update ppl benchmark (open-mmlab#293)

humu789 · Dec 17, 2021 · 31e8aed · 31e8aed
1 parent 1ed55f8
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Showing 2 changed files with 12 additions and 8 deletions.
diff --git a/docs/benchmark.md b/docs/benchmark.md
@@ -799,7 +799,7 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
     <td class="tg-baqh">72.36</td>
     <td class="tg-baqh">72.35</td>
     <td class="tg-baqh">74.19</td>
-    <td class="tg-baqh">-</td>
+    <td class="tg-baqh">72.35</td>
     <td class="tg-0lax">$MMSEG_DIR/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py</td>
   </tr>
   <tr>
@@ -811,7 +811,7 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
     <td class="tg-baqh">78.26</td>
     <td class="tg-baqh">78.24</td>
     <td class="tg-baqh">77.97</td>
-    <td class="tg-baqh">-</td>
+    <td class="tg-baqh">78.09</td>
     <td class="tg-0lax">$MMSEG_DIR/configs/pspnet/pspnet_r50-d8_512x1024_80k_cityscapes.py</td>
   </tr>
   <tr>
@@ -823,10 +823,9 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
     <td class="tg-baqh">79.12</td>
     <td class="tg-baqh">79.12</td>
     <td class="tg-baqh">78.96</td>
-    <td class="tg-baqh">-</td>
+    <td class="tg-baqh">79.12</td>
     <td class="tg-0lax">$MMSEG_DIR/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py</td>
   </tr>
-  <tr>
     <td class="tg-baqh">deeplabv3+</td>
     <td class="tg-baqh">Cityscapes</td>
     <td class="tg-baqh">mIoU</td>
@@ -835,10 +834,10 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
     <td class="tg-baqh">79.6</td>
     <td class="tg-baqh">79.6</td>
     <td class="tg-baqh">79.43</td>
-    <td class="tg-baqh">-</td>
+    <td class="tg-baqh">79.6</td>
     <td class="tg-0lax">$MMSEG_DIR/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py</td>
   </tr>
-  <tr>
+  </tr>
     <td class="tg-baqh">Fast-SCNN</td>
     <td class="tg-baqh">Cityscapes</td>
     <td class="tg-baqh">mIoU</td>
@@ -847,7 +846,7 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
     <td class="tg-baqh">70.93</td>
     <td class="tg-baqh">70.92</td>
     <td class="tg-baqh">66.0</td>
-    <td class="tg-baqh">-</td>
+    <td class="tg-baqh">70.92</td>
     <td class="tg-0lax">$MMSEG_DIR/configs/fastscnn/fast_scnn_lr0.12_8x4_160k_cityscapes.py</td>
   </tr>
 </tbody>

diff --git a/mmdeploy/codebase/mmseg/deploy/mmsegmentation.py b/mmdeploy/codebase/mmseg/deploy/mmsegmentation.py
@@ -125,6 +125,7 @@ def single_gpu_test(model: torch.nn.Module,
                         data_loader: DataLoader,
                         show: bool = False,
                         out_dir: Optional[str] = None,
+                        pre_eval: bool = True,
                         **kwargs):
         """Run test with single gpu.
 
@@ -134,10 +135,14 @@ def single_gpu_test(model: torch.nn.Module,
             show (bool): Specifying whether to show plotted results. Defaults
                 to `False`.
             out_dir (str): A directory to save results, defaults to `None`.
+            pre_eval (bool): Use dataset.pre_eval() function to generate
+                pre_results for metric evaluation. Mutually exclusive with
+                efficient_test and format_results. Default: False.
 
         Returns:
             list: The prediction results.
         """
         from mmseg.apis import single_gpu_test
-        outputs = single_gpu_test(model, data_loader, show, out_dir, **kwargs)
+        outputs = single_gpu_test(
+            model, data_loader, show, out_dir, pre_eval=pre_eval, **kwargs)
         return outputs