fix EVF-SAMUltra node options

README.MD

@@ -1579,7 +1579,7 @@ Node Options:
 * image: The input image.
 * model: Select the model. Currently, there are options for evf-sam2 and evf sam.
 * presicion: Model accuracy can be selected from fp16, bf16, and fp32.
-* load_in_bit: Load the model with positional accuracy. You can choose from 16, 8, and 4.
+* load_in_bit: Load the model with positional accuracy. You can choose from full, 8, and 4.
 * pormpt: Prompt words used for segmentation.
 * detail_method: Edge processing methods. provides VITMatte, VITMatte(local), PyMatting, GuidedFilter. If the model has been downloaded after the first use of VITMatte, you can use VITMatte (local) afterwards.
 * detail_erode: Mask the erosion range inward from the edge. the larger the value, the larger the range of inward repair.

README_CN.MD

@@ -1557,7 +1557,7 @@ SegmentAnythingUltra的V2升级版，增加了VITMatte边缘处理方法。
 * image: 图片输入。
 * model: 选择模型。目前有 evf-sam2 和 evf-sam 可选。
 * presicion: 模型精度，可选择fp16, bf16 和 fp32。
-* load_in_bit: 按位精度加载模型。可选择16,8 和 4。
+* load_in_bit: 按位精度加载模型。可选择full, 8 和 4。
 * pormpt: 用于分割的提示词。
 * detail_method: 边缘处理方法。提供了VITMatte, VITMatte(local), PyMatting, GuidedFilter。如果首次使用VITMatte后模型已经下载，之后可以使用VITMatte(local)。
 * detail_erode: 遮罩边缘向内侵蚀范围。数值越大，向内修复的范围越大。

py/evf_sam_ultra.py

@@ -16,7 +16,7 @@ class EVF_SAM_Ultra:
     def INPUT_TYPES(cls):
         model_list = ["evf-sam2","evf-sam"]
         precision_list = ["fp16", "bf16", "fp32"]
-        load_in_bit_list = [16, 8, 4]
+        load_in_bit_list = ["full", "8", "4"]
         method_list = ['VITMatte', 'VITMatte(local)', 'PyMatting', 'GuidedFilter', ]
         device_list = ['cuda', 'cpu']
         return {"required":
@@ -62,6 +62,11 @@ class EVF_SAM_Ultra:
         else:
             model_type = 'effi'
 
+        if load_in_bit == 'full':
+            load_in_bit = 16
+        else:
+            load_in_bit = int(load_in_bit)
+
         model_path = ""
         model_folder_name = 'EVF-SAM'
         try:

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui_layerstyle"
 description = "A set of nodes for ComfyUI it generate image like Adobe Photoshop's Layer Style. the Drop Shadow is first completed node, and follow-up work is in progress."
-version = "1.0.30"
+version = "1.0.31"
 license = "MIT"
 dependencies = ["numpy", "pillow", "torch", "matplotlib", "Scipy", "scikit_image", "opencv-contrib-python", "pymatting", "segment_anything", "timm", "addict", "yapf", "colour-science", "wget", "mediapipe", "loguru", "typer_config", "fastapi", "rich", "google-generativeai", "diffusers", "omegaconf", "tqdm", "transformers", "kornia", "image-reward", "ultralytics", "blend_modes", "blind-watermark", "qrcode", "pyzbar", "transparent-background", "huggingface_hub", "accelerate", "torchscale", "wandb", "hydra-core", "psd-tools"]