update metafile (#183)

configs/kie/sdmgr/metafile.yml

@@ -7,6 +7,7 @@ Collections:
     Training Resources: 1x GeForce GTX 1080 Ti
     Architecture:
       - UNet
+      - SDMGRHead
   Paper: https://arxiv.org/abs/2103.14470.pdf
   README: configs/kie/sdmgr/README.md
 

configs/textdet/dbnet/metafile.yml

@@ -4,6 +4,7 @@ Collections:
     Training Data: ICDAR2015
     Training Techniques:
       - SGD with Momentum
+      - Weight Decay
     Training Resources: 8x GeForce GTX 1080 Ti
     Architecture:
       - ResNet
@@ -18,7 +19,7 @@ Models:
     Metadata:
       Training Data: ICDAR2015
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
         Dataset: ICDAR2015
         Metrics:
           hmean-iou: 0.795
@@ -30,7 +31,7 @@ Models:
     Metadata:
       Training Data: ICDAR2015
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
         Dataset: ICDAR2015
         Metrics:
           hmean-iou: 0.830

configs/textdet/maskrcnn/metafile.yml

@@ -1,12 +1,14 @@
 Collections:
 - Name: Mask R-CNN
   Metadata:
-    Training Data: ICDARDataset
+    Training Data: ICDAR SCUT-CTW1500
     Training Techniques:
       - SGD with Momentum
+      - Weight Decay
     Training Resources: 8x GeForce GTX 1080 Ti
     Architecture:
-      - RoI Align
+      - ResNet
+      - FPN
       - RPN
   Paper: https://arxiv.org/pdf/1703.06870.pdf
   README: configs/textdet/maskrcnn/README.md
@@ -18,7 +20,7 @@ Models:
     Metadata:
       Training Data: CTW1500
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
         Dataset: CTW1500
         Metrics:
           hmean: 0.732
@@ -30,7 +32,7 @@ Models:
     Metadata:
       Training Data: ICDAR2015
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
         Dataset: ICDAR2015
         Metrics:
           hmean: 0.825
@@ -42,7 +44,7 @@ Models:
     Metadata:
       Training Data: ICDAR2017
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
         Dataset: ICDAR2017
         Metrics:
           hmean: 0.789

configs/textdet/panet/metafile.yml

@@ -1,7 +1,7 @@
 Collections:
 - Name: PANet
   Metadata:
-    Training Data: ICDARDataset
+    Training Data: ICDAR SCUT-CTW1500
     Training Techniques:
       - Adam
     Training Resources: 8x GeForce GTX 1080 Ti
@@ -18,7 +18,7 @@ Models:
     Metadata:
       Training Data: CTW1500
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
         Dataset: CTW1500
         Metrics:
           hmean-iou: 0.806
@@ -30,20 +30,8 @@ Models:
     Metadata:
       Training Data: ICDAR2015
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
         Dataset: ICDAR2015
         Metrics:
           hmean-iou: 0.791
     Weights: https://download.openmmlab.com/mmocr/textdet/panet/panet_r18_fpem_ffm_sbn_600e_icdar2015_20210219-42dbe46a.pth
-
-  - Name: panet_r50_fpem_ffm_600e_icdar2017
-    In Collection: PANet
-    Config: configs/textdet/panet/panet_r50_fpem_ffm_600e_icdar2017.py
-    Metadata:
-      Training Data: ICDAR2017
-    Results:
-      - Task: Instance Segmentation
-        Dataset: ICDAR2017
-        Metrics:
-          hmean-iou:
-    Weights:

configs/textdet/psenet/metafile.yml

@@ -1,7 +1,7 @@
 Collections:
 - Name: PSENet
   Metadata:
-    Training Data: ICDARDataset
+    Training Data: ICDAR SCUT-CTW1500
     Training Techniques:
       - Adam
     Training Resources: 8x GeForce GTX 1080 Ti
@@ -18,7 +18,7 @@ Models:
     Metadata:
       Training Data: CTW1500
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
         Dataset: CTW1500
         Metrics:
           hmean-iou: 0.784
@@ -30,7 +30,7 @@ Models:
     Metadata:
       Training Data: ICDAR2015
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
         Dataset: ICDAR2015
         Metrics:
           hmean-iou: 0.807
@@ -40,10 +40,10 @@ Models:
     In Collection: PSENet
     Config: configs/textdet/psenet/psenet_r50_fpnf_600e_icdar2015.py
     Metadata:
-      Training Data: ICDAR2017
+      Training Data: ICDAR2017 ICDAR2015
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
-        Dataset: ICDAR2017
+        Dataset: ICDAR2017 ICDAR2015
         Metrics:
           hmean-iou: 0.847
     Weights: https://download.openmmlab.com/mmocr/textdet/psenet/psenet_r50_fpnf_600e_icdar2015_pretrain-eefd8fe6.pth

configs/textdet/textsnake/metafile.yml

@@ -1,7 +1,7 @@
 Collections:
 - Name: TextSnake
   Metadata:
-    Training Data: ICDARDataset
+    Training Data: SCUT-CTW1500
     Training Techniques:
       - SGD with Momentum
     Training Resources: 8x GeForce GTX 1080 Ti
@@ -18,7 +18,7 @@ Models:
     Metadata:
       Training Data: CTW1500
     Results:
-      - Task: Instance Segmentation
+      - Task: Text Detection
         Dataset: CTW1500
         Metrics:
           hmean-iou: 0.817

configs/textrecog/crnn/metafile.yml

@@ -4,6 +4,8 @@ Collections:
     Training Data: OCRDataset
     Training Techniques:
       - Adadelta
+    Epochs: 5
+    Batch Size: 256
     Training Resources: 4x GeForce GTX 1080 Ti
     Architecture:
       - VeryDeepVgg
@@ -21,13 +23,13 @@ Models:
       - Task: Regular Text Recognition
         Dataset: IIIT5K
         Metrics:
-          acc: 80.5
+          word_acc: 80.5
       - Task: Regular Text Recognition
         Dataset: SVT
         Metrics:
-          acc: 81.5
+          word_acc: 81.5
       - Task: Regular Text Recognition
         Dataset: ICDAR2013
         Metrics:
-          acc: 86.5
+          word_acc: 86.5
     Weights: https://download.openmmlab.com/mmocr/textrecog/crnn/crnn_academic-a723a1c5.pth

configs/textrecog/nrtr/metafile.yml

@@ -4,6 +4,8 @@ Collections:
     Training Data: OCRDataset
     Training Techniques:
       - Adam
+    Epochs: 5
+    Batch Size: 8192
     Training Resources: 64x GeForce GTX 1080 Ti
     Architecture:
       - ResNet31OCR
@@ -24,27 +26,27 @@ Models:
       - Task: Regular Text Recognition
         Dataset: IIIT5K
         Metrics:
-          acc: 93.9
+          word_acc: 93.9
       - Task: Regular Text Recognition
         Dataset: SVT
         Metrics:
-          acc: 80.0
+          word_acc: 80.0
       - Task: Regular Text Recognition
         Dataset: ICDAR2013
         Metrics:
-          acc: 93.5
+          word_acc: 93.5
       - Task: Irregular Text Recognition
         Dataset: ICDAR2015
         Metrics:
-          acc: 74.5
+          word_acc: 74.5
       - Task: Irregular Text Recognition
         Dataset: SVTP
         Metrics:
-          acc: 78.5
+          word_acc: 78.5
       - Task: Irregular Text Recognition
         Dataset: CT80
         Metrics:
-          acc: 86.5
+          word_acc: 86.5
     Weights: https://download.openmmlab.com/mmocr/textrecog/nrtr/nrtr_r31_academic_20210406-954db95e.pth
 
   - Name: nrtr_r31_1by8_1by4_academic
@@ -58,25 +60,25 @@ Models:
       - Task: Regular Text Recognition
         Dataset: IIIT5K
         Metrics:
-          acc: 94.7
+          word_acc: 94.7
       - Task: Regular Text Recognition
         Dataset: SVT
         Metrics:
-          acc: 87.5
+          word_acc: 87.5
       - Task: Regular Text Recognition
         Dataset: ICDAR2013
         Metrics:
-          acc: 93.3
+          word_acc: 93.3
       - Task: Irregular Text Recognition
         Dataset: ICDAR2015
         Metrics:
-          acc: 75.1
+          word_acc: 75.1
       - Task: Irregular Text Recognition
         Dataset: SVTP
         Metrics:
-          acc: 78.9
+          word_acc: 78.9
       - Task: Irregular Text Recognition
         Dataset: CT80
         Metrics:
-          acc: 87.9
+          word_acc: 87.9
     Weights: https://download.openmmlab.com/mmocr/textrecog/nrtr/nrtr_r31_1by8_1by4_academic_20210406-ce16e7cc.pth

configs/textrecog/robust_scanner/metafile.yml

@@ -4,6 +4,8 @@ Collections:
     Training Data: OCRDataset
     Training Techniques:
       - Adam
+    Epochs: 5
+    Batch Size: 1024
     Training Resources: 16x GeForce GTX 1080 Ti
     Architecture:
       - ResNet31OCR
@@ -30,25 +32,25 @@ Models:
       - Task: Regular Text Recognition
         Dataset: IIIT5K
         Metrics:
-          acc: 95.1
+          word_acc: 95.1
       - Task: Regular Text Recognition
         Dataset: SVT
         Metrics:
-          acc: 89.2
+          word_acc: 89.2
       - Task: Regular Text Recognition
         Dataset: ICDAR2013
         Metrics:
-          acc: 93.1
+          word_acc: 93.1
       - Task: Irregular Text Recognition
         Dataset: ICDAR2015
         Metrics:
-          acc: 77.8
+          word_acc: 77.8
       - Task: Irregular Text Recognition
         Dataset: SVTP
         Metrics:
-          acc: 80.3
+          word_acc: 80.3
       - Task: Irregular Text Recognition
         Dataset: CT80
         Metrics:
-          acc: 90.3
+          word_acc: 90.3
     Weights: https://download.openmmlab.com/mmocr/textrecog/robustscanner/robustscanner_r31_academic-5f05874f.pth

configs/textrecog/sar/metafile.yml

@@ -5,6 +5,8 @@ Collections:
     Training Techniques:
       - Adam
     Training Resources: 48x GeForce GTX 1080 Ti
+    Epochs: 5
+    Batch Size: 3072
     Architecture:
       - ResNet31OCR
       - SAREncoder
@@ -30,27 +32,27 @@ Models:
       - Task: Regular Text Recognition
         Dataset: IIIT5K
         Metrics:
-          acc: 95.0
+          word_acc: 95.0
       - Task: Regular Text Recognition
         Dataset: SVT
         Metrics:
-          acc: 89.6
+          word_acc: 89.6
       - Task: Regular Text Recognition
         Dataset: ICDAR2013
         Metrics:
-          acc: 93.7
+          word_acc: 93.7
       - Task: Irregular Text Recognition
         Dataset: ICDAR2015
         Metrics:
-          acc: 79.0
+          word_acc: 79.0
       - Task: Irregular Text Recognition
         Dataset: SVTP
         Metrics:
-          acc: 82.2
+          word_acc: 82.2
       - Task: Irregular Text Recognition
         Dataset: CT80
         Metrics:
-          acc: 88.9
+          word_acc: 88.9
     Weights: https://download.openmmlab.com/mmocr/textrecog/crnn/crnn_academic-a723a1c5.pth
 
   - Name: sar_r31_sequential_decoder_academic
@@ -70,37 +72,25 @@ Models:
       - Task: Regular Text Recognition
         Dataset: IIIT5K
         Metrics:
-          acc: 95.2
+          word_acc: 95.2
       - Task: Regular Text Recognition
         Dataset: SVT
         Metrics:
-          acc: 88.7
+          word_acc: 88.7
       - Task: Regular Text Recognition
         Dataset: ICDAR2013
         Metrics:
-          acc: 92.4
+          word_acc: 92.4
       - Task: Irregular Text Recognition
         Dataset: ICDAR2015
         Metrics:
-          acc: 78.2
+          word_acc: 78.2
       - Task: Irregular Text Recognition
         Dataset: SVTP
         Metrics:
-          acc: 81.9
+          word_acc: 81.9
       - Task: Irregular Text Recognition
         Dataset: CT80
         Metrics:
-          acc: 89.6
+          word_acc: 89.6
     Weights: https://download.openmmlab.com/mmocr/textrecog/sar/sar_r31_sequential_decoder_academic-d06c9a8e.pth
-
-  - Name: sar_r31_parallel_decoder_chinese
-    In Collection: SAR
-    Config: configs/textrecog/sar/sar_r31_parallel_decoder_chinese.py
-    Metadata:
-      Training Data:
-    Results:
-      - Task:
-        Dataset:
-        Metrics:
-          acc:
-    Weights: https://download.openmmlab.com/mmocr/textrecog/sar/sar_r31_parallel_decoder_chineseocr_20210507-b4be8214.pth

configs/textrecog/seg/metafile.yml

@@ -1,9 +1,11 @@
 Collections:
-- Name: SEG
+- Name: SegOCR
   Metadata:
     Training Data: mixture
     Training Techniques:
       - Adam
+    Epochs: 5
+    Batch Size: 64
     Training Resources: 4x GeForce GTX 1080 Ti
     Architecture:
       - ResNet31OCR
@@ -13,7 +15,7 @@ Collections:
 
 Models:
   - Name: seg_r31_1by16_fpnocr_academic
-    In Collection: SEG
+    In Collection: SegOCR
     Config: configs/textrecog/seg/seg_r31_1by16_fpnocr_academic.py
     Metadata:
       Training Data: SynthText
@@ -21,17 +23,17 @@ Models:
       - Task: Regular Text Recognition
         Dataset: IIIT5K
         Metrics:
-          acc: 90.9
+          word_acc: 90.9
       - Task: Regular Text Recognition
         Dataset: SVT
         Metrics:
-          acc: 81.8
+          word_acc: 81.8
       - Task: Regular Text Recognition
         Dataset: ICDAR2013
         Metrics:
-          acc: 90.7
+          word_acc: 90.7
       - Task: Irregular Text Recognition
         Dataset: CT80
         Metrics:
-          acc: 80.9
+          word_acc: 80.9
     Weights: https://download.openmmlab.com/mmocr/textrecog/seg/seg_r31_1by16_fpnocr_academic-72235b11.pth

configs/textrecog/tps/metafile.yml

@@ -1,9 +1,11 @@
 Collections:
-- Name: TPS
+- Name: TPS-CRNN
   Metadata:
     Training Data: OCRDataset
     Training Techniques:
       - Adadelta
+    Epochs: 5
+    Batch Size: 256
     Training Resources: 4x GeForce GTX 1080 Ti
     Architecture:
       - TPSPreprocessor
@@ -25,25 +27,25 @@ Models:
       - Task: Regular Text Recognition
         Dataset: IIIT5K
         Metrics:
-          acc: 80.8
+          word_acc: 80.8
       - Task: Regular Text Recognition
         Dataset: SVT
         Metrics:
-          acc: 81.3
+          word_acc: 81.3
       - Task: Regular Text Recognition
         Dataset: ICDAR2013
         Metrics:
-          acc: 85.0
+          word_acc: 85.0
       - Task: Irregular Text Recognition
         Dataset: ICDAR2015
         Metrics:
-          acc: 59.6
+          word_acc: 59.6
       - Task: Irregular Text Recognition
         Dataset: SVTP
         Metrics:
-          acc: 68.1
+          word_acc: 68.1
       - Task: Irregular Text Recognition
         Dataset: CT80
         Metrics:
-          acc: 53.8
+          word_acc: 53.8
     Weights: https://download.openmmlab.com/mmocr/textrecog/tps/crnn_tps_academic_dataset_20210510-d221a905.pth