Update google drive links

qiaoliang6 · qiaoliang6 · commit 10cf40d5ab11 · 2021-07-26T17:50:08.000+08:00
diff --git a/demo/text_detection/east/readme.md b/demo/text_detection/east/readme.md
@@ -46,7 +46,7 @@ Results on various datasets and trained models download:
 | ICDAR2015      | QUAD    | ResNet-50 |  ImageNet    | (L-1280, S-720) |  71.43   | 79.20  | 75.11 | [config](config/east_r50_quad.py), [pth](https://pan.baidu.com/s/1uAaXN6iCVfIKniJPID6K5Q ) (Access Code: lgu5 )         |
 | ICDAR2015      | QUAD    | ResNet-50 |  ImageNet    | (L-1600, S-900) |  71.52   | 79.30  | 75.21 | [config](config/east_r50_quad.py), [pth](https://pan.baidu.com/s/1uAaXN6iCVfIKniJPID6K5Q ) (Access Code: lgu5 )         |
 
-> Note: Models are stored in BaiduYunPan.
+> Note: Models are stored in BaiduYunPan, and can also be downloaded from [Google Drive](https://drive.google.com/drive/folders/1dWZN2uMKMgJalHcBHWvpAuku1eyXq-Jj?usp=sharing)
 
 ## Citation
 
diff --git a/demo/text_detection/mask_rcnn_det/readme.md b/demo/text_detection/mask_rcnn_det/readme.md
@@ -47,7 +47,7 @@ Results on various datasets and trained models download:
 | SCUT-CTW1500 (considers NOT CARE)  | ResNet-101| COCO   |  L-1080|   | 87.24     | 79.22  | 83.04 | -        |
 | ICDAR 2015            | ResNet-50 | COCO       |  L-1600| 89.19     | 77.03     | 82.67 |[config](config/mask_rcnn_r101_ctw.py), [pth](https://pan.baidu.com/s/1VzKduWXSqMhmvX6YFmlCJQ) (Access Code: k17n)|
 | ICDAR 2015            | ResNet-101 | COCO       | L-1600| 90.43     | 75.11     | 82.06|[config](config/mask_rcnn_r101_ctw.py), [pth](https://pan.baidu.com/s/1VzKduWXSqMhmvX6YFmlCJQ) (Access Code: k17n)|
-> Note: Models are stored in BaiduYunPan.
+> Note: Models are stored in BaiduYunPan, and can also be downloaded from [Google Drive](https://drive.google.com/drive/folders/1w2cwYiuneb2qRM3e-82pylIUqGr8hs0d?usp=sharing)
 > Pretrained model on COCO can be download in the repository of [mmdetection/mask_rcnn](https://github.com/open-mmlab/mmdetection/tree/master/configs/mask_rcnn).
 
 ## Citation
diff --git a/demo/text_detection/text_perceptron_det/readme.md b/demo/text_detection/text_perceptron_det/readme.md
@@ -52,7 +52,7 @@ Results on various datasets and trained models download:
 | SCUT-CTW1500  (considers NOT CARE) | ResNet-50                | SynthText+IC17, [pth](https://pan.baidu.com/s/17lnY0shAtvDlHZXz_E1vSQ) (Access Code: 8dn0)|   L-1250 | 87.5 | 84.5 | 85.9| [config](config/tp_det_r50.py), [pth](https://pan.baidu.com/s/1dZ2Pa-I0JE3bNPUDGL70wA)(Access Code: duuo)|
 > The original SCUT-CTW1500 was released to only support text detection task, where all text instances are considered. When this dataset was used in text spotting task, some instances (blurred or in other languages) were labeled as not care.   
 
-> Note: Models are stored in BaiduYunPan.
+> Note: Models are stored in BaiduYunPan, and can also be downloaded from [Google Drive](https://drive.google.com/drive/folders/1BuIt7fhzCh3kFXEVbtR1MS-kYVXmjsNq?usp=sharing)
 
 ## Citation
 
diff --git a/demo/text_ie/trie/readme.md b/demo/text_ie/trie/readme.md
@@ -34,7 +34,7 @@ Results on various datasets and trained models can be download as follows:
 | :---------: | :------: | :--------: | :---------: | :--------: | :------: | :---: |
 | Wildreceipt | ResNet50 |  ImageNet  | (512, 512)  | (512, 512) |  87.08   |  [config](./configs/wildreceipt_gt_trie.py), [pth](https://pan.baidu.com/s/1TO8dtZ7HrCQrycOLAy5frg) (Access Code:parf)     |
 
-> Note: Models are stored in BaiduYunPan.
+> Note: Models are stored in BaiduYunPan, and can also be downloaded from [Google Drive](https://drive.google.com/drive/folders/1RWZJsYDYTzH7PjL48bbjBgy2BCfe0WRn?usp=sharing)
 
 
 ## Citation
diff --git a/demo/text_recognition/__base__/readme.md b/demo/text_recognition/__base__/readme.md
@@ -40,8 +40,7 @@ This code repository contains an implementation of (CRNN:[An End-to-End Trainabl
 
 ## 3. Getting Started
 ### Preparation
-A quick start can directly use the lmdb-formatted dataset [data_lmdb_release.zip](http://) contains the full benchmarks for scene text recognition tasks as belows.
-
+A quick start is to use above lmdb-formatted datasets that contain the full benchmarks for scene text recognition tasks as belows.
 ```
 Data Type: LMDB
 
@@ -125,7 +124,7 @@ bash ./train.sh
         <td><center> 78.9 </center></td>
         <td><center> 80.6 </center></td>
         <td><center><p><a href="./res32_bilstm_ctc.py"> Config </a></p></center>
-        <td><center><p><a href="https://pan.baidu.com/s/1Ad91GOxnFm3XcGZJoR8XAQ"> pth </a>(Code:yc98)</p></center></td>
+        <td><center><p> pth <a href="https://pan.baidu.com/s/1Ad91GOxnFm3XcGZJoR8XAQ">BaiduYunPan </a>(Code:yc98), <a href="https://drive.google.com/drive/folders/1VNYKzqSQ1tNPfBvglmfjDfaNWR6RQSFj?usp=sharing">Google Drive </a></p></center></td>
 	<tr>
     <tr>
 		<td><center> Attention(Report) </center></td>
@@ -150,10 +149,9 @@ bash ./train.sh
         <td><center> 82.5 </center></td>
         <td><center> 81.9 </center></td>
         <td><center><p><a href="./res32_bilstm_attn.py"> Config </a></p></center>
-        <td><center><p><a href="https://pan.baidu.com/s/1B5pBYYXTgdXNQNfue_ET9A"> pth  </a>(Code:mdtf)</p></center></td>
+        <td><center><p> pth <a href="https://pan.baidu.com/s/1B5pBYYXTgdXNQNfue_ET9A">BaiduYunPan </a> (Code:mdtf),  <a href="https://drive.google.com/drive/folders/1ZL_wyWq2AFURRN5Bcj6EN85-71b7MXVr?usp=sharing"> Google Drive</a> </p></center></td>
 	<tr>
 <table>
-> Note: Models are stored in BaiduYunPan.
 
 
 ### Visualization
diff --git a/demo/text_recognition/ace/readme.md b/demo/text_recognition/ace/readme.md
@@ -42,7 +42,7 @@ Aggregation cross-entropy (ACE: [Aggregation Cross-Entropy for Sequence Recognit
 
 ## 3. Getting Started
 ### Preparation
-A quick start can directly use the lmdb-formatted dataset [data_lmdb_release.zip](http://) contains the full benchmarks for scene text recognition tasks as belows.
+A quick start is to use above lmdb-formatted datasets that contain the full benchmarks for scene text recognition tasks as belows.
 
 ```
 Data Type: LMDB
@@ -121,7 +121,7 @@ bash ./test_ace.sh
         <td><center> 71.9 </center></td>
         <td><center> 77.1 </center></td>
         <td><center><p><a href="./configs/res32_ace.py"> Config </a></p></center></td>
-        <td><center><p><a href="https://pan.baidu.com/s/1j__kSmlFLYZXGabsqpZKQQ"> pth </a>(Code:brey)</p></center></td>
+        <td><center><p> pth<a href="https://pan.baidu.com/s/1j__kSmlFLYZXGabsqpZKQQ"> BaiduYunPan </a>(Code:brey),<a href="https://drive.google.com/drive/folders/1gplNfTC4bbiAsQVDSnlttIZ0F1ASsZbj?usp=sharing"> Google Drive </a> </p></center></td>
 	<tr>
 <table>
 
diff --git a/demo/text_recognition/rflearning/readme.md b/demo/text_recognition/rflearning/readme.md
@@ -42,7 +42,7 @@ This code repository contains an implementation of (RF-Learning: [Reciprocal Fea
 ## 3. Getting Started
 
 ### Preparation
-A quick start can directly use the lmdb-formatted dataset [data_lmdb_release.zip](http://) contains the full benchmarks for scene text recognition tasks as belows.
+A quick start is to use above lmdb-formatted datasets that contain the full benchmarks for scene text recognition tasks as belows.
 
 ```
 Data Type: LMDB
@@ -126,7 +126,7 @@ bash ./train.sh
         <td><center> 86.7 </center></td>
         <td><center> 88.2 </center></td>
         <td><center><p><a href="./configs/res32_bilstm_visual.py"> Config </a></p></center></td>
-        <td><center><p><a href="https://pan.baidu.com/s/1nS4-s6TZdZM0LYXLQHy-TQ"> pth </a> (Code:opjk)</p></center></td>
+        <td><center><p> pth <a href="https://pan.baidu.com/s/1nS4-s6TZdZM0LYXLQHy-TQ">BaiduYunPan </a> (Code:opjk),  <a href="https://drive.google.com/drive/folders/15n5b5XptYtvgZ3MfBpVpNoyNviJuknPb?usp=sharing">Google Drive </a> </p></center></td>
 	<tr>
     <tr>
         <td><center> RF-Learning total(Report) </center></td>
@@ -150,7 +150,7 @@ bash ./train.sh
         <td><center> 82.0 </center></td>
         <td><center> 84.7 </center></td>
         <td><center><p><a href="./configs/res32_bilstm_attn.py"> Config </a></p></center></td>
-        <td><center><p><a href="https://pan.baidu.com/s/1nS4-s6TZdZM0LYXLQHy-TQ"> pth </a> (Code:opjk) </p></center></td>
+         <td><center><p> pth <a href="https://pan.baidu.com/s/1nS4-s6TZdZM0LYXLQHy-TQ">BaiduYunPan </a> (Code:opjk),  <a href="https://drive.google.com/drive/folders/1l-49Gl-R1nW5MYjqoEjvFgvibJbISSYx?usp=sharing">Google Drive </a> </p></center></td>
 	<tr>
 <table>
 
diff --git a/demo/text_recognition/spin/readme.md b/demo/text_recognition/spin/readme.md
@@ -40,7 +40,7 @@ This code repository contains an implementation of (SPIN: [SPIN: Structure-Prese
 
 ## 3 Getting Started
 ### Preparation
-A quick start can directly use the lmdb-formatted dataset [data_lmdb_release.zip](http://) contains the full benchmarks for scene text recognition tasks as belows.
+A quick start is to use above lmdb-formatted datasets that contain the full benchmarks for scene text recognition tasks as belows.
 
 ```
 Data Type: LMDB
@@ -132,7 +132,7 @@ bash ./test_scripts/test_gaspin.sh
         <td><center> 80.9 </center></td>
         <td><center> 83.0 </center></td>
         <td><center><p><a href="./configs/affine_res32_attn.py"> Config </a></p></center></td>
-        <td><center><p><a href="https://pan.baidu.com/s/1vnpzAfRYZ-Yuf3FzqhSNTg"> pth </a> (Code:1lcp )</p></center></td>
+        <td><center><p> pth <a href="https://pan.baidu.com/s/1jt8kb71GP1nrLa1KzRSwFw">BaiduYunPan </a> (Code:4les), <a href="https://drive.google.com/drive/folders/17kJNCRZ79GiVJIDvxcSBTDBmtmp5q-hh?usp=sharing" > Google Drive</a></p></center></td>
 	<tr>
     <tr>
 		<td><center> TPS(Report) </center></td>
@@ -156,8 +156,8 @@ bash ./test_scripts/test_gaspin.sh
         <td><center> 82.6 </center></td>
         <td><center> 83.7 </center></td>
         <td><center><p><a href="./configs/tps_res32_attn.py"> Config </a></p></center></td>
-        <td><center><p><a href="https://pan.baidu.com/s/1vnpzAfRYZ-Yuf3FzqhSNTg"> pth </a>(Code:1lcp)</p>
-            </center></td>
+        <td><center><p> pth <a href="https://pan.baidu.com/s/1H7zr3Kh83Sjpd9SQ5plS7w">BaiduYunPan </a> (Code:a0tx), <a href="https://drive.google.com/drive/folders/1aF4L_0Wp5An_ogC_XdAgYi6CbODvYG4X?usp=sharing" > Google Drive</a></p></center></td>
+      
 	<tr>
     <tr>
 		<td><center> SPIN(Report) </center></td>
@@ -182,8 +182,8 @@ bash ./test_scripts/test_gaspin.sh
         <td><center> 83.7 </center></td>
         <td><center>
             <p><a href="./configs/spin_res32_attn.py"> Config </a></p></center></td>
-        <td><center><p><a href="https://pan.baidu.com/s/1vnpzAfRYZ-Yuf3FzqhSNTg"> pth </a>(Code:1lcp)</p>
-            </center></td>
+        <td><center><p> pth <a href="https://pan.baidu.com/s/17mw2FvNhscABOC7drkqT9g">BaiduYunPan </a> (Code:1vyj), <a href="https://drive.google.com/drive/folders/1AUK1Wt5NbMSeSvl3ttfqfbwl9cRkcetp?usp=sharing" > Google Drive</a></p></center></td>
+     
 	<tr>
     <tr>
 		<td><center> GA-SPIN(Report) </center></td>
@@ -208,8 +208,7 @@ bash ./test_scripts/test_gaspin.sh
         <td><center> 84.7 </center></td>
         <td><center>
             <p><a href="./configs/gaspin_res32_attn.py"> Config </a></p></center></td>
-        <td><center><p><a href="https://pan.baidu.com/s/1pwRDQaJdoVIDwE5nYOiggw"> pth </a>(Code:sebs)</p>
-            </center></td>
+       <td><center><p> pth <a href="https://pan.baidu.com/s/1paseZdViDSAnxoK8A-FPlQ">BaiduYunPan </a> (Code:o4ob), <a href="https://drive.google.com/drive/folders/1-yAU-BIyqk3ouRAkCTf00Gx12apkjNfi?usp=sharing" > Google Drive</a></p></center></td>
 	<tr>
 <table>
 
diff --git a/demo/text_spotting/mango/readme.md b/demo/text_spotting/mango/readme.md
@@ -249,7 +249,7 @@ Results on various datasets and trained models download:
 		<td><p><a href="./configs/mango_r101_ete_finetune.py">cfg </a>, <a href="https://pan.baidu.com/s/1NI1_Nl8gSDh9zTX-lof9OA">pth </a> (Access Code: 6rz6)</p></td>
 	</tr>
 </table>
-> Note: Models are stored in BaiduYunPan.
+> Note: Models are stored in BaiduYunPan, and can also be downloaded from [Google Drive](https://drive.google.com/drive/folders/1VLVbdEabCSZ54dNLvbBsMaXV2nrGrx9G?usp=sharing)
 
 
 ## Citation
diff --git a/demo/text_spotting/mask_rcnn_spot/readme.md b/demo/text_spotting/mask_rcnn_spot/readme.md
@@ -155,7 +155,7 @@ Results on various datasets and trained models download:
 		<td><p><a href="./configs/mask_rcnn_spotter_finetune.py">cfg </a>, <a href="https://pan.baidu.com/s/1TVmG8hh9r9mWfdaNynkqSg">pth </a> (Access Code: 7npy)</p></td>
 	</tr>
 </table>
-> Note: Models are stored in BaiduYunPan.
+> Note: Models are stored in BaiduYunPan, and can also be downloaded from [Google Drive](https://drive.google.com/drive/folders/1tFtLw1Lm6Lc3ve_wNwrmedJ5dS0HPSh9?usp=sharing)
 
 
 ## Citation:
diff --git a/readme.md b/readme.md
@@ -45,7 +45,7 @@ To date, davarocr contains the following algorithms:
 
 - YORO (to be released) (ACM MM 2019)
 
-- FREE (to be released) (TIP 2020)
+- FREE (to be released) (TIP 2021)
 
 ***Layout Recognition***
 
@@ -82,6 +82,7 @@ Going to the specific algorithm's directory to see more details.
 ## Problem solution and collection
 For the problems existing in the process of installation and researching, we will reasonably collect them and provide corresponding solutions. Please refer to [FAQ.md](./docs/FAQ.md) for details. 
 
+
 ## Changelog
 
 DavarOCR v0.1.0 was released in 23/07/2021.
