diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec index 5134d74483684c2a52cc0515bee997801d9b335b..03faa7597a78392e4f43cfd2a99cfafd534f3fdc 100644 --- a/paddle/fluid/API.spec +++ b/paddle/fluid/API.spec @@ -328,7 +328,7 @@ paddle.fluid.layers.polygon_box_transform (ArgSpec(args=['input', 'name'], varar paddle.fluid.layers.yolov3_loss (ArgSpec(args=['x', 'gtbox', 'gtlabel', 'anchors', 'anchor_mask', 'class_num', 'ignore_thresh', 'downsample_ratio', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '991e934c3e09abf0edec7c9c978b4691')) paddle.fluid.layers.box_clip (ArgSpec(args=['input', 'im_info', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '397e9e02b451d99c56e20f268fa03f2e')) paddle.fluid.layers.multiclass_nms (ArgSpec(args=['bboxes', 'scores', 'score_threshold', 'nms_top_k', 'keep_top_k', 'nms_threshold', 'normalized', 'nms_eta', 'background_label', 'name'], varargs=None, keywords=None, defaults=(0.3, True, 1.0, 0, None)), ('document', 'ca7d1107b6c5d2d6d8221039a220fde0')) -paddle.fluid.layers.distribute_fpn_proposals (ArgSpec(args=['fpn_rois', 'min_level', 'max_level', 'refer_level', 'refer_scale', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'fa7008889611447edd1bac71dd42b558')) +paddle.fluid.layers.distribute_fpn_proposals (ArgSpec(args=['fpn_rois', 'min_level', 'max_level', 'refer_level', 'refer_scale', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'fdffe52577f7e74c090b030867fefc11')) paddle.fluid.layers.accuracy (ArgSpec(args=['input', 'label', 'k', 'correct', 'total'], varargs=None, keywords=None, defaults=(1, None, None)), ('document', '9808534c12c5e739a10f73ebb0b4eafd')) paddle.fluid.layers.auc (ArgSpec(args=['input', 'label', 'curve', 'num_thresholds', 'topk', 'slide_steps'], varargs=None, keywords=None, defaults=('ROC', 4095, 1, 1)), ('document', 'e0e95334fce92d16c2d9db6e7caffc47')) paddle.fluid.layers.exponential_decay (ArgSpec(args=['learning_rate', 'decay_steps', 'decay_rate', 'staircase'], varargs=None, keywords=None, defaults=(False,)), ('document', '98a5050bee8522fcea81aa795adaba51')) diff --git a/python/paddle/fluid/layers/detection.py b/python/paddle/fluid/layers/detection.py index 1d2cc4649353362c777bd7d500087cb79555d055..c738577f631fed7f0426f4f0faa612d27948512a 100644 --- a/python/paddle/fluid/layers/detection.py +++ b/python/paddle/fluid/layers/detection.py @@ -2231,21 +2231,23 @@ def distribute_fpn_proposals(fpn_rois, refer_scale, name=None): """ - Distribute all proposals into different fpn level, with respect to scale - of the proposals, the referring scale and the referring level. Besides, to - restore the order of proposals, we return an array which indicates the - original index of rois in current proposals. To compute fpn level for each - roi, the formula is given as follows: + In Feature Pyramid Networks (FPN) models, it is needed to distribute all + proposals into different FPN level, with respect to scale of the proposals, + the referring scale and the referring level. Besides, to restore the order + of proposals, we return an array which indicates the original index of rois + in current proposals. To compute FPN level for each roi, the formula is + given as follows: .. math:: - roi\_scale = \sqrt{BBoxArea(fpn\_roi)} - level = floor(\log(\\frac{roi\_scale}{refer\_scale}) + refer\_level) + roi\_scale &= \sqrt{BBoxArea(fpn\_roi)} - where BBoxArea is the area of each roi + level = floor(&\log(\\frac{roi\_scale}{refer\_scale}) + refer\_level) + + where BBoxArea is a function to compute the area of each roi. Args: - fpn_rois(variable): The input fpn_rois, the last dimension is 4. + fpn_rois(variable): The input fpn_rois, the second dimension is 4. min_level(int): The lowest level of FPN layer where the proposals come from. max_level(int): The highest level of FPN layer where the proposals