更新模型调用

gui/predict.py

@@ -1,6 +1,6 @@
 import torch
 from torchvision import transforms
-from model import CNNClassifier
+from model import CustomCNN
 from PIL import Image
 from io import BytesIO
 
@@ -9,7 +9,7 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 # 加载预训练模型
 model_path = './shotrdp.pth'
-model = CNNClassifier(len(class_labels))
+model = CustomCNN(len(class_labels))
 model.load_state_dict(torch.load(model_path, weights_only=True))
 model.to(device)
 
@@ -34,13 +34,13 @@ def solve(image_bytes):
     return _result
 
 
-# if __name__ == '__main__':
+if __name__ == '__main__':
-#     image_path = './screen/0.png'
+    image_path = './screen/0.png'
-#
+
-#     image = Image.open(image_path).convert('RGB')
+    image = Image.open(image_path).convert('RGB')
-#     image = transform(image).unsqueeze(0).to(device)
+    image = transform(image).unsqueeze(0).to(device)
-#
+
-#     output = model(image)
+    output = model(image)
-#     _, predicted = torch.max(output.data, 1)
+    _, predicted = torch.max(output.data, 1)
-#
+
-#     print(f"File name: {image_path}, Predicted result: {class_labels[predicted.item()]}, Output: {output.data}")
+    print(f"File name: {image_path}, Predicted result: {class_labels[predicted.item()]}, Output: {output.data}")