merge

dmlc · Jerryzcn · Jul 8, 2020 · May 6, 2020 · May 6, 2020 · May 6, 2020
commit e73985a889e1cf3a3f9fcfb94a7707624a2b17ce
diff --git a/docs/tutorials/pose/cam_demo.py b/docs/tutorials/pose/cam_demo.py
@@ -52,7 +52,7 @@
     detector.reset_class(classes=['person'], reuse_weights={'person':'person'})
     detector.hybridize()
 
-Next for the estimator, we choose ``simple_pose_resnet18_v1b`` for it is light-weighted.
+Next for the estimators, we choose ``simple_pose_resnet18_v1b`` for it is light-weighted.
 
 The default ``simple_pose_resnet18_v1b`` model was trained with input size 256x192.
 We also provide an optional ``simple_pose_resnet18_v1b`` model trained with input size 128x96.
@@ -61,8 +61,8 @@
 
 .. code-block:: python
 
-    estimator = get_model('simple_pose_resnet18_v1b', pretrained='ccd24037', ctx=ctx)
-    estimator.hybridize()
+    estimators = get_model('simple_pose_resnet18_v1b', pretrained='ccd24037', ctx=ctx)
+    estimators.hybridize()
 
 With OpenCV, we can easily retrieve frames from the webcam.
 
@@ -107,7 +107,7 @@
         pose_input, upscale_bbox = detector_to_simple_pose(frame, class_IDs, scores, bounding_boxs,
                                                            output_shape=(128, 96), ctx=ctx)
         if len(upscale_bbox) > 0:
-            predicted_heatmap = estimator(pose_input)
+            predicted_heatmap = estimators(pose_input)
             pred_coords, confidence = heatmap_to_coord(predicted_heatmap, upscale_bbox)
 
             img = cv_plot_keypoints(frame, pred_coords, confidence, class_IDs, bounding_boxs, scores,

diff --git a/gluoncv/estimators/rcnn/__init__.py b/gluoncv/estimators/rcnn/__init__.py
diff --git a/gluoncv/loss.py b/gluoncv/loss.py
@@ -110,7 +110,7 @@ class SSDMultiBoxLoss(gluon.Block):
     negative_mining_ratio : float, default is 3
         Ratio of negative vs. positive samples.
     rho : float, default is 1.0
-        Threshold for trimmed mean estimator. This is the smooth parameter for the
+        Threshold for trimmed mean estimators. This is the smooth parameter for the
         L1-L2 transition.
     lambd : float, default is 1.0
         Relative weight between classification and box regression loss.

diff --git a/gluoncv/pipelines/__init__.py b/gluoncv/pipelines/__init__.py
@@ -1,2 +1,2 @@
 """GluonCV pipelines"""
-from .estimator import *
+from .estimators import *
diff --git a/gluoncv/pipelines/estimator/__init__.py → gluoncv/pipelines/estimators/__init__.py b/gluoncv/pipelines/estimator/__init__.py → gluoncv/pipelines/estimators/__init__.py
diff --git a/...ncv/pipelines/estimator/base_estimator.py → ...cv/pipelines/estimators/base_estimator.py b/...ncv/pipelines/estimator/base_estimator.py → ...cv/pipelines/estimators/base_estimator.py
diff --git a/gluoncv/pipelines/estimator/center_net.py → gluoncv/pipelines/estimators/center_net.py b/gluoncv/pipelines/estimator/center_net.py → gluoncv/pipelines/estimators/center_net.py
diff --git a/gluoncv/pipelines/estimator/common.py → gluoncv/pipelines/estimators/common.py b/gluoncv/pipelines/estimator/common.py → gluoncv/pipelines/estimators/common.py
diff --git a/gluoncv/estimators/__init__.py → ...ncv/pipelines/estimators/rcnn/__init__.py b/gluoncv/estimators/__init__.py → ...ncv/pipelines/estimators/rcnn/__init__.py
diff --git a/gluoncv/estimators/rcnn/faster_rcnn.py → .../pipelines/estimators/rcnn/faster_rcnn.py b/gluoncv/estimators/rcnn/faster_rcnn.py → .../pipelines/estimators/rcnn/faster_rcnn.py
@@ -5,24 +5,24 @@
 import time
 
 import mxnet as mx
-from mxnet import gluon
-
 import numpy as np
+from mxnet import gluon
 
-from ... import data as gdata
-from ...data.batchify import FasterRCNNTrainBatchify, Tuple, Append
-from ...data.sampler import SplitSortedBucketSampler
-from ...data.transforms import presets
-from ...data.transforms.presets.rcnn import FasterRCNNDefaultTrainTransform, \
+from gluoncv import data as gdata
+from gluoncv.data.batchify import FasterRCNNTrainBatchify, Tuple, Append
+from gluoncv.data.sampler import SplitSortedBucketSampler
+from gluoncv.data.transforms import presets
+from gluoncv.data.transforms.presets.rcnn import FasterRCNNDefaultTrainTransform, \
     FasterRCNNDefaultValTransform
-from ...model_zoo import get_model
-from ...model_zoo.rcnn.faster_rcnn.data_parallel import ForwardBackwardTask
-from ...nn.bbox import BBoxClipToImage
-from ...utils.metrics.coco_detection import COCODetectionMetric
-from ...utils.metrics.rcnn import RPNAccMetric, RPNL1LossMetric, RCNNAccMetric, \
+from gluoncv.model_zoo import get_model
+from gluoncv.model_zoo.rcnn.faster_rcnn.data_parallel import ForwardBackwardTask
+from gluoncv.nn.bbox import BBoxClipToImage
+from gluoncv.pipelines.estimators.base_estimator import BaseEstimator
+from gluoncv.utils.metrics.coco_detection import COCODetectionMetric
+from gluoncv.utils.metrics.rcnn import RPNAccMetric, RPNL1LossMetric, RCNNAccMetric, \
     RCNNL1LossMetric
-from ...utils.metrics.voc_detection import VOC07MApMetric
-from ...utils.parallel import Parallel
+from gluoncv.utils.metrics.voc_detection import VOC07MApMetric
+from gluoncv.utils.parallel import Parallel
 
 try:
     import horovod.mxnet as hvd
@@ -116,18 +116,18 @@ def _get_dataset(dataset, args):
     return train_dataset, val_dataset, val_metric
 
 
-class FasterRCNNEstimator:
+class FasterRCNNEstimator(BaseEstimator):
     """ Estimator for Faster R-CNN.
     """
 
     def __init__(self, cfg, logger=None):
         """
-        Constructs Faster R-CNN estimator.
+        Constructs Faster R-CNN estimators.
 
         Parameters
         ----------
         cfg : configuration object
-            Configuration object containing information for constructing Faster R-CNN estimator.
+            Configuration object containing information for constructing Faster R-CNN estimators.
         logger : logger object, default is None
             If not `None`, will use default logging object.
         """
@@ -301,8 +301,7 @@ def _validate(self, val_data, ctx, eval_metric):
                 eval_metric.update(det_bbox, det_id, det_score, gt_bbox, gt_id, gt_diff)
         return eval_metric.get()
 
-    def fit(self):
-
+    def _fit(self):
         """
         Fit faster R-CNN models.
         """

diff --git a/scripts/detection/faster_rcnn/train_faster_rcnn.py b/scripts/detection/faster_rcnn/train_faster_rcnn.py
@@ -16,7 +16,7 @@
 
 gcv.utils.check_version('0.7.0')
 from gluoncv import utils as gutils
-from gluoncv.estimators.rcnn.faster_rcnn import FasterRCNNEstimator
+from gluoncv.pipelines.estimators.rcnn import FasterRCNNEstimator
 
 try:
     import horovod.mxnet as hvd