commit RandomGenerator node, fix TextJoin input to force

2024-08-30 20:09:57 +08:00
parent 53aa0b25db
commit b01c5ef6fb
5 changed files with 118 additions and 5 deletions
@@ -104,6 +104,7 @@ When this error has occurred, please check the network environment.
 ## Update
 <font size="4">**If the dependency package error after updating,  please double clicking ```repair_dependency.bat``` (for Official ComfyUI Protable) or  ```repair_dependency_aki.bat``` (for ComfyUI-aki-v1.x) in the plugin folder to reinstall the dependency packages. </font><br />    

+* Commit [RandomGenerator](#RandomGenerator) node, Used to generate random numbers within a specified range, with outputs of int, float, and boolean, supporting batch generation of different random numbers by image batch.
 * Commit [EVF-SAMUltra](#EVFSAMUltra) node, it is implementation of [EVF-SAM](https://github.com/hustvl/EVF-SAM) in ComfyUI. Please download model files from [BaiduNetdisk](https://pan.baidu.com/s/1EvaxgKcCxUpMbYKzLnEx9w?pwd=69bn) or [huggingface/EVF-SAM2](https://huggingface.co/YxZhang/evf-sam2/tree/main), [huggingface/EVF-SAM](https://huggingface.co/YxZhang/evf-sam/tree/main) to ```ComfyUI/models/EVF-SAM``` folder(save the models in their respective subdirectories).
 Due to the introduction of new dependencies package, after the plugin upgrade, please reinstall the dependency packages.
 * Commit [ImageTaggerSave](#ImageTaggerSave) and [ImageAutoCropV3](#ImageAutoCropV3) nodes. Used to implement the automatic trimming and marking workflow for the training set (the workflow ```image_tagger_save.json``` is located in the workflow directory).
@@ -1278,6 +1279,23 @@ Output a floating-point value with a precision of 5 decimal places.
 ![image](image/boolean_node.jpg)    
 Output a boolean value.

+### <a id="table1">RandomGenerator</a>
+Used to generate random value within a specified range, with outputs of int, float, and boolean. Supports batch and list generation, and supports batch generation of a set of different random number lists based on image batch.
+![image](image/random_generator_example.jpg)    
+
+Node Options:
+![image](image/random_generator_node.jpg)  
+* image: Optional input, generate a list of random numbers that match the quantity in batches according to the image.
+* min_value: Minimum value. Random numbers will randomly take values from the minimum to the maximum.
+* max_value: Maximum value. Random numbers will randomly take values from the minimum to the maximum.
+* float_decimal_places: Precision of float value.
+* fix_seed:Is the random number seed fixed. If this option is fixed, the generated random number will always be the same.
+
+Outputs:
+int: Integer random number.
+float: Float random number.
+bool: Boolean random number.
+
 ### <a id="table1">NumberCalculator</a>
 ![image](image/number_calculator_node.jpg)    
 Performs mathematical operations on two numeric values and outputs integer and floating point results<sup>*</sup>. Supported operations include```+```, ```-```, ```*```, ```/```, ```**```, ```//```, ```%```.
@@ -105,6 +105,7 @@ git clone https://github.com/chflame163/ComfyUI_LayerStyle.git
 ## 更新说明
 <font size="4">**如果本插件更新后出现依赖包错误，请双击运行插件目录下的```install_requirements.bat```(官方便携包)，或 ```install_requirements_aki.bat```(秋叶整合包) 重新安装依赖包。

+* 添加 [RandomGenerator](#RandomGenerator) 节点，用于生成指定范围内的随机数，有int，float，bool输出，支持按图片批量生成不同的随机数。
 * 添加 [EVF-SAMUltra](#EVFSAMUltra) 节点，是[EVF-SAM](https://github.com/hustvl/EVF-SAM)在ComfyUI中的实现。请从[百度网盘](https://pan.baidu.com/s/1EvaxgKcCxUpMbYKzLnEx9w?pwd=69bn) 或者 [huggingface/EVF-SAM2](https://huggingface.co/YxZhang/evf-sam2/tree/main), [huggingface/EVF-SAM](https://huggingface.co/YxZhang/evf-sam/tree/main) 下载全部模型文件并复制到```ComfyUI/models/EVF-SAM```文件夹(请将模型保存在各自子目录中)。
 由于引入了新的依赖，插件升级后请重新安装依赖包。
 * 添加 [ImageTaggerSave](#ImageTaggerSave) 和 [ImageAutoCropV3](#ImageAutoCropV3) 节点，用于实现训练集自动裁切打标工作流(工作流```image_tagger_save_example.json```在workflow目录中)。
@@ -1259,6 +1260,23 @@ box_preview: 裁切位置预览。
 ![image](image/boolean_node.jpg)    
 输出一个布尔值。

+### <a id="table1">RandomGenerator</a>
+用于生成指定范围内的随机数，有int，float，bool输出，支持批量和列表，支持按图片批量生成一组不同的随机数列表。
+![image](image/random_generator_example.jpg)    
+
+节点选项说明:
+![image](image/random_generator_node.jpg)  
+* image: 可选输入，按照图片批量生成数量相符的随机数列表。
+* min_value：最小值。随机数将从最小值到最大值之间随机取值。
+* max_value：最大值。随机数将从最小值到最大值之间随机取值。
+* float_decimal_places：浮点数精度。
+* fix_seed:是否固定随机数种子。如果此选项固定，生成的随机数将始终相同。
+
+输出:
+int: 整数随机数。
+float: 浮点数随机数。
+bool: 布尔随机数。
+
 ### <a id="table1">NumberCalculator</a>
 ![image](image/number_calculator_node.jpg)    
 对两个数值进行数学运算并输出整数和浮点数结果<sup>*</sup>。支持的运算包括```+```、```-```、```*```、```/```、```**```、```//```、```%```。
@@ -0,0 +1,77 @@
+from .imagefunc import AnyType
+import random
+
+NODE_NAME = 'RandomGenerator'
+
+
+class LSRandomGenerator:
+
+    def __init__(self):
+        self.previous_seeds= set({})
+        self.fixed_seed = 0
+        pass
+
+    @classmethod
+    def INPUT_TYPES(self):
+
+        return {
+            "required": {
+                "min_value": ("FLOAT", {"default": 0, "min": -1.0e14, "max": 1.0e14, "step": 0.01}),
+                "max_value": ("FLOAT", {"default": 10, "min": -1.0e14, "max": 1.0e14, "step": 0.01}),
+                "float_decimal_places": ("INT", {"default": 1, "min": 1, "max": 14, "step": 1}),
+                "fix_seed": ("BOOLEAN", {"default": False}),
+            },
+            "optional": {
+                "image": ("IMAGE", ),
+            }
+        }
+
+    RETURN_TYPES = ("INT", "FLOAT", "BOOLEAN",)
+    RETURN_NAMES = ("int", "float", "bool",)
+    FUNCTION = 'random_generator'
+    CATEGORY = '😺dzNodes/LayerUtility/Data'
+
+    def random_generator(self, min_value, max_value, float_decimal_places, fix_seed, image=None):
+        batch_size = 1
+        if image is not None:
+            batch_size = image.shape[0]
+        ret_nunbers = []
+        for i in range(batch_size):
+            new_seed = self.generate_unique_seed()
+            if fix_seed:
+                if self.fixed_seed == 0:
+                    self.fixed_seed = new_seed
+                seed = self.fixed_seed
+            else:
+                seed = new_seed
+            random.seed(seed)
+            factor = random.uniform(3, 9)
+            random_float = random.uniform(min_value, max_value) / factor
+            random_float = round(random_float * factor, float_decimal_places)
+            random_int = int(random_float)
+            random_bool = random_int %2 == 0
+            ret_nunbers.append((random_int, random_float, random_bool))
+
+        if len(ret_nunbers) > 1:
+            ret_ints = [item[0] for item in ret_nunbers]
+            ret_floats = [item[1] for item in ret_nunbers]
+            ret_bools = [item[2] for item in ret_nunbers]
+            return (ret_ints, ret_floats, ret_bools)
+        else:
+            return (ret_nunbers[0][0], ret_nunbers[0][1], ret_nunbers[0][2])
+
+    def generate_unique_seed(self) -> int:
+        while True:
+            new_number = random.randint(0, 1e14)
+            if new_number not in self.previous_seeds:
+                self.previous_seeds.add(new_number)
+                return new_number
+
+
+NODE_CLASS_MAPPINGS = {
+    "LayerUtility: RandomGenerator": LSRandomGenerator
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "LayerUtility: RandomGenerator": "LayerUtility: Random Generator"
+}
@@ -11,13 +11,13 @@ class TextJoin:
    def INPUT_TYPES(cls):
        return {
            "required": {
-                "text_1": ("STRING", {"multiline": False}),
+                "text_1": ("STRING", {"multiline": False,"forceInput":True}),

            },
            "optional": {
-                "text_2": ("STRING", {"multiline": False}),
-                "text_3": ("STRING", {"multiline": False}),
-                "text_4": ("STRING", {"multiline": False}),
+                "text_2": ("STRING", {"multiline": False,"forceInput":True}),
+                "text_3": ("STRING", {"multiline": False,"forceInput":True}),
+                "text_4": ("STRING", {"multiline": False,"forceInput":True}),
            }
        }

@@ -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 = "1.0.37"
+version = "1.0.38"
 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", "bitsandbytes", "torchscale", "wandb", "hydra-core", "psd-tools"]