提交 efcbe272 编写于 作者: X Xin Pan

Refine detection_map doc.

上级 d00a0436
...@@ -175,12 +175,12 @@ class DetectionMAPOpMaker : public framework::OpProtoAndCheckerMaker { ...@@ -175,12 +175,12 @@ class DetectionMAPOpMaker : public framework::OpProtoAndCheckerMaker {
AddComment(R"DOC( AddComment(R"DOC(
Detection mAP evaluate operator. Detection mAP evaluate operator.
The general steps are as follows. First, calculate the true positive and The general steps are as follows. First, calculate the true positive and
false positive according to the input of detection and labels, then false positive according to the input of detection and labels, then
calculate the mAP evaluate value. calculate the mAP evaluate value.
Supporting '11 point' and 'integral' mAP algorithm. Please get more information Supporting '11 point' and 'integral' mAP algorithm. Please get more information
from the following articles: from the following articles:
https://sanchom.wordpress.com/tag/average-precision/ https://sanchom.wordpress.com/tag/average-precision/
https://arxiv.org/abs/1512.02325 https://arxiv.org/abs/1512.02325
)DOC"); )DOC");
} }
......
...@@ -16,7 +16,7 @@ All layers just related to the detection neural network. ...@@ -16,7 +16,7 @@ All layers just related to the detection neural network.
""" """
from layer_function_generator import generate_layer_fn from layer_function_generator import generate_layer_fn
from layer_function_generator import autodoc from layer_function_generator import autodoc, templatedoc
from ..layer_helper import LayerHelper from ..layer_helper import LayerHelper
import tensor import tensor
import nn import nn
...@@ -155,7 +155,7 @@ def detection_output(loc, ...@@ -155,7 +155,7 @@ def detection_output(loc,
return nmsed_outs return nmsed_outs
@autodoc() @templatedoc()
def detection_map(detect_res, def detection_map(detect_res,
label, label,
class_num, class_num,
...@@ -166,6 +166,47 @@ def detection_map(detect_res, ...@@ -166,6 +166,47 @@ def detection_map(detect_res,
input_states=None, input_states=None,
out_states=None, out_states=None,
ap_version='integral'): ap_version='integral'):
"""
${comment}
Args:
detect_res: ${detect_res_comment}
label: ${label_comment}
class_num: ${class_num_comment}
background_label: ${background_label_comment}
overlap_threshold: ${overlap_threshold_comment}
evaluate_difficult: ${evaluate_difficult_comment}
has_state: ${has_state_comment}
input_states: If not None, It contains 3 elements:
1. pos_count ${pos_count_comment}.
2. true_pos ${true_pos_comment}.
3. false_pos ${false_pos_comment}.
out_states: If not None, it contains 3 elements.
1. accum_pos_count ${accum_pos_count_comment}.
2. accum_true_pos ${accum_true_pos_comment}.
3. accum_false_pos ${accum_false_pos_comment}.
ap_version: ${ap_type_comment}
Returns:
${map_comment}
Examples:
.. code-block:: python
detect_res = fluid.layers.data(
name='detect_res',
shape=[10, 6],
append_batch_size=False,
dtype='float32')
label = fluid.layers.data(
name='label',
shape=[10, 6],
append_batch_size=False,
dtype='float32')
map_out = fluid.layers.detection_map(detect_res, label, 21)
"""
helper = LayerHelper("detection_map", **locals()) helper = LayerHelper("detection_map", **locals())
def __create_var(type): def __create_var(type):
......
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