Create app.py

app.py

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+import os
+import cv2
+import torch  #2.0.1
+import numpy as np
+import gradio as gr
+import torch.nn as nn
+import random
+import string
+from imageAI import SimpleModel
+from myImage import ImageToCV,CVtoImage
+IMAGE_SIZE = 64
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = SimpleModel(path='best_model.pth').to(device)
+
+
+def predict_and_draw(input_image):
+    #input_image=ImageToCV(input_image)
+    
+    instructions = model.predict(input_image)
+    img = cv2.imread(input_image, cv2.IMREAD_GRAYSCALE)
+    img = cv2.resize(img, (IMAGE_SIZE, IMAGE_SIZE))
+    # 創建一個新的白色圖像
+    image = np.zeros((IMAGE_SIZE, IMAGE_SIZE), dtype=np.uint8)
+    
+    # 執行每條繪圖指令
+    for instruction in instructions:
+        try:exec(instruction)
+        except:
+            import traceback
+            traceback.print_exc()
+    #image=CVtoImage(image)
+    return img, image, "\n".join(instructions)
+
+
+iface = gr.Interface(
+    fn=predict_and_draw,
+    inputs=gr.Image(type="filepath"),
+    outputs=[  gr.Image(type="numpy" ,image_mode="L" ,label="Input Image"), gr.Image(type="numpy" ,image_mode="L" ,label="Output Image"), gr.Textbox(label="Generated Instructions")],
+    title="Image to Drawing Instructions",
+    description="Upload an image, and the model will predict drawing instructions based on it."
+)
+
+iface.launch()