diff --git a/docs/check.md b/docs/check.md index c47618b67cbfb2de2bb90758cdd566aaea956310..fac9520f11ef46d3628ecab3fcc4127a468a3ca5 100644 --- a/docs/check.md +++ b/docs/check.md @@ -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。 diff --git a/pdseg/check.py b/pdseg/check.py index 469709e12bb5e6fa83a384639f6ca11b0ce56e1a..9eb8175e0c6377714be538f26c79e61aff51202e 100644 --- a/pdseg/check.py +++ b/pdseg/check.py @@ -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) - -