调试错误:UnicodeDecodeError: 'utf-8' codec can't decode byte 0xff in position 0: invalid start byte
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2024-02-22 11:42:34
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代码:
#-*-coding:utf-8-*-
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
filepath = '/media/wzg16/DATA2/Datasets/data/test_data/cat.jpg'
def distort_color(image,color_ordering=0):
if color_ordering ==0:
image = tf.image.random_brightness(image,max_delta=32./255.)
image = tf.image.random_saturation(image,lower=0.5,upper=1.5)
image = tf.image.random_hue(image,max_delta=0.2)
image = tf.image.random_contrast(image,lower=0.5,upper=1.5)
elif color_ordering ==1:
image = tf.image.random_saturation(image, lower=0.5, upper=1.5)
image = tf.image.random_brightness(image, max_delta=32. / 255.)
image = tf.image.random_contrast(image, lower=0.5, upper=1.5)
image = tf.image.random_hue(image, max_delta=0.2)
elif color_ordering ==2:
image = tf.image.random_hue(image, max_delta=0.2)
image = tf.image.random_brightness(image, max_delta=32. / 255.)
image = tf.image.random_saturation(image, lower=0.5, upper=1.5)
image = tf.image.random_contrast(image, lower=0.5, upper=1.5)
else:
image = tf.image.random_contrast(image, lower=0.5, upper=1.5)
image = tf.image.random_brightness(image, max_delta=32. / 255.)
image = tf.image.random_saturation(image, lower=0.5, upper=1.5)
image = tf.image.random_hue(image, max_delta=0.2)
return tf.clip_by_value(image,0.0,1.0)
def preprocess_for_train(image,height,width,bbox):
if bbox is None:
bbox = tf.constant([0.0,0.0,1.0,1.0],dtype = tf.float32,shape=[1,1,4])
if image.dtype != tf.float32:
image = tf.image.convert_image_dtype(image,tf.float32)
bbox_begin,bbox_size,_ = tf.image.sample_distorted_bounding_box(tf.shape(image),bounding_boxes=bbox)
distorted_image = tf.slice(image,bbox_begin,bbox_size)
##adjust size
distorted_image = tf.image.resize_images(distorted_image,[height,width],method=np.random.randint(4))
## flip left right
distorted_image = tf.image.random_flip_left_right(distorted_image)
## adjust color
distorted_image = distort_color(distorted_image,color_ordering=np.random.randint(2))
return distorted_image
image_raw_data = tf.gfile.FastGFile(filepath,'r').read()
with tf.Session() as sess:
image_data = tf.image.decode_jpeg(image_raw_data)
boxes = tf.constant([[[0.05,0.05,0.9,0.7],[0.35,0.47,0.5,0.56]]])
for i in range(6):
result = preprocess_for_train(image_data,299,299,boxes)
plt.subplot(2,3,i+1)
plt.imshow(result.eval())
plt.show()
出错情况:(pycherm编译器)
错误修改:
文件读取命令:
image_raw_data = tf.gfile.FastGFile(filepath,'r').read()
修改成('r'-->'rb'):
image_raw_data = tf.gfile.FastGFile(filepath,'rb').read()
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