Question

您的帖子似乎主要是代码；请添加更多详细信息。我正在尝试训练模型，但出现错误“无法导入pydot。请安装pydot。例如，安装pip install pydot。”并且我已经安装了pydot和graphviz，

from keras.utils import print_summary
print_summary(model, line_length=None, positions=None, print_fn=None)

# add some visualization
from IPython.display import SVG
from keras.utils.vis_utils import model_to_dot
SVG(model_to_dot(model).create(prog='dot', format='svg'))



# train the network
print("training network...")
sys.stdout.flush()
#class_mode ='categorical', # 2D one-hot encoded labels
H = model.fit_generator(aug.flow(Xtrain, trainY, batch_size=BS), \
    validation_data=(Xval, valY), \
    steps_per_epoch=len(trainX) // BS, \
    epochs=EPOCHS, verbose=1)

# save the model to disk
print("Saving model to disk")
sys.stdout.flush()
model.save("/tmp/mymodel")


# set the matplotlib backend so figures can be saved in the background
# plot the training loss and accuracy
print("Generating plots...")
sys.stdout.flush()
matplotlib.use("Agg")
matplotlib.pyplot.style.use("ggplot")
matplotlib.pyplot.figure()
N = EPOCHS
matplotlib.pyplot.plot(np.arange(0, N), H.history["loss"], label="train_loss")
matplotlib.pyplot.plot(np.arange(0, N), H.history["val_loss"], label="val_loss")
matplotlib.pyplot.plot(np.arange(0, N), H.history["acc"], label="train_acc")
matplotlib.pyplot.plot(np.arange(0, N), H.history["val_acc"], label="val_acc")
matplotlib.pyplot.title("Training Loss and Accuracy on diabetic retinopathy detection")
matplotlib.pyplot.xlabel("Epoch #")
matplotlib.pyplot.ylabel("Loss/Accuracy")
matplotlib.pyplot.legend(loc="lower left")
matplotlib.pyplot.savefig("plot.png")

Answer 1

我认为您正在使用python 3。

在这种情况下，请确保您使用pip3为python 3安装了依赖项，而不是为python 2（使用pip）安装了依赖项。

pip3 install pydot

ImportError：无法导入`pydot`

1 个答案: