提交 0c1831c5 编写于 作者: F FlyingQianMM

add flag with pretrain_weights key

上级 f8ab6cc0
......@@ -74,47 +74,47 @@ image_pretrain = {
}
coco_pretrain = {
'YOLOv3_DarkNet53':
'YOLOv3_DarkNet53_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar',
'YOLOv3_MobileNetV1':
'YOLOv3_MobileNetV1_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar',
'YOLOv3_MobileNetV3_large':
'YOLOv3_MobileNetV3_large_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams',
'YOLOv3_ResNet34':
'YOLOv3_ResNet34_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar',
'YOLOv3_ResNet50_vd':
'YOLOv3_ResNet50_vd_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn.tar',
'FasterRCNN_ResNet50':
'FasterRCNN_ResNet50_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_2x.tar',
'FasterRCNN_ResNet50_vd':
'FasterRCNN_ResNet50_vd_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar',
'FasterRCNN_ResNet101':
'FasterRCNN_ResNet101_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_2x.tar',
'FasterRCNN_ResNet101_vd':
'FasterRCNN_ResNet101_vd_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_2x.tar',
'FasterRCNN_HRNet_W18':
'FasterRCNN_HRNet_W18_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_hrnetv2p_w18_2x.tar',
'MaskRCNN_ResNet50':
'MaskRCNN_ResNet50_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_2x.tar',
'MaskRCNN_ResNet50_vd':
'MaskRCNN_ResNet50_vd_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_2x.tar',
'MaskRCNN_ResNet101':
'MaskRCNN_ResNet101_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_2x.tar',
'MaskRCNN_ResNet101_vd':
'MaskRCNN_ResNet101_vd_COCO':
'https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_vd_fpn_1x.tar',
'UNet': 'https://paddleseg.bj.bcebos.com/models/unet_coco_v3.tgz',
'DeepLabv3p_MobileNetV2_x1.0':
'UNet_COCO': 'https://paddleseg.bj.bcebos.com/models/unet_coco_v3.tgz',
'DeepLabv3p_MobileNetV2_x1.0_COCO':
'https://bj.bcebos.com/v1/paddleseg/deeplab_mobilenet_x1_0_coco.tgz',
'DeepLabv3p_Xception65':
'DeepLabv3p_Xception65_COCO':
'https://paddleseg.bj.bcebos.com/models/xception65_coco.tgz'
}
cityscapes_pretrain = {
'DeepLabv3p_MobileNetV2_x1.0':
'DeepLabv3p_MobileNetV2_x1.0_CITYSCAPES':
'https://paddleseg.bj.bcebos.com/models/mobilenet_cityscapes.tgz',
'DeepLabv3p_Xception65':
'DeepLabv3p_Xception65_CITYSCAPES':
'https://paddleseg.bj.bcebos.com/models/xception65_bn_cityscapes.tgz',
'HRNet_W18':
'HRNet_W18_CITYSCAPES':
'https://paddleseg.bj.bcebos.com/models/hrnet_w18_bn_cityscapes.tgz'
}
......@@ -198,6 +198,7 @@ def get_pretrain_weights(flag, class_name, backbone, save_dir):
new_save_dir = paddlex.pretrain_dir
if class_name in ['YOLOv3', 'FasterRCNN', 'MaskRCNN', 'DeepLabv3p']:
backbone = '{}_{}'.format(class_name, backbone)
backbone = "{}_{}".format(backbone, flag)
if flag == 'COCO':
url = coco_pretrain[backbone]
elif flag == 'CITYSCAPES':
......
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