[Fix] Fix fpg link (open-mmlab#7478)

ZwwWayne · Jul 19, 2022 · 26aaaeb · 26aaaeb
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diff --git a/configs/fpg/README.md b/configs/fpg/README.md
@@ -19,12 +19,14 @@ All backbones are Resnet-50 in pytorch style.
 
 | Method       | Neck        | Lr schd | Mem (GB) | Inf time (fps) | box AP | mask AP | Config | Download |
 |:------------:|:-----------:|:-------:|:--------:|:--------------:|:------:|:-------:|:-------:|:--------:|
-| Faster R-CNN | FPG         | 50e     | 20.0     | -              | 42.2   | -       |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/faster_rcnn_r50_fpg_crop640_50e_coco.py) |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg_crop640_50e_coco/faster_rcnn_r50_fpg_crop640_50e_coco-76220505.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg_crop640_50e_coco/20210218_223520.log.json) |
-| Faster R-CNN | FPG-chn128  | 50e     | 11.9     | -              | 41.2   | -       |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/faster_rcnn_r50_fpg-chn128_crop640_50e_coco.py) |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg-chn128_crop640_50e_coco/faster_rcnn_r50_fpg-chn128_crop640_50e_coco-24257de9.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg-chn128_crop640_50e_coco/20210218_221412.log.json) |
-| Mask R-CNN   | FPG         | 50e     | 23.2     | -              | 42.7   | 37.8    |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/mask_rcnn_r50_fpg_crop640_50e_coco.py) |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg_crop640_50e_coco/mask_rcnn_r50_fpg_crop640_50e_coco-c5860453.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg_crop640_50e_coco/20210222_205447.log.json) |
-| Mask R-CNN   | FPG-chn128  | 50e     | 15.3     | -              | 41.7   | 36.9    |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/mask_rcnn_r50_fpg-chn128_crop640_50e_coco.py) |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg-chn128_crop640_50e_coco/mask_rcnn_r50_fpg-chn128_crop640_50e_coco-5c6ea10d.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg-chn128_crop640_50e_coco/20210223_025039.log.json) |
-| RetinaNet    | FPG         | 50e     | 20.8     | -              | 40.5   | -       |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/retinanet_r50_fpg_crop640_50e_coco.py) |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg_crop640_50e_coco/retinanet_r50_fpg_crop640_50e_coco-46fdd1c6.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg_crop640_50e_coco/20210225_143957.log.json) |
-| RetinaNet    | FPG-chn128  | 50e     | 19.9     | -              | 40.3   | -       |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/retinanet_r50_fpg-chn128_crop640_50e_coco.py) |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg-chn128_crop640_50e_coco/retinanet_r50_fpg-chn128_crop640_50e_coco-5cf33c76.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg-chn128_crop640_50e_coco/20210225_184328.log.json) |
+| Faster R-CNN | FPG         | 50e     | 20.0     | -              | 42.3   | -       |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/faster_rcnn_r50_fpg_crop640_50e_coco.py)        |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg_crop640_50e_coco/faster_rcnn_r50_fpg_crop640_50e_coco_20220311_011856-74109f42.pth) &#124;               [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg_crop640_50e_coco/faster_rcnn_r50_fpg_crop640_50e_coco_20220311_011856.log.json) |
+| Faster R-CNN | FPG-chn128  | 50e     | 11.9     | -              | 41.2   | -       |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/faster_rcnn_r50_fpg-chn128_crop640_50e_coco.py) |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg-chn128_crop640_50e_coco/faster_rcnn_r50_fpg-chn128_crop640_50e_coco_20220311_011857-9376aa9d.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg-chn128_crop640_50e_coco/faster_rcnn_r50_fpg-chn128_crop640_50e_coco_20220311_011857.log.json) |
+| Faster R-CNN | FPN         | 50e     | 20.0     | -              | 38.9   | -       |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/faster_rcnn_r50_fpn_crop640_50e_coco.py)        |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpn_crop640_50e_coco/faster_rcnn_r50_fpn_crop640_50e_coco_20220311_011857-be7c9f42.pth) &#124;               [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpn_crop640_50e_coco/faster_rcnn_r50_fpn_crop640_50e_coco_20220311_011857.log.json)  |
+| Mask R-CNN   | FPG         | 50e     | 23.2     | -              | 43.0   | 38.1    |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/mask_rcnn_r50_fpg_crop640_50e_coco.py)          |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg_crop640_50e_coco/mask_rcnn_r50_fpg_crop640_50e_coco_20220311_011857-233b8334.pth) &#124;                   [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg_crop640_50e_coco/mask_rcnn_r50_fpg_crop640_50e_coco_20220311_011857.log.json) |
+| Mask R-CNN   | FPG-chn128  | 50e     | 15.3     | -              | 41.7   | 37.1    |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/mask_rcnn_r50_fpg-chn128_crop640_50e_coco.py)   |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg-chn128_crop640_50e_coco/mask_rcnn_r50_fpg-chn128_crop640_50e_coco_20220311_011859-043c9b4e.pth) &#124;     [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg-chn128_crop640_50e_coco/mask_rcnn_r50_fpg-chn128_crop640_50e_coco_20220311_011859.log.json)  |
+| Mask R-CNN   | FPN         | 50e     | 23.2     | -              | 49.6   | 35.6    |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/mask_rcnn_r50_fpn_crop640_50e_coco.py)          |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpn_crop640_50e_coco/mask_rcnn_r50_fpn_crop640_50e_coco_20220311_011855-a756664a.pth) &#124;                   [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpn_crop640_50e_coco/mask_rcnn_r50_fpn_crop640_50e_coco_20220311_011855.log.json) |
+| RetinaNet    | FPG         | 50e     | 20.8     | -              | 40.5   | -       |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/retinanet_r50_fpg_crop640_50e_coco.py)          |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg_crop640_50e_coco/retinanet_r50_fpg_crop640_50e_coco_20220311_110809-b0bcf5f4.pth) &#124;                   [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg_crop640_50e_coco/retinanet_r50_fpg_crop640_50e_coco_20220311_110809.log.json) |
+| RetinaNet    | FPG-chn128  | 50e     | 19.9     | -              | 39.9   | -       |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/fpg/retinanet_r50_fpg-chn128_crop640_50e_coco.py)   |[model](https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg-chn128_crop640_50e_coco/retinanet_r50_fpg-chn128_crop640_50e_coco_20220313_104829-ee99a686.pth) &#124;     [log](https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg-chn128_crop640_50e_coco/retinanet_r50_fpg-chn128_crop640_50e_coco_20220313_104829.log.json) |
 
 **Note**: Chn128 means to decrease the number of channels of features and convs from 256 (default) to 128 in
 Neck and BBox Head, which can greatly decrease memory consumption without sacrificing much precision.

diff --git a/configs/fpg/metafile.yml b/configs/fpg/metafile.yml
@@ -27,8 +27,8 @@ Models:
       - Task: Object Detection
         Dataset: COCO
         Metrics:
-          box AP: 42.2
-    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg_crop640_50e_coco/faster_rcnn_r50_fpg_crop640_50e_coco-76220505.pth
+          box AP: 42.3
+    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg_crop640_50e_coco/faster_rcnn_r50_fpg_crop640_50e_coco_20220311_011856-74109f42.pth
 
   - Name: faster_rcnn_r50_fpg-chn128_crop640_50e_coco
     In Collection: Feature Pyramid Grids
@@ -41,7 +41,7 @@ Models:
         Dataset: COCO
         Metrics:
           box AP: 41.2
-    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg-chn128_crop640_50e_coco/faster_rcnn_r50_fpg-chn128_crop640_50e_coco-24257de9.pth
+    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/faster_rcnn_r50_fpg-chn128_crop640_50e_coco/faster_rcnn_r50_fpg-chn128_crop640_50e_coco_20220311_011857-9376aa9d.pth
 
   - Name: mask_rcnn_r50_fpg_crop640_50e_coco
     In Collection: Feature Pyramid Grids
@@ -53,12 +53,12 @@ Models:
       - Task: Object Detection
         Dataset: COCO
         Metrics:
-          box AP: 42.7
+          box AP: 43.0
       - Task: Instance Segmentation
         Dataset: COCO
         Metrics:
-          mask AP:  37.8
-    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg_crop640_50e_coco/mask_rcnn_r50_fpg_crop640_50e_coco-c5860453.pth
+          mask AP:  38.1
+    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg_crop640_50e_coco/mask_rcnn_r50_fpg_crop640_50e_coco_20220311_011857-233b8334.pth
 
   - Name: mask_rcnn_r50_fpg-chn128_crop640_50e_coco
     In Collection: Feature Pyramid Grids
@@ -74,8 +74,8 @@ Models:
       - Task: Instance Segmentation
         Dataset: COCO
         Metrics:
-          mask AP:  36.9
-    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg-chn128_crop640_50e_coco/mask_rcnn_r50_fpg-chn128_crop640_50e_coco-5c6ea10d.pth
+          mask AP:  37.1
+    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/mask_rcnn_r50_fpg-chn128_crop640_50e_coco/mask_rcnn_r50_fpg-chn128_crop640_50e_coco_20220311_011859-043c9b4e.pth
 
   - Name: retinanet_r50_fpg_crop640_50e_coco
     In Collection: Feature Pyramid Grids
@@ -88,7 +88,7 @@ Models:
         Dataset: COCO
         Metrics:
           box AP: 40.5
-    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg_crop640_50e_coco/retinanet_r50_fpg_crop640_50e_coco-46fdd1c6.pth
+    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg_crop640_50e_coco/retinanet_r50_fpg_crop640_50e_coco_20220311_110809-b0bcf5f4.pth
 
   - Name: retinanet_r50_fpg-chn128_crop640_50e_coco
     In Collection: Feature Pyramid Grids
@@ -100,5 +100,5 @@ Models:
       - Task: Object Detection
         Dataset: COCO
         Metrics:
-          box AP: 40.3
-    Weights: https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg-chn128_crop640_50e_coco/retinanet_r50_fpg-chn128_crop640_50e_coco-5cf33c76.pth
+          box AP: 39.9
+    Weights:  https://download.openmmlab.com/mmdetection/v2.0/fpg/retinanet_r50_fpg-chn128_crop640_50e_coco/retinanet_r50_fpg-chn128_crop640_50e_coco_20220313_104829-ee99a686.pth