
+      120,
+      0,
+      123,
+      0,
+      "IMAGE"
+    ],
+    [
+      1543,
+      121,
+      5,
+      122,
+      0,
+      "IMAGE"
+    ],
+    [
+      1544,
+      565,
+      0,
+      559,
+      0,
+      "MODEL"
+    ],
+    [
+      1545,
+      574,
+      0,
+      557,
+      2,
+      "IMAGE"
+    ],
+    [
+      1546,
+      564,
+      0,
+      559,
+      4,
+      "VAE"
+    ],
+    [
+      1547,
+      172,
+      0,
+      176,
+      0,
+      "IMAGE"
     ]
   ],
   "groups": [
@@ -17947,10 +18816,10 @@
     {
       "title": "Outpainting (lama)",
       "bounding": [
-        1048,
-        -427,
-        2021,
-        484
+        1057,
+        -392,
+        2030,
+        453
       ],
       "color": "#a1309b",
       "font_size": 24,
@@ -17967,6 +18836,18 @@
       "color": "#8A8",
       "font_size": 24,
       "locked": false
+    },
+    {
+      "title": "Inpaint with LaMa",
+      "bounding": [
+        1060,
+        -869,
+        1650,
+        470
+      ],
+      "color": "#88A",
+      "font_size": 24,
+      "locked": false
     }
   ],
   "config": {},
diff --git a/imgs/sample.png b/imgs/sample.png
index 0c411d6..76e859a 100644
Binary files a/imgs/sample.png and b/imgs/sample.png differ
diff --git a/lowrise.py b/lowrise.py
index e6f902b..bad74e9 100644
--- a/lowrise.py
+++ b/lowrise.py
@@ -21,7 +21,7 @@ from PIL import ImageDraw
 
 #     CATEGORY = "abyz22"
 
-#     def run(sefl,*args,**kwargs):
+#     def run(self,*args,**kwargs):
 #         return None
 
 
diff --git a/outpainting_lama.py b/outpainting_lama.py
index 191a5d1..1983aa3 100644
--- a/outpainting_lama.py
+++ b/outpainting_lama.py
@@ -14,6 +14,7 @@ from PIL import Image
 from numpy import dtype
 from scipy import ndimage
 from torch import device
+import nodes
 
 # Get the absolute path of various directories
 my_dir = os.path.dirname(os.path.abspath(__file__))
@@ -358,18 +359,18 @@ class abyz22_lamaPreprocessor:
     ):  # pixel= 1,768,512,3
         # 모드 설정
         # print("☆★ " * 20)
-        
-        if Width==0 and Height==0:
+
+        if Width == 0 and Height == 0:
             encoded_image = self._encode_image(vae, pixels.to("cuda" if torch.cuda.is_available() else "cpu"))
             encoded_image_dict = {"samples": encoded_image.cpu()}
             mask_with_1 = torch.ones_like(pixels[:, :, :, 0])
             encoded_image_dict = SetLatentNoiseMask().set_mask(encoded_image_dict, mask_with_1)[0]
-            return (pixels.to("cuda" if torch.cuda.is_available() else "cpu"),encoded_image_dict)
-        
+            return (pixels.to("cuda" if torch.cuda.is_available() else "cpu"), encoded_image_dict)
+
         np.random.seed(seed)
         random.seed(seed)
         model_lama = LamaInpainting()
-        image,imgs, masks = None, None,None
+        image, imgs, masks = None, None, None
         if Width_Ratio_min > Width_Ratio_max:
             Width_Ratio_min, Width_Ratio_max = Width_Ratio_max, Width_Ratio_min
         if Height_Ratio_min > Height_Ratio_max:
@@ -382,7 +383,7 @@ class abyz22_lamaPreprocessor:
             Down, Right = int(Height - Up), int(Width - Left)
 
             copy_img = pixels.clone()[i, :, :, :]
-            final_img_with_alpha = copy_img*255.0
+            final_img_with_alpha = copy_img * 255.0
             if Up + Down > 0:
                 image = torch.rand((pixels.shape[1] + Up + Down, pixels.shape[2], pixels.shape[3]))
                 image[Up : Up + pixels.shape[1], :, :] = copy_img
@@ -480,3 +481,88 @@ class abyz22_lamaPreprocessor:
     )
     FUNCTION = "preprocess"
     CATEGORY = "abyz22"
+
+
+class abyz22_lamaInpaint:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "pixels": ("IMAGE",),  # N,H,W,C
+                "vae": ("VAE",),
+            },
+            "optional": {
+                "mask": ("MASK",),  #  N,H,W
+                "mask_(img)": ("IMAGE",),
+            },
+        }
+
+    RETURN_TYPES = (
+        "IMAGE",
+        "LATENT",
+        "IMAGE",
+    )
+    RETURN_NAMES = (
+        "LaMa Preprocessed Image",
+        "LaMa Preprocessed Latent",
+        "LaMa Image",
+    )
+    FUNCTION = "preprocess"
+    CATEGORY = "abyz22"
+    FUNCTION = "run"
+
+    def _encode_image(self, vae, image):
+        # encoder = VAEEncode()
+        wrapper = VAEWrapper(vae)
+        image = image[:, :, :, 0:3]
+        image_without_alpha = image.to(wrapper.vae.vae_dtype) * 2.0 - 1.0
+        image = image_without_alpha.permute(0, 3, 1, 2)
+        # image = rearrange(image_without_alpha, "1 w h c -> 1 c w h")
+        encoded_image = wrapper.encode_first_stage_(image)
+        if torch.all(torch.isnan(encoded_image.mean())):
+            print("All values produced are NANs, automatically upcasting dtype to float32")
+            wrapper.to(torch.float32)
+            encoded_image = wrapper.encode_first_stage_(image)
+        vae_output = wrapper.get_first_stage_encoding_(encoded_image)
+        return vae_output
+
+    def run(self, *args, **kwargs):
+        pixels, vae = kwargs["pixels"], kwargs["vae"]
+        if kwargs.get("mask") is not None:
+            mask = kwargs.get("mask")
+        elif kwargs.get("mask_(img)") is not None:
+            # print(len(kwargs.get("mask_(img)")))
+            # print(kwargs.get("mask_(img)")[0].shape)
+            mask = kwargs.get("mask_(img)")[0][:, :, :, 0]
+        else:
+            mask = torch.zeros_like(pixels)[:, :, :, 0]
+        print("mask shape : ", mask.shape, mask.min(), mask.max())
+        # 이미지 크기/값 lama에 맞추기 (0.0~1.0 -> 0~255)
+        for i in range(pixels.shape[0]):
+            image_with_alpha = (torch.cat([pixels[i], mask[i].unsqueeze(-1)], -1).numpy() * 255).astype(np.uint8)  # 알파채널 합침
+
+            model_lama = LamaInpainting()
+            final_img = model_lama(image_with_alpha)
+            final_img = torch.from_numpy(final_img) / 255.0
+            print(final_img.shape)
+            final_img = torchvision.transforms.Resize((final_img.shape[0:2]))(final_img.permute(2, 0, 1)).permute(1, 2, 0)
+        final_img = final_img.unsqueeze(0)
+        lama_image=final_img.clone().to("cuda" if torch.cuda.is_available() else "cpu")
+        encoded_image = self._encode_image(vae, final_img.to("cuda" if torch.cuda.is_available() else "cpu"))
+        encoded_image_dict = {"samples": encoded_image.cpu()}
+        # mask = torch.ones_like(pixels[:, :, :, 0])
+        latent = SetLatentNoiseMask().set_mask(encoded_image_dict, mask)[0]
+
+        latent = nodes.VAEEncode().encode(vae, final_img)[0]
+        # latent = nodes.VAEEncodeForInpaint().encode(vae, final_img, mask, grow_mask_by=6)[0]
+
+        print('before concat : ',final_img.shape,mask.unsqueeze(-1).shape)
+        final_img = torch.cat([final_img, mask.unsqueeze(-1)], -1)
+        print(final_img.shape, final_img.min(), final_img.max())
+        c = final_img[:, :, :, 0:3]
+        m = final_img[:, :, :, 3:4]
+        m = (m > 0.5).float()
+        final_img = c * (1 - m) - m
+        print(final_img.shape, final_img.min(), final_img.max())
+
+        return (final_img.to("cuda" if torch.cuda.is_available() else "cpu"), latent,lama_image)
diff --git a/outpainting_node.py b/outpainting_node.py
index 6107b69..759d58e 100644
--- a/outpainting_node.py
+++ b/outpainting_node.py
@@ -79,7 +79,7 @@ class abyz22_Pad_Image:
         pose_image = obj.estimate_pose(
             image, "disable", "enable", "disable", resolution=resolution, bbox_detector="yolox_s.onnx", pose_estimator="dw-ss_ucoco.onnx"
         )["result"][0]
-        padded_image,padded_pose_image=None,None
+        padded_image, padded_pose_image = None, None
 
         # Resize_by = random.uniform(Ratio_min, Ratio_max)
         for i, Resize_by in enumerate(Resize_bys):
@@ -93,7 +93,7 @@ class abyz22_Pad_Image:
             # resized_image = 3,768,512
             dx, dy = abs(image.shape[2] - resized_image.shape[2]), abs(image.shape[1] - resized_image.shape[1])
             rdx, rdy = random.randint(0, dx), random.randint(0, dy)
-            if Resize_by < 1:
+            if Resize_by <= 1:
                 mode_list = {
                     "Top-Left": (0, dx, 0, dy),
                     "Top": (int(round(dx / 2)), int(round(dx / 2)) + 1, 0, dy),
@@ -162,7 +162,7 @@ class abyz22_Pad_Image:
                 final_image = padded_image
                 final_pose_image = padded_pose_image
             else:
-                final_image = torch.cat((final_image, padded_image))
+                final_image = torch.cat((final_image, padded_image))  # TODO 여기서 문제 발생? expected Tensor as element 0 in argument 0, but got NoneType
                 final_pose_image = torch.cat((final_pose_image, padded_pose_image))
 
         latent = nodes.VAEEncode().encode(vae, final_image)[0]
diff --git a/utils.py b/utils.py
index 573c57a..bfd435c 100644
--- a/utils.py
+++ b/utils.py
@@ -39,15 +39,15 @@ class abyz22_Topipe:
     CATEGORY = "abyz22"
 
     def run(sefl, *args, **kwargs):
-        pipe={}
-        pipe['MODEL']=kwargs.get('MODEL')
-        pipe['CLIP']=kwargs.get('CLIP')
-        pipe['VAE']=kwargs.get('VAE')
-        pipe['POSITIVE']=kwargs.get('Positive')
-        pipe['NEGATIVE']=kwargs.get('Negative')
-        pipe['IMAGE']=kwargs.get('IMAGE')
-        pipe['latent_image']=kwargs.get('latent_Image')
-        pipe['latent']=kwargs.get('latent')
+        pipe = {}
+        pipe["MODEL"] = kwargs.get("MODEL")
+        pipe["CLIP"] = kwargs.get("CLIP")
+        pipe["VAE"] = kwargs.get("VAE")
+        pipe["POSITIVE"] = kwargs.get("Positive")
+        pipe["NEGATIVE"] = kwargs.get("Negative")
+        pipe["IMAGE"] = kwargs.get("IMAGE")
+        pipe["latent_image"] = kwargs.get("latent_Image")
+        pipe["latent"] = kwargs.get("latent")
         return (pipe,)
 
 
@@ -62,6 +62,7 @@ class abyz22_Frompipe:
         }
 
     RETURN_TYPES = (
+        "PIPE",
         "MODEL",
         "CLIP",
         "VAE",
@@ -72,6 +73,7 @@ class abyz22_Frompipe:
         "LATENT",
     )
     RETURN_NAMES = (
+        "pipe",
         "MODEL",
         "CLIP",
         "VAE",
@@ -96,7 +98,86 @@ class abyz22_Frompipe:
         image = pipe.get("IMAGE")
         latent_image = pipe.get("latent_image")
         latent = pipe.get("latent")
-        return (model, clip, vae, positive, negative, image, latent_image, latent,)
+        return (pipe, model, clip, vae, positive, negative, image, latent_image, latent)
+
+
+class abyz22_Editpipe:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "pipe": ("PIPE",),
+            },
+            "optional": {
+                "MODEL": ("MODEL",),
+                "CLIP": ("CLIP",),
+                "VAE": ("VAE",),
+                "Positive": ("CONDITIONING",),
+                "Negative": ("CONDITIONING",),
+                "IMAGE": ("IMAGE",),
+                "latent_Image": ("LATENT",),
+                "latent": ("LATENT",),
+            },
+        }
+
+    RETURN_TYPES = ("PIPE",)
+    RETURN_NAMES = ("pipe",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "abyz22"
+
+    def run(sefl, *args, **kwargs):
+        pipe = kwargs["pipe"]
+        if kwargs.get("MODEL") is not None:
+            pipe["MODEL"] = kwargs["MODEL"]
+        if kwargs.get("CLIP") is not None:
+            pipe["CLIP"] = kwargs["CLIP"]
+        if kwargs.get("VAE") is not None:
+            pipe["VAE"] = kwargs["VAE"]
+        if kwargs.get("Positive") is not None:
+            pipe["POSITIVE"] = kwargs["Positive"]
+        if kwargs.get("Negative") is not None:
+            pipe["NEGATIVE"] = kwargs["Negative"]
+        if kwargs.get("IMAGE") is not None:
+            pipe["IMAGE"] = kwargs["IMAGE"]
+        if kwargs.get("latent_Image") is not None:
+            pipe["latent_image"] = kwargs["latent_Image"]
+
+        return (pipe,)
+
+class abyz22_Convertpipe:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "pipe": ("PIPE",),
+            },
+        }
+
+    RETURN_TYPES = ("BASIC_PIPE",)
+    RETURN_NAMES = ("basic_pipe",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "abyz22"
+
+    def run(sefl, *args, **kwargs):
+        pipe = kwargs["pipe"]
+        model=pipe['MODEL']
+        clip=pipe['CLIP']
+        vae=pipe['VAE']
+        positive=pipe['POSITIVE']
+        negative=pipe['NEGATIVE']
+
+        basic_pipe=(model,clip,vae,positive,negative)
+        return (basic_pipe,)
 
 
 def tensor_convert_rgba(image, prefer_copy=True):