unify box coordinate bias (#2311)

dygraph/configs/cascade_rcnn/_base_/cascade_mask_rcnn_r50_fpn.yml

@@ -76,7 +76,6 @@ BBoxPostProcess:
     keep_top_k: 100
     score_threshold: 0.05
     nms_threshold: 0.5
-    normalized: true
 
 
 MaskHead:

dygraph/configs/cascade_rcnn/_base_/cascade_rcnn_r50_fpn.yml

@@ -74,4 +74,3 @@ BBoxPostProcess:
     keep_top_k: 100
     score_threshold: 0.05
     nms_threshold: 0.5
-    normalized: true

dygraph/configs/faster_rcnn/_base_/faster_rcnn_r50.yml

@@ -65,4 +65,3 @@ BBoxPostProcess:
     keep_top_k: 100
     score_threshold: 0.05
     nms_threshold: 0.5
-    normalized: true

dygraph/configs/faster_rcnn/_base_/faster_rcnn_r50_fpn.yml

@@ -72,4 +72,3 @@ BBoxPostProcess:
     keep_top_k: 100
     score_threshold: 0.05
     nms_threshold: 0.5
-    normalized: true

dygraph/configs/hrnet/_base_/faster_rcnn_hrnetv2p_w18.yml

@@ -67,4 +67,3 @@ BBoxPostProcess:
     keep_top_k: 100
     score_threshold: 0.05
     nms_threshold: 0.5
-    normalized: true

dygraph/configs/mask_rcnn/_base_/mask_rcnn_r50.yml

@@ -67,7 +67,6 @@ BBoxPostProcess:
     keep_top_k: 100
     score_threshold: 0.05
     nms_threshold: 0.5
-    normalized: true
 
 MaskHead:
   head: MaskFeat

dygraph/configs/mask_rcnn/_base_/mask_rcnn_r50_fpn.yml

@@ -71,7 +71,6 @@ BBoxPostProcess:
     keep_top_k: 100
     score_threshold: 0.05
     nms_threshold: 0.5
-    normalized: true
 
 MaskHead:
   head: MaskFeat

dygraph/configs/ppyolo/_base_/ppyolo_mbv3_large.yml

@@ -55,4 +55,3 @@ BBoxPostProcess:
     nms_threshold: 0.45
     nms_top_k: 1000
     score_threshold: 0.005
-    normalized: false

dygraph/configs/ppyolo/_base_/ppyolo_mbv3_small.yml

@@ -55,4 +55,3 @@ BBoxPostProcess:
     nms_threshold: 0.45
     nms_top_k: 1000
     score_threshold: 0.005
-    normalized: false

dygraph/configs/ppyolo/_base_/ppyolo_r18vd.yml

@@ -56,5 +56,4 @@ BBoxPostProcess:
     score_threshold: 0.01
     post_threshold: 0.01
     nms_top_k: -1
-    normalized: false
     background_label: -1

dygraph/configs/ppyolo/_base_/ppyolo_r50vd_dcn.yml

@@ -64,5 +64,4 @@ BBoxPostProcess:
     score_threshold: 0.01
     post_threshold: 0.01
     nms_top_k: -1
-    normalized: false
     background_label: -1

dygraph/configs/ssd/README.md

@@ -6,8 +6,8 @@
 
 | 骨架网络        | 网络类型       | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP |                           下载                          | 配置文件 |
 | :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
-| VGG             | SSD            |    8    |   240e    |     ----     |  78.2  | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_vgg16_300_240e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/ssd/ssd_vgg16_300_240e_voc.yml) |
-| MobileNet v1    | SSD            |    32    |   120e    |     ----     |  73.3  | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) |
+| VGG             | SSD            |    8    |   240e    |     ----     |  77.8  | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_vgg16_300_240e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/ssd/ssd_vgg16_300_240e_voc.yml) |
+| MobileNet v1    | SSD            |    32    |   120e    |     ----     |  73.8  | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) |
 
 **注意：** SSD-VGG使用4GPU在总batch size为32下训练240个epoch。SSD-MobileNetv1使用2GPU在总batch size为64下训练120周期。
 

dygraph/configs/vehicle/vehicle_yolov3_darknet.yml

@@ -21,7 +21,6 @@ BBoxPostProcess:
     score_threshold: 0.005
     nms_threshold: 0.45
     nms_top_k: 400
-    normalized: false
 
 num_classes: 6
 

dygraph/configs/yolov3/_base_/yolov3_darknet53.yml

@@ -40,4 +40,3 @@ BBoxPostProcess:
     score_threshold: 0.01
     nms_threshold: 0.45
     nms_top_k: 1000
-    normalized: false

dygraph/configs/yolov3/_base_/yolov3_mobilenet_v1.yml

@@ -42,4 +42,3 @@ BBoxPostProcess:
     score_threshold: 0.01
     nms_threshold: 0.45
     nms_top_k: 1000
-    normalized: false

dygraph/configs/yolov3/_base_/yolov3_mobilenet_v3_large.yml

@@ -43,4 +43,3 @@ BBoxPostProcess:
     score_threshold: 0.01
     nms_threshold: 0.45
     nms_top_k: 1000
-    normalized: false

dygraph/configs/yolov3/_base_/yolov3_mobilenet_v3_small.yml

@@ -43,4 +43,3 @@ BBoxPostProcess:
     score_threshold: 0.01
     nms_threshold: 0.45
     nms_top_k: 1000
-    normalized: false

dygraph/configs/yolov3/_base_/yolov3_r50vd_dcn.yml

@@ -44,4 +44,3 @@ BBoxPostProcess:
     score_threshold: 0.01
     nms_threshold: 0.45
     nms_top_k: 1000
-    normalized: false

dygraph/ppdet/data/transform/operators.py

@@ -214,8 +214,8 @@ class RandomErasingImage(BaseOperator):
                 continue
 
             x1, y1, x2, y2 = gt_bbox[idx, :]
-            w_bbox = x2 - x1 + 1
-            h_bbox = y2 - y1 + 1
+            w_bbox = x2 - x1
+            h_bbox = y2 - y1
             area = w_bbox * h_bbox
 
             target_area = random.uniform(self.lower, self.higher) * area

dygraph/ppdet/modeling/layers.py

@@ -363,7 +363,7 @@ class MultiClassNMS(object):
                  nms_top_k=-1,
                  keep_top_k=100,
                  nms_threshold=.5,
-                 normalized=False,
+                 normalized=True,
                  nms_eta=1.0,
                  return_rois_num=True):
         super(MultiClassNMS, self).__init__()