提交 4cbf8369 编写于 作者: S sunyanfang01

add transforms vdl

上级 bc44ce9d
......@@ -15,6 +15,7 @@
from .ops import *
from .imgaug_support import execute_imgaug
import random
import os
import os.path as osp
import numpy as np
from PIL import Image, ImageEnhance
......@@ -57,8 +58,24 @@ class Compose(ClsTransform):
raise Exception(
"Elements in transforms should be defined in 'paddlex.cls.transforms' or class of imgaug.augmenters.Augmenter, see docs here: https://paddlex.readthedocs.io/zh_CN/latest/apis/transforms/"
)
def __call__(self, im, label=None):
self.images_writer = None
def set_vdl(self, vdl_save_dir=None):
# 对数据预处理结果在VisualDL中可视化
self.images_writer = None
if vdl_save_dir is not None:
if not osp.isdir(vdl_save_dir):
if osp.exists(vdl_save_dir):
os.remove(vdl_save_dir)
os.makedirs(vdl_save_dir)
from visualdl import LogWriter
vdl_images_dir = osp.join(vdl_save_dir, 'image_transforms')
self.images_writer = LogWriter(vdl_images_dir)
def release_vdl(self):
self.images_writer = None
def __call__(self, im, label=None, step=0):
"""
Args:
im (str/np.ndarray): 图像路径/图像np.ndarray数据。
......@@ -67,6 +84,7 @@ class Compose(ClsTransform):
tuple: 根据网络所需字段所组成的tuple;
字段由transforms中的最后一个数据预处理操作决定。
"""
im_file = str(step)
if isinstance(im, np.ndarray):
if len(im.shape) != 3:
raise Exception(
......@@ -74,10 +92,16 @@ class Compose(ClsTransform):
format(len(im.shape)))
else:
try:
im_file = im
im = cv2.imread(im).astype('float32')
except:
raise TypeError('Can\'t read The image file {}!'.format(im))
im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
if self.images_writer is not None:
self.images_writer.add_image(tag='0. origin image',
img=im,
step=step)
op_id = 1
for op in self.transforms:
if isinstance(op, ClsTransform):
outputs = op(im, label)
......@@ -91,6 +115,12 @@ class Compose(ClsTransform):
outputs = (im, )
if label is not None:
outputs = (im, label)
if self.images_writer is not None:
tag = str(op_id) + '. ' + op.__class__.__name__
self.images_writer.add_image(tag=tag,
img=im,
step=step)
op_id += 1
return outputs
def add_augmenters(self, augmenters):
......@@ -434,6 +464,7 @@ class RandomDistort(ClsTransform):
params['im'] = im
if np.random.uniform(0, 1) < prob:
im = ops[id](**params)
im = im.astype('float32')
if label is None:
return (im, )
else:
......
......@@ -18,6 +18,7 @@ except Exception:
from collections import Sequence
import random
import os
import os.path as osp
import numpy as np
......@@ -50,7 +51,7 @@ class Compose(DetTransform):
ValueError: 数据长度不匹配。
"""
def __init__(self, transforms):
def __init__(self, transforms, vdl_save_dir=None):
if not isinstance(transforms, list):
raise TypeError('The transforms must be a list!')
if len(transforms) < 1:
......@@ -69,8 +70,24 @@ class Compose(DetTransform):
raise Exception(
"Elements in transforms should be defined in 'paddlex.det.transforms' or class of imgaug.augmenters.Augmenter, see docs here: https://paddlex.readthedocs.io/zh_CN/latest/apis/transforms/"
)
def __call__(self, im, im_info=None, label_info=None):
self.images_writer = None
def set_vdl(self, vdl_save_dir=None):
# 对数据预处理结果在VisualDL中可视化
self.images_writer = None
if vdl_save_dir is not None:
if not osp.isdir(vdl_save_dir):
if osp.exists(vdl_save_dir):
os.remove(vdl_save_dir)
os.makedirs(vdl_save_dir)
from visualdl import LogWriter
vdl_images_dir = osp.join(vdl_save_dir, 'image_transforms')
self.images_writer = LogWriter(vdl_images_dir)
def release_vdl(self):
self.images_writer = None
def __call__(self, im, im_info=None, label_info=None, step=0):
"""
Args:
im (str/np.ndarray): 图像路径/图像np.ndarray数据。
......@@ -133,12 +150,21 @@ class Compose(DetTransform):
return (im, im_info)
else:
return (im, im_info, label_info)
if isinstance(im, str):
im_file = im
else:
im_file = str(step)
outputs = decode_image(im, im_info, label_info)
im = outputs[0]
im_info = outputs[1]
if len(outputs) == 3:
label_info = outputs[2]
if self.images_writer is not None:
self.images_writer.add_image(tag='0. origin image',
img=im,
step=step)
op_id = 1
for op in self.transforms:
if im is None:
return None
......@@ -151,6 +177,12 @@ class Compose(DetTransform):
outputs = (im, im_info, label_info)
else:
outputs = (im, im_info)
if self.images_writer is not None:
tag = str(op_id) + '. ' + op.__class__.__name__
self.images_writer.add_image(tag=tag,
img=im,
step=step)
op_id += 1
return outputs
def add_augmenters(self, augmenters):
......@@ -621,6 +653,7 @@ class RandomDistort(DetTransform):
if np.random.uniform(0, 1) < prob:
im = ops[id](**params)
im = im.astype('float32')
if label_info is None:
return (im, im_info)
else:
......
......@@ -13,6 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from .ops import *
from .imgaug_support import execute_imgaug
import random
......@@ -45,7 +46,7 @@ class Compose(SegTransform):
"""
def __init__(self, transforms):
def __init__(self, transforms, vdl_save_dir=None):
if not isinstance(transforms, list):
raise TypeError('The transforms must be a list!')
if len(transforms) < 1:
......@@ -61,8 +62,24 @@ class Compose(SegTransform):
raise Exception(
"Elements in transforms should be defined in 'paddlex.seg.transforms' or class of imgaug.augmenters.Augmenter, see docs here: https://paddlex.readthedocs.io/zh_CN/latest/apis/transforms/"
)
def __call__(self, im, im_info=None, label=None):
self.images_writer = None
def set_vdl(self, vdl_save_dir=None):
# 对数据预处理结果在VisualDL中可视化
self.images_writer = None
if vdl_save_dir is not None:
if not osp.isdir(vdl_save_dir):
if osp.exists(vdl_save_dir):
os.remove(vdl_save_dir)
os.makedirs(vdl_save_dir)
from visualdl import LogWriter
vdl_images_dir = osp.join(vdl_save_dir, 'image_transforms')
self.images_writer = LogWriter(vdl_images_dir)
def release_vdl(self):
self.images_writer = None
def __call__(self, im, im_info=None, label=None, step=0):
"""
Args:
im (str/np.ndarray): 图像路径/图像np.ndarray数据。
......@@ -75,7 +92,7 @@ class Compose(SegTransform):
Returns:
tuple: 根据网络所需字段所组成的tuple;字段由transforms中的最后一个数据预处理操作决定。
"""
im_file = str(step)
if im_info is None:
im_info = list()
if isinstance(im, np.ndarray):
......@@ -85,6 +102,7 @@ class Compose(SegTransform):
format(len(im.shape)))
else:
try:
im_file = im
im = cv2.imread(im).astype('float32')
except:
raise ValueError('Can\'t read The image file {}!'.format(im))
......@@ -93,6 +111,11 @@ class Compose(SegTransform):
if label is not None:
if not isinstance(label, np.ndarray):
label = np.asarray(Image.open(label))
if self.images_writer is not None:
self.images_writer.add_image(tag='0. origin image',
img=im,
step=step)
op_id = 1
for op in self.transforms:
if isinstance(op, SegTransform):
outputs = op(im, im_info, label)
......@@ -107,6 +130,12 @@ class Compose(SegTransform):
outputs = (im, im_info, label)
else:
outputs = (im, im_info)
if self.images_writer is not None:
tag = str(op_id) + '. ' + op.__class__.__name__
self.images_writer.add_image(tag=tag,
img=im,
step=step)
op_id += 1
return outputs
def add_augmenters(self, augmenters):
......@@ -1053,6 +1082,7 @@ class RandomDistort(SegTransform):
params['im'] = im
if np.random.uniform(0, 1) < prob:
im = ops[id](**params)
im = im.astype('float32')
if label is None:
return (im, im_info)
else:
......
......@@ -34,6 +34,19 @@ eval_dataset = pdx.datasets.ImageNet(
label_list='vegetables_cls/labels.txt',
transforms=eval_transforms)
# 可使用VisualDL查看数据预处理的中间结果
# VisualDL启动方式: visualdl --logdir vdl_output --port 8001
# 浏览器打开 https://0.0.0.0:8001即可
# 其中0.0.0.0为本机访问,如为远程服务, 改成相应机器IP
train_transforms.set_vdl(vdl_save_dir='vdl_output')
for step, data in enumerate(train_dataset.iterator()):
data.append(step)
train_transforms(*data)
if step == 5:
break
train_transforms.release_vdl()
# 初始化模型,并进行训练
# 可使用VisualDL查看训练指标
# VisualDL启动方式: visualdl --logdir output/mobilenetv2/vdl_log --port 8001
......
......@@ -38,6 +38,30 @@ eval_dataset = pdx.datasets.VOCDetection(
label_list='insect_det/labels.txt',
transforms=eval_transforms)
# 可使用VisualDL查看数据预处理的中间结果
# VisualDL启动方式: visualdl --logdir vdl_output --port 8001
# 浏览器打开 https://0.0.0.0:8001即可
# 其中0.0.0.0为本机访问,如为远程服务, 改成相应机器IP
train_transforms.set_vdl(vdl_save_dir='vdl_output')
for step, data in enumerate(train_dataset.iterator()):
data.append(step)
train_transforms(*data)
if step == 5:
break
train_transforms.release_vdl()
# 可使用VisualDL查看数据预处理的中间结果
# VisualDL启动方式: visualdl --logdir vdl_output --port 8001
# 浏览器打开 https://0.0.0.0:8001即可
# 其中0.0.0.0为本机访问,如为远程服务, 改成相应机器IP
train_transforms.vdl_save_dir = 'vdl_output'
for step, data in enumerate(train_dataset.iterator()):
data.append(step)
train_transforms(*data)
if step == 5:
break
train_transforms.vdl_save_dir = None
# 初始化模型,并进行训练
# 可使用VisualDL查看训练指标
# VisualDL启动方式: visualdl --logdir output/yolov3_darknet/vdl_log --port 8001
......
......@@ -33,6 +33,18 @@ eval_dataset = pdx.datasets.SegDataset(
label_list='optic_disc_seg/labels.txt',
transforms=eval_transforms)
# 可使用VisualDL查看数据预处理的中间结果
# VisualDL启动方式: visualdl --logdir vdl_output --port 8001
# 浏览器打开 https://0.0.0.0:8001即可
# 其中0.0.0.0为本机访问,如为远程服务, 改成相应机器IP
train_transforms.vdl_save_dir = 'vdl_output'
for step, data in enumerate(train_dataset.iterator()):
data.append(step)
train_transforms(*data)
if step == 5:
break
train_transforms.vdl_save_dir = None
# 初始化模型,并进行训练
# 可使用VisualDL查看训练指标
# VisualDL启动方式: visualdl --logdir output/deeplab/vdl_log --port 8001
......
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