update
This commit is contained in:
Meeeyo
@@ -127,7 +127,11 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"GenericImageLoader": "全能加载图像🐠meeeyo.com",
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"GenericImageLoader": "全能加载图像🐠meeeyo.com",
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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"ImageAdjuster": "重置图像🐠meeeyo.com",
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"CustomCrop": "裁剪图像🐠meeeyo.com",
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"SaveImagEX": "保存图像🐠meeeyo.com",
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@@ -3,6 +3,11 @@ import os, re,io, base64, csv, torch
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import shutil, requests, chardet, pathlib
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import openpyxl, folder_paths, node_helpers
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import os, re,io, base64, csv, torch
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import shutil, requests, chardet, pathlib
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import openpyxl, folder_paths, node_helpers
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=======
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import os
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import re
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import csv
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@@ -15,6 +20,7 @@ import openpyxl
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import folder_paths
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import node_helpers
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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import numpy as np
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from PIL import Image, ImageOps, ImageSequence
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from pathlib import Path
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@@ -24,6 +30,9 @@ from io import BytesIO
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from . import AnyType, any_typ
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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@@ -33,7 +42,11 @@ class GenericImageLoader:
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def INPUT_TYPES(cls):
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return {
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"required": {
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"image_input": ("STRING", {"default": ""}),
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=======
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"path_or_input": ("STRING", {"default": ""}),
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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}
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}
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RETURN_TYPES = ("IMAGE", "MASK")
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@@ -45,8 +58,13 @@ class GenericImageLoader:
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def IS_CHANGED():
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return float("NaN")
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def load_image(self, image_input):
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path = image_input.strip()
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=======
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def load_image(self, path_or_input):
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path = path_or_input.strip()
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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for ctrl in ['\u202a', '\u202b', '\u202c', '\u202d', '\u202e']:
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while path.startswith(ctrl):
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path = path.lstrip(ctrl)
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@@ -86,8 +104,11 @@ class GenericImageLoader:
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return img_tensor, mask_tensor
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=======
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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#======加载重置图像
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class LoadAndAdjustImage:
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@@ -256,22 +277,28 @@ class ImageAdjuster:
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def IS_CHANGED(self):
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return float("NaN")
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=======
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=======
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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def process_image(self, image, mask, max_dimension=1024, size_option="Custom"):
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batch_size = image.shape[0]
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processed_images = []
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processed_masks = []
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def process_image(self, image, max_dimension=1024, size_option="Custom"):
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batch_size = image.shape[0]
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processed_images = []
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>>>>>>> db71d026f74322a6e66276701198bfe8b5d44ad8
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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widths = []
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heights = []
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@@ -280,18 +307,24 @@ class ImageAdjuster:
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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current_mask = mask[i]
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input_pil_image = Image.fromarray((current_image.numpy() * 255).astype(np.uint8))
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input_pil_mask = Image.fromarray((current_mask.numpy() * 255).astype(np.uint8))
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input_pil_image = Image.fromarray((current_image.numpy() * 255).astype(np.uint8))
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>>>>>>> db71d026f74322a6e66276701198bfe8b5d44ad8
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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W, H = input_pil_image.size
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processed_image_pil = input_pil_image.copy()
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@@ -306,9 +339,15 @@ class ImageAdjuster:
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processed_mask_pil = input_pil_mask.copy()
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processed_mask_pil = ImageOps.exif_transpose(processed_mask_pil)
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processed_mask_pil = input_pil_mask.copy()
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processed_mask_pil = ImageOps.exif_transpose(processed_mask_pil)
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>>>>>>> db71d026f74322a6e66276701198bfe8b5d44ad8
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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if processed_image_pil.mode == 'P':
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processed_image_pil = processed_image_pil.convert("RGBA")
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elif 'A' in processed_image_pil.getbands():
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@@ -323,8 +362,14 @@ class ImageAdjuster:
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if processed_mask_pil.mode != "L":
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processed_mask_pil = processed_mask_pil.convert("L")
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if processed_mask_pil.mode != "L":
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processed_mask_pil = processed_mask_pil.convert("L")
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=======
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>>>>>>> db71d026f74322a6e66276701198bfe8b5d44ad8
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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if size_option != "Custom":
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aspect_ratio = W / H
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@@ -365,8 +410,13 @@ class ImageAdjuster:
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processed_mask_pil = ImageOps.fit(processed_mask_pil, (target_width, target_height), method=Image.Resampling.BILINEAR, centering=(0.5, 0.5))
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processed_mask_pil = ImageOps.fit(processed_mask_pil, (target_width, target_height), method=Image.Resampling.BILINEAR, centering=(0.5, 0.5))
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>>>>>>> db71d026f74322a6e66276701198bfe8b5d44ad8
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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else:
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ratio = min(max_dimension / W, max_dimension / H)
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adjusted_width = round(W * ratio)
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@@ -382,26 +432,37 @@ class ImageAdjuster:
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processed_mask_pil = processed_mask_pil.resize((adjusted_width, adjusted_height), Image.Resampling.BILINEAR)
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processed_mask_pil = processed_mask_pil.resize((adjusted_width, adjusted_height), Image.Resampling.BILINEAR)
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=======
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>>>>>>> db71d026f74322a6e66276701198bfe8b5d44ad8
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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processed_image = np.array(processed_image_pil).astype(np.float32) / 255.0
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processed_image = torch.from_numpy(processed_image)
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processed_images.append(processed_image)
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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processed_mask = np.array(processed_mask_pil).astype(np.float32) / 255.0
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processed_mask = torch.from_numpy(processed_mask)
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processed_masks.append(processed_mask)
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>>>>>>> db71d026f74322a6e66276701198bfe8b5d44ad8
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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if size_option != "Custom":
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widths.append(target_width)
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heights.append(target_height)
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@@ -413,7 +474,10 @@ class ImageAdjuster:
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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output_mask = torch.stack(processed_masks)
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if all(w == widths[0] for w in widths) and all(h == heights[0] for h in heights):
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@@ -422,6 +486,8 @@ class ImageAdjuster:
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return (output_image, output_mask, widths[0], heights[0])
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if all(w == widths[0] for w in widths) and all(h == heights[0] for h in heights):
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@@ -430,6 +496,7 @@ class ImageAdjuster:
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return (output_image, widths[0], heights[0])
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>>>>>>> db71d026f74322a6e66276701198bfe8b5d44ad8
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>>>>>>> 79ed250c5d0d1f11fccbec9087431ff25fc1e810
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>>>>>>> f14d0c29f81a549b32997f82e610ad71cdb4404c
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def _resize_to_million_pixels(self, W, H):
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aspect_ratio = W / H
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