auto save

img/py.py

-from PIL import Image,ImageSequence
+import turtle
+import random
+import numpy as np
+import torch
+import torch.nn as nn
+from PLT import Image
 
 
-img = Image.open("dive.gif")
-num = 0
-for i in ImageSequence.Iterator(img):
-    i.save(r"./img"+str(num)+".png")
-    num += 1
+class Painter(nn.Module):
+    """智能画笔神经网络"""
+    def __init__(self):
+        super().__init__()
+        self.fc = nn.Sequential(
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+            nn.Linear(4, 128),
+            nn.ReLU(),
+            nn.Linear(128, 64),
+            nn.Tanh(),
+            nn.Linear(64, 3)  # 输出: 笔压, 转向, 步长
+        )
+        
+    def forward(self, inputs):
+        return self.fc(inputs)
+
+class InkPaintingSystem:
+    def __init__(self):
+        self.screen = turtle.Screen()
+        self.screen.setup(800, 600)
+        self.screen.bgcolor("#F0EAD6")  # 宣纸底色
+        self.pen = turtle.Turtle()
+        self.pen.speed(0)
+        self.pen.width(2)
+        self.pen.color("#2F1B0A")  # 墨色
+        
+        # 初始化神经网络
+        self.painter = Painter()
+        self.optimizer = torch.optim.Adam(self.painter.parameters(), lr=0.001)
+        
+        # 风格参考图
+        self.style_img = self.load_style("style_sample.jpg")
+        
+        # 绘画参数
+        self.stroke_count = 0
+        self.max_strokes = 500
+        
+        # 启动绘画
+        self.paint()
+        turtle.done()
+    
+    def load_style(self, path):
+        """载入风格参考图"""
+        img = Image.open(path).convert('L').resize((64,64))
+        return torch.FloatTensor(np.array(img)/255.0)
+    
+    def get_state(self):
+        """获取当前状态特征"""
+        pos = self.pen.position()
+        angle = self.pen.heading()
+        return [
+            pos[0]/400,  # 归一化坐标
+            pos[1]/300,
+            angle/360,
+            self.stroke_count/self.max_strokes
+        ]
+    
+    def style_loss(self, generated):
+        """计算风格差异损失"""
+        gen_tensor = torch.FloatTensor(generated).unsqueeze(0)
+        return nn.MSELoss()(gen_tensor, self.style_img)
+    
+    def paint_stroke(self, action):
+        """执行绘画动作"""
+        pressure, angle_delta, length = action
+        self.pen.pensize(max(1, pressure*10))
+        
+        # 应用动作
+        self.pen.setheading(self.pen.heading() + angle_delta*180)
+        target = self.pen.position() + \
+                self.pen.heading().to_vector() * length*100
+        
+        # 水墨晕染效果
+        for _ in range(3):
+            self.pen.forward(length*20)
+            self.pen.pensize(self.pen.pensize()*0.9)
+        
+        self.pen.penup()
+        self.pen.goto(target)
+        self.pen.pendown()
+    
+    def paint(self):
+        """主绘画循环"""
+        while self.stroke_count < self.max_strokes:
+            state = torch.FloatTensor(self.get_state())
+            action = self.painter(state)  # 神经网络决策
+            
+            # 执行绘画动作
+            self.paint_stroke(action.detach().numpy())
+            
+            # 获取当前画布图像
+            canvas_img = self.get_canvas_image()
+            
+            # 计算并反向传播损失
+            loss = self.style_loss(canvas_img)
+            self.optimizer.zero_grad()
+            loss.backward()
+            self.optimizer.step()
+            
+            self.stroke_count += 1
+    
+    def get_canvas_image(self):
+        """获取当前画布图像"""
+        canvas = np.array(turtle.getcanvas().postscript()
+                        .split("\n")[3:], dtype=np.uint8)
+        return Image.fromarray(canvas).convert('L').resize((64,64))
+
+if __name__ == "__main__":
+    artist = InkPaintingSystem()
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