tslgithub / image_class

基于keras集成多种图像分类模型: VGG16、VGG19、InceptionV3、Xception、MobileNet、AlexNet、LeNet、ZF_Net、ResNet18、ResNet34、ResNet50、ResNet_101、ResNet_152、DenseNet
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VGG16 #3

Open myFirstGitHubHAHAHA opened 5 years ago

myFirstGitHubHAHAHA commented 5 years ago

At first , thank you for providing a complete code. When i use the VGG16 model,I got this result I think it might be wrong. But why?

90/90 [======] - 34s - loss: 7.9056 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850om inf to 8.30082, saving model to ./checkpoints/VGG16/VGG16.h5 Epoch 2/300 90/90 [======] - 24s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850rove Epoch 3/300 90/90 [======] - 23s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850rove Epoch 4/300 90/90 [======] - 22s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850rove Epoch 5/300 89/90 [=====>.] - ETA: 0s - loss: 7.9866 - acc: 0.5045Epoch 00004: val_loss did not improve

90/90 [======] - 22s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850 Epoch 6/300 90/90 [======] - 21s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850rove Epoch 7/300 90/90 [======] - 21s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850rove Epoch 8/300 89/90 [====>.] - ETA: 0s - loss: 7.9685 - acc: 0.5056Epoch 00007: val_loss did not improve

90/90 [======] - 21s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850 Epoch 9/300 90/90 [======] - 21s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850rove Epoch 10/300 90/90 [======] - 21s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850rove Epoch 11/300 89/90 [====>.] - ETA: 0s - loss: 7.9866 - acc: 0.5045Epoch 00010: val_loss did not improve

90/90 [=====] - 21s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850 Epoch 12/300 90/90 [=====] - 20s - loss: 7.9785 - acc: 0.5050 - val_loss: 8.3008 - val_acc: 0.4850rove Epoch 00011: early stopping Done

tslgithub commented 5 years ago

Try ResNet

xiyangxia commented 2 years ago

Try ResNet

这个是因为啥?vgg,alexnet这些全是0.5左右,只有resnet系列的是正常的,其他的是错的吗,还是整个都不对