add default result visualization for base detector

mmdet/core/eval/class_names.py

@@ -95,7 +95,7 @@ def get_classes(dataset):
 
     if mmcv.is_str(dataset):
         if dataset in alias2name:
-            labels = eval(alias2name[dataset] + '_labels()')
+            labels = eval(alias2name[dataset] + '_classes()')
         else:
             raise ValueError('Unrecognized dataset: {}'.format(dataset))
     else:

mmdet/models/detectors/base.py

 import logging
 from abc import ABCMeta, abstractmethod
 
+import mmcv
+import numpy as np
 import torch
 import torch.nn as nn
 
+from mmdet.core import tensor2imgs, get_classes
+
 
 class BaseDetector(nn.Module):
     """Base class for detectors"""
@@ -66,3 +70,38 @@ class BaseDetector(nn.Module):
             return self.forward_train(img, img_meta, **kwargs)
         else:
             return self.forward_test(img, img_meta, **kwargs)
+
+    def show_result(self,
+                    data,
+                    result,
+                    img_norm_cfg,
+                    dataset='coco',
+                    score_thr=0.3):
+        img_tensor = data['img'][0]
+        img_metas = data['img_meta'][0].data[0]
+        imgs = tensor2imgs(img_tensor, **img_norm_cfg)
+        assert len(imgs) == len(img_metas)
+
+        if isinstance(dataset, str):
+            class_names = get_classes(dataset)
+        elif isinstance(dataset, list):
+            class_names = dataset
+        else:
+            raise TypeError('dataset must be a valid dataset name or a list'
+                            ' of class names, not {}'.format(type(dataset)))
+
+        for img, img_meta in zip(imgs, img_metas):
+            h, w, _ = img_meta['img_shape']
+            img_show = img[:h, :w, :]
+            labels = [
+                np.full(bbox.shape[0], i, dtype=np.int32)
+                for i, bbox in enumerate(result)
+            ]
+            labels = np.concatenate(labels)
+            bboxes = np.vstack(result)
+            mmcv.imshow_det_bboxes(
+                img_show,
+                bboxes,
+                labels,
+                class_names=class_names,
+                score_thr=score_thr)