update ocrnet doc

configs/ocnet_w18_cityscapes.yaml → configs/ocrnet_w18_cityscapes.yaml

@@ -27,7 +27,7 @@ FREEZE:
     MODEL_FILENAME: "model"
     PARAMS_FILENAME: "params"
 MODEL:
-    MODEL_NAME: "ocnet"
+    MODEL_NAME: "ocrnet"
     DEFAULT_NORM_TYPE: "bn"
     HRNET:
         STAGE2:
@@ -41,12 +41,12 @@ MODEL:
         OCR_KEY_CHANNELS: 256
     MULTI_LOSS_WEIGHT: [1.0, 1.0]
 TRAIN:
-    PRETRAINED_MODEL_DIR: u"./pretrained_model/ocnet_w18_cityscape/best_model"
-    MODEL_SAVE_DIR: "output/ocnet_w18_bn_cityscapes"
+    PRETRAINED_MODEL_DIR: u"./pretrained_model/ocrnet_w18_cityscape/best_model"
+    MODEL_SAVE_DIR: "output/ocrnet_w18_bn_cityscapes"
     SNAPSHOT_EPOCH: 1
     SYNC_BATCH_NORM: True
 TEST:
-    TEST_MODEL: "output/ocnet_w18_bn_cityscapes/first"
+    TEST_MODEL: "output/ocrnet_w18_bn_cityscapes/first"
 SOLVER:
     LR: 0.01
     LR_POLICY: "poly"

docs/model_zoo.md

@@ -68,6 +68,6 @@ train数据集合为Cityscapes训练集合，测试为Cityscapes的验证集合
 | PSPNet/bn | Cityscapes |[pspnet101_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/pspnet101_cityscapes.tgz) |16|false| 0.7734 |
 | HRNet_W18/bn | Cityscapes |[hrnet_w18_bn_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/hrnet_w18_bn_cityscapes.tgz) | 4 | false | 0.7936 |
 | Fast-SCNN/bn | Cityscapes |[fast_scnn_cityscapes.tar](https://paddleseg.bj.bcebos.com/models/fast_scnn_cityscape.tar) | 32 | false | 0.6964 |
-| OCNet/bn | Cityscapes |[ocnet_w18_bn_cityscapes.tar.gz](https://paddleseg.bj.bcebos.com/models/ocnet_w18_bn_cityscapes.tar.gz) | 4 | false | 0.8023 |
+| OCRNet/bn | Cityscapes |[ocrnet_w18_bn_cityscapes.tar.gz](https://paddleseg.bj.bcebos.com/models/ocrnet_w18_bn_cityscapes.tar.gz) | 4 | false | 0.8023 |
 
 测试环境为python 3.7.3，v100，cudnn 7.6.2。

pdseg/models/model_builder.py

@@ -26,7 +26,7 @@ from loss import multi_dice_loss
 from loss import multi_bce_loss
 from lovasz_losses import lovasz_hinge
 from lovasz_losses import lovasz_softmax
-from models.modeling import deeplab, unet, icnet, pspnet, hrnet, fast_scnn,ocnet
+from models.modeling import deeplab, unet, icnet, pspnet, hrnet, fast_scnn, ocrnet
 
 
 class ModelPhase(object):
@@ -85,8 +85,8 @@ def seg_model(image, class_num):
         logits = hrnet.hrnet(image, class_num)
     elif model_name == 'fast_scnn':
         logits = fast_scnn.fast_scnn(image, class_num)
-    elif model_name == 'ocnet':
-        logits = ocnet.ocnet(image, class_num)
+    elif model_name == 'ocrnet':
+        logits = ocrnet.ocrnet(image, class_num)
     else:
         raise Exception(
             "unknow model name, only support unet, deeplabv3p, icnet, pspnet, hrnet, fast_scnn"

pretrained_model/download_model.py

@@ -96,8 +96,8 @@ model_urls = {
     "https://paddleseg.bj.bcebos.com/models/hrnet_w18_bn_cityscapes.tgz",
     "fast_scnn_cityscapes":
     "https://paddleseg.bj.bcebos.com/models/fast_scnn_cityscape.tar",
-    "ocnet_w18_bn_cityscapes":
-    "https://paddleseg.bj.bcebos.com/models/ocnet_w18_bn_cityscapes.tar.gz",
+    "ocrnet_w18_bn_cityscapes":
+    "https://paddleseg.bj.bcebos.com/models/ocrnet_w18_bn_cityscapes.tar.gz",
 }
 
 if __name__ == "__main__":