在使用 matplotlib 在其上绘制一个框后，如何保存从 tfrecord 解码的图像？

Question

img = tf.image.decode_jpeg(camera_image)
plt.imshow(img, cmap=cmap)
title = camera_name
plt.title(title)
plt.show()
plt.savefig('image.png')

plt.savefig() 不起作用。保存的图片是空白的。

但是 plt.show() 清楚地显示了一张带有边界框的图像

Answer 1

这是一个示例，其中我从 VGG16 模型的第 1 层块中保存特征图。稍后我加载相同的图像并绘制它。

我正在使用 plt.savefig() 保存图像，稍后使用 load_img() 加载同一图像并绘制它。您必须在 plt.show() 之前调用 plt.savefig()。

代码-

# plot feature map of first conv layer for given image
from keras.applications.vgg16 import VGG16
from keras.applications.vgg16 import preprocess_input
from keras.preprocessing.image import load_img
from keras.preprocessing.image import img_to_array
from keras.models import Model
from matplotlib import pyplot
from numpy import expand_dims

# load the model
model = VGG16()

# redefine model to output right after the first hidden layer
model = Model(inputs=model.inputs, outputs=model.layers[1].output)
model.summary()

# load the image with the required shape
img = load_img('bird.jpg', target_size=(224, 224))

# convert the image to an array
img = img_to_array(img)

# expand dimensions so that it represents a single 'sample'
img = expand_dims(img, axis=0)

# prepare the image (e.g. scale pixel values for the vgg)
img = preprocess_input(img)

# get feature map for first hidden layer
feature_maps = model.predict(img)

# plot all 64 maps in an 8x8 squares
square = 8
ix = 1
for _ in range(square):
    for _ in range(square):
        # specify subplot and turn of axis
        ax = pyplot.subplot(square, square, ix)
        ax.set_xticks([])
        ax.set_yticks([])
        # plot filter channel in grayscale
        pyplot.imshow(feature_maps[0, :, :, ix-1], cmap='gray')
        ix += 1

# save the figure
pyplot.savefig("Bird_Layer1")

# load the saved figure
img = load_img('Bird_Layer1.png')

# print the loaded figure
pyplot.show(img)

输出-

Model: "model_17"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_17 (InputLayer)        (None, 224, 224, 3)       0         
_________________________________________________________________
block1_conv1 (Conv2D)        (None, 224, 224, 64)      1792      
=================================================================
Total params: 1,792
Trainable params: 1,792
Non-trainable params: 0
_________________________________________________________________

希望这能回答您的问题。快乐学习。

在使用 matplotlib 在其上绘制一个框后，如何保存从 tfrecord 解码的图像？

How do I save my image which is decoded from tfrecord after plotting a box on it using matplotlib?

python

matplotlib

deep-learning

tensorflow2.0