[Docs] fix link issues

open-mmlab · Nov 23, 2021 · 2cda666 · 2cda666
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diff --git a/README.md b/README.md
@@ -107,7 +107,7 @@ If you find this project useful in your research, please consider cite:
 
 ## Contributing
 
-We appreciate all contributions to improve mmfewshot. Please refer to [CONTRIBUTING.md in MMFewShot](https://github.com/open-mmlab/mmfewshot/blob/main/.github/CONTRIBUTING.md) for the contributing guideline.
+We appreciate all contributions to improve mmfewshot. Please refer to [CONTRIBUTING.md](https://github.com/open-mmlab/mmfewshot/blob/main/.github/CONTRIBUTING.md) in MMFewShot for the contributing guideline.
 
 ## Acknowledgement
 

diff --git a/configs/classification/README.md b/configs/classification/README.md
@@ -6,4 +6,4 @@ If you're new of mmfewshot, you can check out [Get Started](https://mmfewshot.re
 and [Classification Tutorials](https://mmfewshot.readthedocs.io/en/latest/classification/index.html) to try out MMFewShot.
 
 ## Data Preparation
-Please follow [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/master/tools/data/classification) to prepare data.
+Please follow [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/main/tools/data/classification) to prepare data.
diff --git a/configs/detection/README.md b/configs/detection/README.md
@@ -5,4 +5,4 @@ If you're new of mmfewshot, you can check out [Get Started](https://mmfewshot.re
 and [Detection Tutorials](https://mmfewshot.readthedocs.io/en/latest/detection/index.html) to try out MMFewShot.
 
 ## Data Preparation
-Please follow [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/master/tools/data/detection) to prepare data.
+Please follow [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/main/tools/data/detection) to prepare data.
diff --git a/configs/detection/attention_rpn/README.md b/configs/detection/attention_rpn/README.md
@@ -46,9 +46,9 @@ dataset link is https://github.com/fanq15/Few-Shot-Object-Detection-Dataset.
 }
 ```
 
-**Note**: ALL the reported results use the data split released from [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/master/datasets/README.md) official repo.
+**Note**: ALL the reported results use the data split released from [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/main/datasets/README.md) official repo.
 Currently, each setting is only evaluated with one fixed few shot dataset.
-Please refer to [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/master/tools/data/detection) to get more details about the dataset and data preparation.
+Please refer to [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/main/tools/data/detection) to get more details about the dataset and data preparation.
 
 
 
@@ -87,7 +87,7 @@ bash ./tools/detection/dist_train.sh \
 
 **Note**:
 - The paper doesn't conduct experiments of VOC dataset.
-  Therefore, we use the VOC setting of [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/master/datasets/README.md) to evaluate the method.
+  Therefore, we use the VOC setting of [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/main/datasets/README.md) to evaluate the method.
 - Some implementation details should be noticed:
   - The training batch size are 8x2 for all the VOC experiments and 4x2 for all the COCO experiments(following the official repo).
   - Only the roi head will be trained during few shot fine-tuning for VOC experiments.
@@ -134,22 +134,22 @@ bash ./tools/detection/dist_train.sh \
 **Note**:
 - Following the original implementation, the training batch size are 4x2 for all the COCO experiments.
 - The official implementation use different COCO data split from TFA, and we report the results of both setting.
-  To reproduce the result following official data split (coco 17), please refer to [Data Preparation](https://github.com/open-mmlab/mmfewshot/tree/master/tools/data/detection/coco) to get more details about data preparation.
+  To reproduce the result following official data split (coco 17), please refer to [Data Preparation](https://github.com/open-mmlab/mmfewshot/tree/main/tools/data/detection/coco) to get more details about data preparation.
 - The performance of the base training and few shot setting can be unstable, even using the same random seed.
   To reproduce the reported few shot results, it is highly recommended using the released model for few shot fine-tuning.
 
 ### Base Training
 
 | Arch  | data source| Base mAP |  ckpt | log |
 | :------: | :-----------: | :------: | :------: |:------: |
-| [r50 c4](/configs/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_base-training.py) | [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/master/datasets/README.md) | 23.6 |[ckpt](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_base-training_20211102_003348-da28cdfd.pth) | [log](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_base-training.log.json) |
-| [r50 c4](/configs/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_official-base-training.py) | [official repo](https://github.com/fanq15/FewX/tree/master/datasets) | 24.0 | [ckpt](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_official-base-training_20211102_003347-f9e2dab0.pth) | [log](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_official-base-training.log.json) |
+| [r50 c4](/configs/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_base-training.py) | [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/main/datasets/README.md) | 23.6 |[ckpt](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_base-training_20211102_003348-da28cdfd.pth) | [log](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_base-training.log.json) |
+| [r50 c4](/configs/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_official-base-training.py) | [official repo](https://github.com/fanq15/FewX/tree/main/datasets) | 24.0 | [ckpt](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_official-base-training_20211102_003347-f9e2dab0.pth) | [log](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_official-base-training.log.json) |
 
 
 ### Few Shot Finetuning
 
 | Arch  | data source|  Shot | Novel mAP |  ckpt | log |
 | :--------------: |  :--------------: | :-----------: |  :------: |:------: |:------: |
-| [r50 c4](/configs/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_10shot-fine-tuning.py) | [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/master/datasets/README.md) | 10 | 9.2 | [ckpt](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_10shot-fine-tuning_20211103_003801-94ec8ada.pth) | [log](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_10shot-fine-tuning.log.json) |
-| [r50 c4](/configs/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_30shot-fine-tuning.py) | [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/master/datasets/README.md) | 30 | 14.8 | [ckpt](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_30shot-fine-tuning_20211103_010800-50611991.pth) | [log](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_30shot-fine-tuning.log.json) |
-| [r50 c4](/configs/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_10shot-fine-tuning.py) | [official repo](https://github.com/fanq15/FewX/tree/master/datasets) | 10 | 11.6 | [ckpt](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_official-10shot-fine-tuning_20211107_214729-6d046301.pth) | [log](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_official-10shot-fine-tuning.log.json) |
+| [r50 c4](/configs/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_10shot-fine-tuning.py) | [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/main/datasets/README.md) | 10 | 9.2 | [ckpt](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_10shot-fine-tuning_20211103_003801-94ec8ada.pth) | [log](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_10shot-fine-tuning.log.json) |
+| [r50 c4](/configs/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_30shot-fine-tuning.py) | [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/main/datasets/README.md) | 30 | 14.8 | [ckpt](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_30shot-fine-tuning_20211103_010800-50611991.pth) | [log](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_30shot-fine-tuning.log.json) |
+| [r50 c4](/configs/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_10shot-fine-tuning.py) | [official repo](https://github.com/fanq15/FewX/tree/main/datasets) | 10 | 11.6 | [ckpt](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_official-10shot-fine-tuning_20211107_214729-6d046301.pth) | [log](https://download.openmmlab.com/mmfewshot/detection/attention_rpn/coco/attention-rpn_r50_c4_4xb2_coco_official-10shot-fine-tuning.log.json) |
diff --git a/configs/detection/fsce/README.md b/configs/detection/fsce/README.md
@@ -42,9 +42,9 @@ loss (CPE loss). Our design outperforms current state-ofthe-art works in any sho
 }
 ```
 
-**Note**: ALL the reported results use the data split released from [fsce](https://github.com/ucbdrive/few-shot-object-detection/blob/master/datasets/README.md) official repo, unless stated otherwise.
+**Note**: ALL the reported results use the data split released from [fsce](https://github.com/ucbdrive/few-shot-object-detection/blob/main/datasets/README.md) official repo, unless stated otherwise.
 Currently, each setting is only evaluated with one fiNed few shot dataset.
-Please refer to [here](https://github.com/open-mmlab/mmfewshot/tree/master/tools/data/detection) to get more details about the dataset and data preparation.
+Please refer to [here](https://github.com/open-mmlab/mmfewshot/tree/main/tools/data/detection) to get more details about the dataset and data preparation.
 
 
 ## How to reproduce FSCE
@@ -100,7 +100,7 @@ bash ./tools/detection/dist_train.sh \
 
 
 **Note**:
-- All the base training configs is the same as [TFA](https://github.com/open-mmlab/mmfewshot/tree/master/configs/detection/fsce/README.md).
+- All the base training configs is the same as [TFA](https://github.com/open-mmlab/mmfewshot/tree/main/configs/detection/fsce/README.md).
   Therefore, the few shot fine-tuning can directly reuse the reshaped
   base model of fsce by creating a symlink or copying the whole checkpoint to the corresponding folder.
   Also, the released base training checkpoint is the same as the TFA, too.

diff --git a/configs/detection/fsdetview/README.md b/configs/detection/fsdetview/README.md
@@ -35,9 +35,9 @@ Our code and data are available at http://imagine.enpc.fr/~xiaoy/FSDetView/.
 }
 ```
 
-**Note**: ALL the reported results use the data split released from [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/master/datasets/README.md) official repo.
+**Note**: ALL the reported results use the data split released from [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/main/datasets/README.md) official repo.
 Currently, each setting is only evaluated with one fixed few shot dataset.
-Please refer to [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/master/tools/data/detection) to get more details about the dataset and data preparation.
+Please refer to [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/main/tools/data/detection) to get more details about the dataset and data preparation.
 
 ## How to reproduce FSDetView
 

diff --git a/configs/detection/meta_rcnn/README.md b/configs/detection/meta_rcnn/README.md
@@ -34,9 +34,9 @@ Code: https://yanxp.github.io/metarcnn.html.
 }
 ```
 
-**Note**: ALL the reported results use the data split released from [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/master/datasets/README.md) official repo.
+**Note**: ALL the reported results use the data split released from [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/main/datasets/README.md) official repo.
 Currently, each setting is only evaluated with one fixed few shot dataset.
-Please refer to [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/master/tools/data/detection) to get more details about the dataset and data preparation.
+Please refer to [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/main/tools/data/detection) to get more details about the dataset and data preparation.
 
 ## How to reproduce Meta RCNN
 

diff --git a/configs/detection/mpsr/README.md b/configs/detection/mpsr/README.md
@@ -33,9 +33,9 @@ Code is available at https://github.com/jiaxi-wu/MPSR.
 ```
 
 
-**Note**: ALL the reported results use the data split released from [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/master/datasets/README.md) official repo.
+**Note**: ALL the reported results use the data split released from [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/main/datasets/README.md) official repo.
 Currently, each setting is only evaluated with one fixed few shot dataset.
-Please refer to [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/master/tools/data/detection) to get more details about the dataset and data preparation.
+Please refer to [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/main/tools/data/detection) to get more details about the dataset and data preparation.
 
 ## How to reproduce MPSR
 Following the original implementation, it consists of 2 steps:

diff --git a/configs/detection/tfa/README.md b/configs/detection/tfa/README.md
@@ -37,9 +37,9 @@ The code as well as the pretrained models are available at https://github.com/uc
 
 
 
-**Note**: ALL the reported results use the data split released from [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/master/datasets/README.md) official repo.
+**Note**: ALL the reported results use the data split released from [TFA](https://github.com/ucbdrive/few-shot-object-detection/blob/main/datasets/README.md) official repo.
 Currently, each setting is only evaluated with one fixed few shot dataset.
-Please refer to [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/master/tools/data/detection) to get more details about the dataset and data preparation.
+Please refer to [DATA Preparation](https://github.com/open-mmlab/mmfewshot/tree/main/tools/data/detection) to get more details about the dataset and data preparation.
 
 
 ## How to reproduce TFA