[Fix] Update ddrnet readme (#3198)

open-mmlab · Jul 14, 2023 · 5fc1979 · 5fc1979
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diff --git a/configs/ddrnet/README.md b/configs/ddrnet/README.md
@@ -24,10 +24,10 @@ Semantic segmentation is a key technology for autonomous vehicles to understand
 
 ### Cityscapes
 
-| Method | Backbone      | Crop Size | Lr schd | Mem(GB) | Inf time(fps) | Device | mIoU  | mIoU(ms+flip) | config                                                                                                                                    | download                                                                                                                                                                                                                                                                                                                                                                                                             |
-| ------ | ------------- | --------- | ------- | ------- | ------------- | ------ | ----- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| DDRNet | DDRNet23-slim | 1024x1024 | 120000  | 1.70    | 85.85         | A100   | 77.84 | 80.15         | [config](https://github.com/open-mmlab/mmsegmentation/blob/main/configs/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230426_145312-6a5e5174.pth) \| [log](https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230426_145312.json) |
-| DDRNet | DDRNet23      | 1024x1024 | 120000  | 7.26    | 33.41         | A100   | 79.99 | 81.71         | [config](https://github.com/open-mmlab/mmsegmentation/blob/main/configs/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024.py)      | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230425_162633-81601db0.pth) \| [log](https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230425_162633.json)                     |
+| Method | Backbone      | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | Device | mIoU  | mIoU(ms+flip) | config                                                                                                                                    | download                                                                                                                                                                                                                                                                                                                                                                                                             |
+| ------ | ------------- | --------- | ------- | -------- | -------------- | ------ | ----- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| DDRNet | DDRNet23-slim | 1024x1024 | 120000  | 1.70     | 85.85          | A100   | 77.84 | 80.15         | [config](https://github.com/open-mmlab/mmsegmentation/blob/main/configs/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230426_145312-6a5e5174.pth) \| [log](https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230426_145312.json) |
+| DDRNet | DDRNet23      | 1024x1024 | 120000  | 7.26     | 33.41          | A100   | 79.99 | 81.71         | [config](https://github.com/open-mmlab/mmsegmentation/blob/main/configs/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024.py)      | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230425_162633-81601db0.pth) \| [log](https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230425_162633.json)                     |
 
 ## Notes
 

diff --git a/configs/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024.py b/configs/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024.py
@@ -10,7 +10,7 @@
     1.0023, 0.9539, 0.9843, 1.1116, 0.9037, 1.0865, 1.0955, 1.0865, 1.1529,
     1.0507
 ]
-
+checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/pretrain/ddrnet23s-in1kpre_3rdparty-1ccac5b1.pth'  # noqa
 crop_size = (1024, 1024)
 data_preprocessor = dict(
     type='SegDataPreProcessor',
@@ -31,9 +31,7 @@
         ppm_channels=128,
         norm_cfg=norm_cfg,
         align_corners=False,
-        init_cfg=dict(
-            type='Pretrained',
-            checkpoint='pretrained/ddrnet23s_in1k_mmseg.pth')),
+        init_cfg=dict(type='Pretrained', checkpoint=checkpoint)),
     decode_head=dict(
         type='DDRHead',
         in_channels=32 * 4,

diff --git a/configs/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024.py b/configs/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024.py
@@ -10,7 +10,7 @@
     1.0023, 0.9539, 0.9843, 1.1116, 0.9037, 1.0865, 1.0955, 1.0865, 1.1529,
     1.0507
 ]
-
+checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/pretrain/ddrnet23-in1kpre_3rdparty-9ca29f62.pth'  # noqa
 crop_size = (1024, 1024)
 data_preprocessor = dict(
     type='SegDataPreProcessor',
@@ -31,9 +31,7 @@
         ppm_channels=128,
         norm_cfg=norm_cfg,
         align_corners=False,
-        init_cfg=dict(
-            type='Pretrained',
-            checkpoint='pretrained/ddrnet23_in1k_mmseg.pth')),
+        init_cfg=dict(type='Pretrained', checkpoint=checkpoint)),
     decode_head=dict(
         type='DDRHead',
         in_channels=64 * 4,

diff --git a/configs/ddrnet/metafile.yaml b/configs/ddrnet/metafile.yaml
@@ -1,5 +1,5 @@
 Collections:
-- Name: ''
+- Name: DDRNet
   License: Apache License 2.0
   Metadata:
     Training Data:
@@ -11,4 +11,54 @@ Collections:
   README: configs/ddrnet/README.md
   Frameworks:
   - PyTorch
-Models: []
+Models:
+- Name: ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024
+  In Collection: DDRNet
+  Results:
+    Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 77.84
+      mIoU(ms+flip): 80.15
+  Config: configs/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024.py
+  Metadata:
+    Training Data: Cityscapes
+    Batch Size: 12
+    Architecture:
+    - DDRNet23-slim
+    - DDRNet
+    Training Resources: 2x A100 GPUS
+    Memory (GB): 1.7
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230426_145312-6a5e5174.pth
+  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230426_145312.json
+  Paper:
+    Title: Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation
+      of Road Scenes
+    URL: http://arxiv.org/abs/2101.06085
+  Code: ''
+  Framework: PyTorch
+- Name: ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024
+  In Collection: DDRNet
+  Results:
+    Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 79.99
+      mIoU(ms+flip): 81.71
+  Config: configs/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024.py
+  Metadata:
+    Training Data: Cityscapes
+    Batch Size: 12
+    Architecture:
+    - DDRNet23
+    - DDRNet
+    Training Resources: 2x A100 GPUS
+    Memory (GB): 7.26
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230425_162633-81601db0.pth
+  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024_20230425_162633.json
+  Paper:
+    Title: Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation
+      of Road Scenes
+    URL: http://arxiv.org/abs/2101.06085
+  Code: ''
+  Framework: PyTorch
diff --git a/tools/misc/publish_model.py b/tools/misc/publish_model.py
@@ -1,9 +1,12 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import argparse
 import subprocess
+from hashlib import sha256
 
 import torch
 
+BLOCK_SIZE = 128 * 1024
+
 
 def parse_args():
     parser = argparse.ArgumentParser(
@@ -14,6 +17,17 @@ def parse_args():
     return args
 
 
+def sha256sum(filename: str) -> str:
+    """Compute SHA256 message digest from a file."""
+    hash_func = sha256()
+    byte_array = bytearray(BLOCK_SIZE)
+    memory_view = memoryview(byte_array)
+    with open(filename, 'rb', buffering=0) as file:
+        for block in iter(lambda: file.readinto(memory_view), 0):
+            hash_func.update(memory_view[:block])
+    return hash_func.hexdigest()
+
+
 def process_checkpoint(in_file, out_file):
     checkpoint = torch.load(in_file, map_location='cpu')
     # remove optimizer for smaller file size
@@ -22,7 +36,7 @@ def process_checkpoint(in_file, out_file):
     # if it is necessary to remove some sensitive data in checkpoint['meta'],
     # add the code here.
     torch.save(checkpoint, out_file)
-    sha = subprocess.check_output(['sha256sum', out_file]).decode()
+    sha = sha256sum(in_file)
     final_file = out_file.rstrip('.pth') + f'-{sha[:8]}.pth'
     subprocess.Popen(['mv', out_file, final_file])