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PaddleSeg
提交 cd6e06d3 编写于 作者: L LutaoChu 提交者： wuzewu
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improve data check (#49) 

* update check.py

* Update check.md
上级 f10169ae
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docs/check.md
浏览文件 @ cd6e06d3
......@@ -6,7 +6,7 @@
# YAML_FILE_PATH为yaml配置文件路径
python pdseg/check.py --cfg ${YAML_FILE_PATH}
```
运行后，命令行将显示校验结果的概览信息，详细信息可到detail.log文件中查看。
运行后，命令行将显示校验结果的概览信息，详细的错误信息可到detail.log文件中查看。
### 1 列表分割符校验
判断在`TRAIN_FILE_LIST`，`VAL_FILE_LIST`和`TEST_FILE_LIST`列表文件中的分隔符`DATASET.SEPARATOR`设置是否正确。
......@@ -31,18 +31,24 @@ python pdseg/check.py --cfg ${YAML_FILE_PATH}
标注类别最好从0开始，否则可能影响精度。
### 6 标注像素统计
统计每种类别像素数量，显示以供参考。
统计每种类别的像素总数和所占比例，显示以供参考。统计结果如下：
```
Doing label pixel statistics:
(label class, total pixel number, percentage) = [(0, 2048984, 0.5211), (1, 1682943, 0.428), (2, 197976, 0.0503), (3, 2257, 0.0006)]
```
### 7 图像格式校验
检查图片类型`DATASET.IMAGE_TYPE`是否设置正确。
**NOTE:** 当数据集包含三通道图片时`DATASET.IMAGE_TYPE`设置为rgb；
当数据集全部为四通道图片时`DATASET.IMAGE_TYPE`设置为rgba；
### 8 图像与标注图尺寸一致性校验
### 8 图像最大尺寸统计
统计数据集中图片的最大高和最大宽，显示以供参考。
### 9 图像与标注图尺寸一致性校验
验证图像尺寸和对应标注图尺寸是否一致。
### 9 模型验证参数`EVAL_CROP_SIZE`校验
### 10 模型验证参数`EVAL_CROP_SIZE`校验
验证`EVAL_CROP_SIZE`是否设置正确，共有3种情形：
- 当`AUG.AUG_METHOD`为unpadding时，`EVAL_CROP_SIZE`的宽高应不小于`AUG.FIX_RESIZE_SIZE`的宽高。
......@@ -51,5 +57,5 @@ python pdseg/check.py --cfg ${YAML_FILE_PATH}
- 当`AUG.AUG_METHOD`为rangscaling时，`EVAL_CROP_SIZE`的宽高应不小于缩放后图像中最大的宽高。
### 10 数据增强参数`AUG.INF_RESIZE_VALUE`校验
### 11 数据增强参数`AUG.INF_RESIZE_VALUE`校验
验证`AUG.INF_RESIZE_VALUE`是否在[`AUG.MIN_RESIZE_VALUE`~`AUG.MAX_RESIZE_VALUE`]范围内。若在范围内，则通过校验。
pdseg/check.py
浏览文件 @ cd6e06d3
......@@ -16,6 +16,7 @@ import logging
from utils.config import cfg
def init_global_variable():
"""
初始化全局变量
......@@ -31,8 +32,8 @@ def init_global_variable():
global min_aspectratio # 图片最小宽高比
global max_aspectratio # 图片最大宽高比
global img_dim # 图片的通道数
global list_wrong #文件名格式错误列表
global imread_failed #图片读取失败列表, 二元列表
global list_wrong # 文件名格式错误列表
global imread_failed # 图片读取失败列表, 二元列表
global label_wrong # 标注图片出错列表
global label_gray_wrong # 标注图非灰度图列表
......@@ -52,29 +53,33 @@ def init_global_variable():
label_wrong = []
label_gray_wrong = []
def parse_args():
parser = argparse.ArgumentParser(description='PaddleSeg check')
parser.add_argument(
'--cfg',
dest='cfg_file',
help='Config file for training (and optionally testing)',
default=None,
type=str
)
'--cfg',
dest='cfg_file',
help='Config file for training (and optionally testing)',
default=None,
type=str)
return parser.parse_args()
def error_print(str):
return "".join(["\nNOT PASS ", str])
def correct_print(str):
return "".join(["\nPASS ", str])
def cv2_imread(file_path, flag=cv2.IMREAD_COLOR):
"""
解决 cv2.imread 在window平台打开中文路径的问题.
"""
return cv2.imdecode(np.fromfile(file_path, dtype=np.uint8), flag)
def get_image_max_height_width(img):
"""获取图片最大宽和高"""
global max_width, max_height
......@@ -83,21 +88,24 @@ def get_image_max_height_width(img):
max_height = max(height, max_height)
max_width = max(width, max_width)
def get_image_min_max_aspectratio(img):
"""计算图片最大宽高比"""
global min_aspectratio, max_aspectratio
img_shape = img.shape
height, width = img_shape[0], img_shape[1]
min_aspectratio = min(width/height, min_aspectratio)
max_aspectratio = max(width/height, max_aspectratio)
min_aspectratio = min(width / height, min_aspectratio)
max_aspectratio = max(width / height, max_aspectratio)
return min_aspectratio, max_aspectratio
def get_image_dim(img):
"""获取图像的通道数"""
img_shape = img.shape
if img_shape[-1] not in img_dim:
img_dim.append(img_shape[-1])
def is_label_gray(grt):
"""判断标签是否为灰度图"""
grt_shape = grt.shape
......@@ -106,6 +114,7 @@ def is_label_gray(grt):
else:
return False
def image_label_shape_check(img, grt):
"""
验证图像和标注的大小是否匹配
......@@ -117,11 +126,11 @@ def image_label_shape_check(img, grt):
grt_height = grt.shape[0]
grt_width = grt.shape[1]
if img_height != grt_height or img_width != grt_width:
flag = False
return flag
def ground_truth_check(grt, grt_path):
"""
验证标注图像的格式
......@@ -143,6 +152,7 @@ def ground_truth_check(grt, grt_path):
return png_format, unique, counts
def sum_gt_check(png_format, grt_classes, num_of_each_class):
"""
统计所有标注图上的格式、类别和每个类别的像素数
......@@ -160,7 +170,8 @@ def sum_gt_check(png_format, grt_classes, num_of_each_class):
png_format_wrong_num += 1
if cfg.DATASET.IGNORE_INDEX in grt_classes:
grt_classes2 = np.delete(grt_classes, np.where(grt_classes == cfg.DATASET.IGNORE_INDEX))
grt_classes2 = np.delete(
grt_classes, np.where(grt_classes == cfg.DATASET.IGNORE_INDEX))
else:
grt_classes2 = grt_classes
if min(grt_classes2) < 0 or max(grt_classes2) > cfg.DATASET.NUM_CLASSES - 1:
......@@ -179,6 +190,7 @@ def sum_gt_check(png_format, grt_classes, num_of_each_class):
total_grt_classes += add_class
return is_label_correct
def gt_check():
"""
对标注图像进行校验，输出校验结果
......@@ -192,16 +204,20 @@ def gt_check():
return
else:
logger.info(error_print("label format check"))
logger.info("total {} label images are png format, {} label images are not png "
"format".format(png_format_right_num, png_format_wrong_num))
logger.info(
"total {} label images are png format, {} label images are not png "
"format".format(png_format_right_num, png_format_wrong_num))
if len(png_format_wrong_image) > 0:
for i in png_format_wrong_image:
logger.debug(i)
total_nc = sorted(zip(total_grt_classes, total_num_of_each_class))
logger.info("\nDoing label pixel statistics...\nTotal label classes "
"and their corresponding numbers:\n{} ".format(total_nc))
total_ratio = total_num_of_each_class / sum(total_num_of_each_class)
total_ratio = np.around(total_ratio, decimals=4)
total_nc = sorted(
zip(total_grt_classes, total_num_of_each_class, total_ratio))
logger.info(
"\nDoing label pixel statistics:\n"
"(label class, total pixel number, percentage) = {} ".format(total_nc))
if len(label_wrong) == 0 and not total_nc[0][0]:
logger.info(correct_print("label class check!"))
......@@ -210,13 +226,15 @@ def gt_check():
if total_nc[0][0]:
logger.info("Warning: label classes should start from 0")
if len(label_wrong) > 0:
logger.info("fatal error: label class is out of range [0, {}]".format(cfg.DATASET.NUM_CLASSES - 1))
logger.info(
"fatal error: label class is out of range [0, {}]".format(
cfg.DATASET.NUM_CLASSES - 1))
for i in label_wrong:
logger.debug(i)
def eval_crop_size_check(max_height, max_width, min_aspectratio, max_aspectratio):
def eval_crop_size_check(max_height, max_width, min_aspectratio,
max_aspectratio):
"""
判断eval_crop_siz与验证集及测试集的max_height, max_width的关系
param
......@@ -225,69 +243,109 @@ def eval_crop_size_check(max_height, max_width, min_aspectratio, max_aspectratio
"""
if cfg.AUG.AUG_METHOD == "stepscaling":
if max_width <= cfg.EVAL_CROP_SIZE[0] and max_height <= cfg.EVAL_CROP_SIZE[1]:
if max_width <= cfg.EVAL_CROP_SIZE[
0] and max_height <= cfg.EVAL_CROP_SIZE[1]:
logger.info(correct_print("EVAL_CROP_SIZE check"))
logger.info(
"satisfy current EVAL_CROP_SIZE: ({},{}) >= max width and max height of images: ({},{})"
.format(cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1], max_width,
max_height))
else:
logger.info(error_print("EVAL_CROP_SIZE check"))
if max_width > cfg.EVAL_CROP_SIZE[0]:
logger.info("The EVAL_CROP_SIZE[0]: {} should larger max width of images {}!".format(
cfg.EVAL_CROP_SIZE[0], max_width))
logger.info(
"EVAL_CROP_SIZE[0]: {} should >= max width of images {}!".
format(cfg.EVAL_CROP_SIZE[0], max_width))
if max_height > cfg.EVAL_CROP_SIZE[1]:
logger.info(error_print("The EVAL_CROP_SIZE[1]: {} should larger max height of images {}!".format(
cfg.EVAL_CROP_SIZE[1], max_height)))
logger.info(
"EVAL_CROP_SIZE[1]: {} should >= max height of images {}!".
format(cfg.EVAL_CROP_SIZE[1], max_height))
elif cfg.AUG.AUG_METHOD == "rangescaling":
if min_aspectratio <= 1 and max_aspectratio >= 1:
if cfg.EVAL_CROP_SIZE[0] >= cfg.AUG.INF_RESIZE_VALUE and cfg.EVAL_CROP_SIZE[1] >= cfg.AUG.INF_RESIZE_VALUE:
if cfg.EVAL_CROP_SIZE[0] >= cfg.AUG.INF_RESIZE_VALUE \
and cfg.EVAL_CROP_SIZE[1] >= cfg.AUG.INF_RESIZE_VALUE:
logger.info(correct_print("EVAL_CROP_SIZE check"))
logger.info(
"satisfy current EVAL_CROP_SIZE: ({},{}) >= ({},{}) ".
format(cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1],
cfg.AUG.INF_RESIZE_VALUE, cfg.AUG.INF_RESIZE_VALUE))
else:
logger.info(error_print("EVAL_CROP_SIZE check"))
logger.info("EVAL_CROP_SIZE: ({},{}) must large than img size({},{})"
.format(cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1],
cfg.AUG.INF_RESIZE_VALUE, cfg.AUG.INF_RESIZE_VALUE))
logger.info(
"EVAL_CROP_SIZE must >= img size({},{}), current EVAL_CROP_SIZE is ({},{})"
.format(cfg.AUG.INF_RESIZE_VALUE, cfg.AUG.INF_RESIZE_VALUE,
cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1]))
elif min_aspectratio > 1:
max_height_rangscaling = cfg.AUG.INF_RESIZE_VALUE / min_aspectratio
max_height_rangscaling = round(max_height_rangscaling)
if cfg.EVAL_CROP_SIZE[0] >= cfg.AUG.INF_RESIZE_VALUE and cfg.EVAL_CROP_SIZE[1] >= max_height_rangscaling:
if cfg.EVAL_CROP_SIZE[
0] >= cfg.AUG.INF_RESIZE_VALUE and cfg.EVAL_CROP_SIZE[
1] >= max_height_rangscaling:
logger.info(correct_print("EVAL_CROP_SIZE check"))
logger.info(
"satisfy current EVAL_CROP_SIZE: ({},{}) >= ({},{}) ".
format(cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1],
cfg.AUG.INF_RESIZE_VALUE, max_height_rangscaling))
else:
logger.info(error_print("EVAL_CROP_SIZE check"))
logger.info("EVAL_CROP_SIZE: ({},{}) must large than img size({},{})"
.format(cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1],
cfg.AUG.INF_RESIZE_VALUE, max_height_rangscaling))
logger.info(
"EVAL_CROP_SIZE must >= img size({},{}), current EVAL_CROP_SIZE is ({},{})"
.format(cfg.AUG.INF_RESIZE_VALUE, max_height_rangscaling,
cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1]))
elif max_aspectratio < 1:
max_width_rangscaling = cfg.AUG.INF_RESIZE_VALUE * max_aspectratio
max_width_rangscaling = round(max_width_rangscaling)
if cfg.EVAL_CROP_SIZE[0] >= max_width_rangscaling and cfg.EVAL_CROP_SIZE[1] >= cfg.AUG.INF_RESIZE_VALUE:
if cfg.EVAL_CROP_SIZE[
0] >= max_width_rangscaling and cfg.EVAL_CROP_SIZE[
1] >= cfg.AUG.INF_RESIZE_VALUE:
logger.info(correct_print("EVAL_CROP_SIZE check"))
logger.info(
"satisfy current EVAL_CROP_SIZE: ({},{}) >= ({},{}) ".
format(cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1],
max_height_rangscaling, cfg.AUG.INF_RESIZE_VALUE))
else:
logger.info(error_print("EVAL_CROP_SIZE check"))
logger.info("EVAL_CROP_SIZE: ({},{}) must large than img size({},{})"
.format(cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1],
max_width_rangscaling, cfg.AUG.INF_RESIZE_VALUE))
logger.info(
"EVAL_CROP_SIZE must >= img size({},{}), current EVAL_CROP_SIZE is ({},{})"
.format(max_width_rangscaling, cfg.AUG.INF_RESIZE_VALUE,
cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1]))
elif cfg.AUG.AUG_METHOD == "unpadding":
if len(cfg.AUG.FIX_RESIZE_SIZE) != 2:
logger.info(error_print("EVAL_CROP_SIZE check"))
logger.info("you set AUG.AUG_METHOD = 'unpadding', but AUG.FIX_RESIZE_SIZE is wrong. "
"AUG.FIX_RESIZE_SIZE should be a tuple of length 2")
elif cfg.EVAL_CROP_SIZE[0] >= cfg.AUG.FIX_RESIZE_SIZE[0] and cfg.EVAL_CROP_SIZE[1] >= cfg.AUG.FIX_RESIZE_SIZE[1]:
logger.info(
"you set AUG.AUG_METHOD = 'unpadding', but AUG.FIX_RESIZE_SIZE is wrong. "
"AUG.FIX_RESIZE_SIZE should be a tuple of length 2")
elif cfg.EVAL_CROP_SIZE[0] >= cfg.AUG.FIX_RESIZE_SIZE[0] \
and cfg.EVAL_CROP_SIZE[1] >= cfg.AUG.FIX_RESIZE_SIZE[1]:
logger.info(correct_print("EVAL_CROP_SIZE check"))
logger.info(
"satisfy current EVAL_CROP_SIZE: ({},{}) >= AUG.FIX_RESIZE_SIZE: ({},{}) "
.format(cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1],
cfg.AUG.FIX_RESIZE_SIZE[0], cfg.AUG.FIX_RESIZE_SIZE[1]))
else:
logger.info(error_print("EVAL_CROP_SIZE check"))
logger.info("EVAL_CROP_SIZE: ({},{}) must large than img size({},{})"
.format(cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1],
cfg.AUG.FIX_RESIZE_SIZE[0], cfg.AUG.FIX_RESIZE_SIZE[1]))
logger.info(
"EVAL_CROP_SIZE: ({},{}) must >= AUG.FIX_RESIZE_SIZE: ({},{})".
format(cfg.EVAL_CROP_SIZE[0], cfg.EVAL_CROP_SIZE[1],
cfg.AUG.FIX_RESIZE_SIZE[0], cfg.AUG.FIX_RESIZE_SIZE[1]))
else:
logger.info("\nERROR! cfg.AUG.AUG_METHOD setting wrong, it should be one of "
"[unpadding, stepscaling, rangescaling]")
logger.info(
"\nERROR! cfg.AUG.AUG_METHOD setting wrong, it should be one of "
"[unpadding, stepscaling, rangescaling]")
def inf_resize_value_check():
if cfg.AUG.AUG_METHOD == "rangescaling":
if cfg.AUG.INF_RESIZE_VALUE < cfg.AUG.MIN_RESIZE_VALUE or \
cfg.AUG.INF_RESIZE_VALUE > cfg.AUG.MIN_RESIZE_VALUE:
logger.info("\nWARNING! you set AUG.AUG_METHOD = 'rangescaling'"
"AUG.INF_RESIZE_VALUE: {} not in [AUG.MIN_RESIZE_VALUE, AUG.MAX_RESIZE_VALUE]: "
"[{}, {}].".format(cfg.AUG.INF_RESIZE_VALUE, cfg.AUG.MIN_RESIZE_VALUE, cfg.AUG.MAX_RESIZE_VALUE))
logger.info(
"\nWARNING! you set AUG.AUG_METHOD = 'rangescaling'"
"AUG.INF_RESIZE_VALUE: {} not in [AUG.MIN_RESIZE_VALUE, AUG.MAX_RESIZE_VALUE]: "
"[{}, {}].".format(cfg.AUG.INF_RESIZE_VALUE,
cfg.AUG.MIN_RESIZE_VALUE,
cfg.AUG.MAX_RESIZE_VALUE))
def image_type_check(img_dim):
"""
......@@ -299,13 +357,17 @@ def image_type_check(img_dim):
if (1 in img_dim or 3 in img_dim) and cfg.DATASET.IMAGE_TYPE == 'rgba':
logger.info(error_print("DATASET.IMAGE_TYPE check"))
logger.info("DATASET.IMAGE_TYPE is {} but the type of image has "
"gray or rgb\n".format(cfg.DATASET.IMAGE_TYPE))
elif (1 not in img_dim and 3 not in img_dim and 4 in img_dim) and cfg.DATASET.IMAGE_TYPE == 'rgb':
"gray or rgb\n".format(cfg.DATASET.IMAGE_TYPE))
elif (1 not in img_dim and 3 not in img_dim
and 4 in img_dim) and cfg.DATASET.IMAGE_TYPE == 'rgb':
logger.info(correct_print("DATASET.IMAGE_TYPE check"))
logger.info("\nWARNING: DATASET.IMAGE_TYPE is {} but the type of all image is rgba".format(cfg.DATASET.IMAGE_TYPE))
logger.info(
"\nWARNING: DATASET.IMAGE_TYPE is {} but the type of all image is rgba"
.format(cfg.DATASET.IMAGE_TYPE))
else:
logger.info(correct_print("DATASET.IMAGE_TYPE check"))
def shape_check():
"""输出shape校验结果"""
if len(shape_unequal_image) == 0:
......@@ -313,7 +375,8 @@ def shape_check():
logger.info("All images are the same shape as the labels")
else:
logger.info(error_print("shape check"))
logger.info("Some images are not the same shape as the labels as follow: ")
logger.info(
"Some images are not the same shape as the labels as follow: ")
for i in shape_unequal_image:
logger.debug(i)
......@@ -321,13 +384,19 @@ def shape_check():
def file_list_check(list_name):
"""检查分割符是否复合要求"""
if len(list_wrong) == 0:
logger.info(correct_print(list_name.split(os.sep)[-1] + " DATASET.SEPARATOR check"))
logger.info(
correct_print(
list_name.split(os.sep)[-1] + " DATASET.SEPARATOR check"))
else:
logger.info(error_print(list_name.split(os.sep)[-1] + " DATASET.SEPARATOR check"))
logger.info("The following list is not separated by {}".format(cfg.DATASET.SEPARATOR))
logger.info(
error_print(
list_name.split(os.sep)[-1] + " DATASET.SEPARATOR check"))
logger.info("The following list is not separated by {}".format(
cfg.DATASET.SEPARATOR))
for i in list_wrong:
logger.debug(i)
def imread_check():
if len(imread_failed) == 0:
logger.info(correct_print("dataset reading check"))
......@@ -338,18 +407,25 @@ def imread_check():
for i in imread_failed:
logger.debug(i)
def label_gray_check():
if len(label_gray_wrong) == 0:
logger.info(correct_print("label gray check"))
logger.info("All label images are gray")
else:
logger.info(error_print("label gray check"))
logger.info("{} label images are not gray\nLabel pixel statistics may "
"be insignificant".format(len(label_gray_wrong)))
logger.info(
"{} label images are not gray\nLabel pixel statistics may be insignificant"
.format(len(label_gray_wrong)))
for i in label_gray_wrong:
logger.debug(i)
def max_img_size_statistics():
logger.info("\nDoing max image size statistics:")
logger.info("max width and max height of images are ({},{})".format(
max_width, max_height))
def check_train_dataset():
list_file = cfg.DATASET.TRAIN_FILE_LIST
......@@ -376,15 +452,18 @@ def check_train_dataset():
if not is_gray:
label_gray_wrong.append(line)
grt = cv2.cvtColor(grt, cv2.COLOR_BGR2GRAY)
get_image_max_height_width(img)
get_image_dim(img)
is_equal_img_grt_shape = image_label_shape_check(img, grt)
if not is_equal_img_grt_shape:
shape_unequal_image.append(line)
png_format, grt_classes, num_of_each_class = ground_truth_check(grt, grt_path)
png_format, grt_classes, num_of_each_class = ground_truth_check(
grt, grt_path)
if not png_format:
png_format_wrong_image.append(line)
is_label_correct = sum_gt_check(png_format, grt_classes, num_of_each_class)
is_label_correct = sum_gt_check(png_format, grt_classes,
num_of_each_class)
if not is_label_correct:
label_wrong.append(line)
......@@ -393,12 +472,10 @@ def check_train_dataset():
label_gray_check()
gt_check()
image_type_check(img_dim)
max_img_size_statistics()
shape_check()
def check_val_dataset():
list_file = cfg.DATASET.VAL_FILE_LIST
logger.info("\n-----------------------------\n2. Check val dataset...")
......@@ -430,10 +507,12 @@ def check_val_dataset():
is_equal_img_grt_shape = image_label_shape_check(img, grt)
if not is_equal_img_grt_shape:
shape_unequal_image.append(line)
png_format, grt_classes, num_of_each_class = ground_truth_check(grt, grt_path)
png_format, grt_classes, num_of_each_class = ground_truth_check(
grt, grt_path)
if not png_format:
png_format_wrong_image.append(line)
is_label_correct = sum_gt_check(png_format, grt_classes, num_of_each_class)
is_label_correct = sum_gt_check(png_format, grt_classes,
num_of_each_class)
if not is_label_correct:
label_wrong.append(line)
......@@ -442,8 +521,11 @@ def check_val_dataset():
label_gray_check()
gt_check()
image_type_check(img_dim)
max_img_size_statistics()
shape_check()
eval_crop_size_check(max_height, max_width, min_aspectratio, max_aspectratio)
eval_crop_size_check(max_height, max_width, min_aspectratio,
max_aspectratio)
def check_test_dataset():
list_file = cfg.DATASET.TEST_FILE_LIST
......@@ -481,10 +563,12 @@ def check_test_dataset():
is_equal_img_grt_shape = image_label_shape_check(img, grt)
if not is_equal_img_grt_shape:
shape_unequal_image.append(line)
png_format, grt_classes, num_of_each_class = ground_truth_check(grt, grt_path)
png_format, grt_classes, num_of_each_class = ground_truth_check(
grt, grt_path)
if not png_format:
png_format_wrong_image.append(line)
is_label_correct = sum_gt_check(png_format, grt_classes, num_of_each_class)
is_label_correct = sum_gt_check(png_format, grt_classes,
num_of_each_class)
if not is_label_correct:
label_wrong.append(line)
else:
......@@ -501,9 +585,12 @@ def check_test_dataset():
if has_label:
gt_check()
image_type_check(img_dim)
max_img_size_statistics()
if has_label:
shape_check()
eval_crop_size_check(max_height, max_width, min_aspectratio, max_aspectratio)
eval_crop_size_check(max_height, max_width, min_aspectratio,
max_aspectratio)
def main(args):
if args.cfg_file is not None:
......@@ -522,6 +609,9 @@ def main(args):
inf_resize_value_check()
print("\nDetailed error information can be viewed in detail.log file.")
if __name__ == "__main__":
args = parse_args()
logger = logging.getLogger()
......@@ -536,5 +626,3 @@ if __name__ == "__main__":
logger.addHandler(sh)
logger.addHandler(th)
main(args)
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