paddle.fluid.layers.不存在于paddle2.2.2代码
时间: 2023-12-08 08:03:54 浏览: 69
对不起,您是正确的。在 PaddlePaddle 2.2.2 中,使用的是静态图模式,而不是动态图模式。以下是在 PaddlePaddle 2.2.2 中实现相同功能的代码:
```python
import paddle
import inverse_isp
import os
import glob
from PIL import Image
import numpy as np
def read_jpg(filename):
"""Read an 8-bit JPG file from disk and normalizes to [0, 1]."""
with open(filename, 'rb') as f:
image = paddle.vision.transforms.functional.decode_image(f.read(), 'RGB')
return paddle.cast(image, 'float32') / 255.0
```
在这里,我们使用 `open()` 函数读取文件,然后使用 `paddle.vision.transforms.functional.decode_image()` 函数解码图像。与 TensorFlow 不同,我们需要将文件打开为二进制模式,并将其作为字节串传递给解码函数。
相关问题
ipaddlepaddle2.2.2代码 paddle.fluid.*已经被 paddle.*取代
是的,您说得对,非常感谢您的提醒。下面是更新后的代码:
```
import paddle
import inverse_isp_paddle as inverse_isp
import os
import glob
from PIL import Image
import numpy as np
os.environ["CUDA_VISIBLE_DEVICES"] = '0'
def read_jpg(filename):
"""Read an 8-bit JPG file from disk and normalize to [0, 1]."""
image_file = paddle.static.io.file_reader(filename)
image = paddle.vision.transforms.image_decode(image_file, 'jpeg')
return paddle.cast(image, 'float32') / 255.0
def read_img(filename):
"""Read an image in most formats."""
image_file = paddle.static.io.file_reader(filename)
image = paddle.vision.transforms.image_decode(image_file, 'auto')
return paddle.cast(image, 'float32') / 255.0
def convert_to_raw(image):
"""Unprocess sRGB to packed raw."""
assert image.shape.is_compatible_with([None, None, 3])
image, metadata = inverse_isp.unprocess(image)
return image, metadata
```
paddlepaddle2.2.2无法使用import paddle.fluid as fluid
抱歉,我之前的回答有些问题。确实,PaddlePaddle 2.2.2已经不再使用`fluid`模块,而是使用`paddle`模块。下面是修改后的代码:
```python
import paddle
import numpy as np
def ccm():
"""Generates random RGB -> Camera color correction matrices."""
# Fixed XYZ -> Camera CCM.
cam2xyz = [[0.4679,0.2145,0.3176],[0.1433,0.8236,0.0331],[0.0003,-0.3607,1.3604]]
xyz2cam = paddle.to_tensor(np.linalg.inv(np.array(cam2xyz)).astype(np.float32))
# Multiplies with RGB -> XYZ to get RGB -> Camera CCM.
rgb2xyz = paddle.to_tensor([[0.4124564, 0.3575761, 0.1804375], [0.2126729, 0.7151522, 0.0721750], [0.0193339, 0.1191920, 0.9503041]])
rgb2cam = paddle.matmul(xyz2cam, rgb2xyz)
# Normalizes each row.
rgb2cam = rgb2cam / paddle.reduce_sum(rgb2cam, axis=-1, keepdim=True)
return rgb2cam
def gains():
"""Generates random gains for brightening and white balance."""
# RGB gain represents brightening.
rgb_gain = 1.0
# Red and blue gains represent white balance.
red_gain = 1.0 / 0.5527
blue_gain = 1.0 / 0.4844
return rgb_gain, red_gain, blue_gain
```