report Proposals AR

foolwood · Feb 21, 2019 · 97b02aa · 97b02aa
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diff --git a/README.md b/README.md
@@ -74,21 +74,21 @@ CUDA_VISIBLE_DEVICES=0,1,2,3 python tools/train.py --dataset coco -j 20 --arch S
 ```
 
 #### Testing
-Test on COCO valiadation set.
+Test on COCO validation set (5K).
 ```bash
 sh scripts/test_recall_coco.sh
 ```
 Our results
 ```shell
-+-----------------+------------------------+------------------------+
-|                 |      Box Proposals     | Segmentation Proposals |
-+                 +------------------------+------------------------+
-|                 | AR_10 | AR_100 | AR_1K | AR_10 | AR_100 | AR_1K |
-+-----------------+-------+--------+-------+-------+--------+-------+
-| DeepMask(paper) |  15.0 |  32.6  |  48.2 |  12.7 |  26.1  |  36.6 |
-+-----------------+-------+--------+-------+-------+--------+-------+
-| DeepMask(our)   |       |        |       |       |        |       |
-+-----------------+-------+--------+-------+-------+--------+-------+
+                +-----------------+------------------------+------------------------+
+                |                 |      Box Proposals     | Segmentation Proposals |
+                +                 +------------------------+------------------------+
+                |                 | AR_10 | AR_100 | AR_1K | AR_10 | AR_100 | AR_1K |
+                +-----------------+-------+--------+-------+-------+--------+-------+
+                | DeepMask(paper) |  18.7 |  34.9  |  46.5 |  14.4 |  25.8  |  33.1 |
+                +-----------------+-------+--------+-------+-------+--------+-------+
+                | DeepMask(ours)  |  18.3 |  35.9  |  48.4 |  13.6 |  26.0  |  33.5 |
+                +-----------------+-------+--------+-------+-------+--------+-------+
 ```
 
 ## Naive Cascade Instance Segmentation (YOLOv3+DeepMask=10FPS~28FPS)

diff --git a/tools/evalPerImage.py b/tools/evalPerImage.py
@@ -122,7 +122,6 @@ def main():
     cocoDt = coco.loadRes(result_path)
 
     print('\n\nBox Proposals Evalution\n\n')
-    annType = ['bbox']  # segm  bbox
     cocoEval = COCOeval(coco, cocoDt)
 
     max_dets = [10, 100, 1000]
@@ -138,7 +137,6 @@ def main():
     cocoEval.summarize()
 
     print('\n\nSegmentation Proposals Evalution\n\n')
-    annType = ['segm']  # segm  bbox
     cocoEval = COCOeval(coco, cocoDt)
 
     max_dets = [10, 100, 1000]