[CodeCamp2023-503] Add docs of Inferencer (#10784)

mmdet/apis/det_inferencer.py

@@ -78,7 +78,7 @@ class DetInferencer(BaseInferencer):
     postprocess_kwargs: set = {
         'print_result',
         'pred_out_dir',
-        'return_datasample',
+        'return_datasamples',
         'no_save_pred',
     }
 
@@ -303,7 +303,7 @@ def __call__(
             no_save_vis: bool = False,
             draw_pred: bool = True,
             pred_score_thr: float = 0.3,
-            return_datasample: bool = False,
+            return_datasamples: bool = False,
             print_result: bool = False,
             no_save_pred: bool = True,
             out_dir: str = '',
@@ -328,13 +328,13 @@ def __call__(
                 Defaults to True.
             pred_score_thr (float): Minimum score of bboxes to draw.
                 Defaults to 0.3.
-            return_datasample (bool): Whether to return results as
+            return_datasamples (bool): Whether to return results as
                 :obj:`DetDataSample`. Defaults to False.
             print_result (bool): Whether to print the inference result w/o
                 visualization to the console. Defaults to False.
             no_save_pred (bool): Whether to force not to save prediction
                 results. Defaults to True.
-            out_file: Dir to save the inference results or
+            out_dir: Dir to save the inference results or
                 visualization. If left as empty, no file will be saved.
                 Defaults to ''.
             texts (str | list[str]): Text prompts. Defaults to None.
@@ -405,7 +405,7 @@ def __call__(
             results = self.postprocess(
                 preds,
                 visualization,
-                return_datasample=return_datasample,
+                return_datasamples=return_datasamples,
                 print_result=print_result,
                 no_save_pred=no_save_pred,
                 pred_out_dir=out_dir,
@@ -498,7 +498,7 @@ def postprocess(
         self,
         preds: PredType,
         visualization: Optional[List[np.ndarray]] = None,
-        return_datasample: bool = False,
+        return_datasamples: bool = False,
         print_result: bool = False,
         no_save_pred: bool = False,
         pred_out_dir: str = '',
@@ -516,7 +516,7 @@ def postprocess(
         Args:
             preds (List[:obj:`DetDataSample`]): Predictions of the model.
             visualization (Optional[np.ndarray]): Visualized predictions.
-            return_datasample (bool): Whether to use Datasample to store
+            return_datasamples (bool): Whether to use Datasample to store
                 inference results. If False, dict will be used.
             print_result (bool): Whether to print the inference result w/o
                 visualization to the console. Defaults to False.
@@ -533,7 +533,7 @@ def postprocess(
             - ``visualization`` (Any): Returned by :meth:`visualize`.
             - ``predictions`` (dict or DataSample): Returned by
                 :meth:`forward` and processed in :meth:`postprocess`.
-                If ``return_datasample=False``, it usually should be a
+                If ``return_datasamples=False``, it usually should be a
                 json-serializable dict containing only basic data elements such
                 as strings and numbers.
         """
@@ -542,14 +542,14 @@ def postprocess(
 
         result_dict = {}
         results = preds
-        if not return_datasample:
+        if not return_datasamples:
             results = []
             for pred in preds:
                 result = self.pred2dict(pred, pred_out_dir)
                 results.append(result)
         elif pred_out_dir != '':
             warnings.warn('Currently does not support saving datasample '
-                          'when return_datasample is set to True. '
+                          'when return_datasamples is set to True. '
                           'Prediction results are not saved!')
         # Add img to the results after printing and dumping
         result_dict['predictions'] = results

projects/XDecoder/xdecoder/inference/image_caption.py

@@ -188,7 +188,7 @@ def __call__(
             no_save_vis: bool = False,
             draw_pred: bool = True,
             pred_score_thr: float = 0.3,
-            return_datasample: bool = False,
+            return_datasamples: bool = False,
             print_result: bool = False,
             no_save_pred: bool = True,
             out_dir: str = '',
@@ -211,7 +211,7 @@ def __call__(
                 Defaults to True.
             pred_score_thr (float): Minimum score of bboxes to draw.
                 Defaults to 0.3.
-            return_datasample (bool): Whether to return results as
+            return_datasamples (bool): Whether to return results as
                 :obj:`DetDataSample`. Defaults to False.
             print_result (bool): Whether to print the inference result w/o
                 visualization to the console. Defaults to False.
@@ -297,7 +297,7 @@ def __call__(
             results = self.postprocess(
                 preds,
                 visualization,
-                return_datasample=return_datasample,
+                return_datasamples=return_datasamples,
                 print_result=print_result,
                 no_save_pred=no_save_pred,
                 pred_out_dir=out_dir,

projects/XDecoder/xdecoder/inference/texttoimage_regionretrieval_inferencer.py

@@ -104,7 +104,7 @@ def __call__(
             no_save_vis: bool = False,
             draw_pred: bool = True,
             pred_score_thr: float = 0.3,
-            return_datasample: bool = False,
+            return_datasamples: bool = False,
             print_result: bool = False,
             no_save_pred: bool = True,
             out_dir: str = '',
@@ -127,7 +127,7 @@ def __call__(
                 Defaults to True.
             pred_score_thr (float): Minimum score of bboxes to draw.
                 Defaults to 0.3.
-            return_datasample (bool): Whether to return results as
+            return_datasamples (bool): Whether to return results as
                 :obj:`DetDataSample`. Defaults to False.
             print_result (bool): Whether to print the inference result w/o
                 visualization to the console. Defaults to False.
@@ -216,7 +216,7 @@ def __call__(
         results = self.postprocess(
             preds,
             visualization,
-            return_datasample=return_datasample,
+            return_datasamples=return_datasamples,
             print_result=print_result,
             no_save_pred=no_save_pred,
             pred_out_dir=out_dir,

projects/gradio_demo/launch.py

@@ -435,7 +435,7 @@ def inference(self, model, image):
         ic_inferencer = ImageCaptionInferencer(
             **self.model_info[model], scope='mmdet', device=get_free_device())
         results_dict = ic_inferencer(
-            image, return_vis=False, no_save_vis=True, return_datasample=True)
+            image, return_vis=False, no_save_vis=True, return_datasamples=True)
         return results_dict['predictions'][0].pred_caption
 
 

tests/test_apis/test_det_inferencer.py

@@ -120,7 +120,7 @@ def test_visualize(self, model):
         'rtmdet-t', 'mask-rcnn_r50_fpn_1x_coco', 'panoptic_fpn_r50_fpn_1x_coco'
     ])
     def test_postprocess(self, model):
-        # return_datasample
+        # return_datasamples
         img_path = 'tests/data/color.jpg'
 
         mock_load = Mock(return_value=None)
@@ -135,7 +135,7 @@ def test_postprocess(self, model):
                 'palette': 'random'
             }
 
-        res = inferencer(img_path, return_datasample=True)
+        res = inferencer(img_path, return_datasamples=True)
         self.assertTrue(is_list_of(res['predictions'], DetDataSample))
 
         with tempfile.TemporaryDirectory() as tmp_dir: