return dict values when input single sample for easycv pipeline

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10423383

modelscope/pipelines/cv/easycv_pipelines/base.py

@@ -4,7 +4,9 @@ import os
 import os.path as osp
 from typing import Any
 
+import numpy as np
 from easycv.utils.ms_utils import EasyCVMeta
+from PIL import ImageFile
 
 from modelscope.hub.snapshot_download import snapshot_download
 from modelscope.pipelines.util import is_official_hub_path
@@ -94,5 +96,19 @@ class EasyCVPipeline(object):
 
         return easycv_config
 
+    def _is_single_inputs(self, inputs):
+        if isinstance(inputs, str) or (isinstance(inputs, list)
+                                       and len(inputs) == 1) or isinstance(
+                                           inputs, np.ndarray) or isinstance(
+                                               inputs, ImageFile.ImageFile):
+            return True
+
+        return False
+
     def __call__(self, inputs) -> Any:
-        return self.predict_op(inputs)
+        outputs = self.predict_op(inputs)
+
+        if self._is_single_inputs(inputs):
+            outputs = outputs[0]
+
+        return outputs

modelscope/pipelines/cv/easycv_pipelines/detection_pipeline.py

@@ -57,4 +57,7 @@ class EasyCVDetectionPipeline(EasyCVPipeline):
             OutputKeys.BOXES: boxes
         } for output in outputs]
 
+        if self._is_single_inputs(inputs):
+            results = results[0]
+
         return results

modelscope/pipelines/cv/easycv_pipelines/face_2d_keypoints_pipeline.py

@@ -40,4 +40,7 @@ class Face2DKeypointsPipeline(EasyCVPipeline):
             OutputKeys.POSES: output['pose']
         } for output in outputs]
 
+        if self._is_single_inputs(inputs):
+            results = results[0]
+
         return results

modelscope/pipelines/cv/easycv_pipelines/human_wholebody_keypoint_pipeline.py

@@ -62,4 +62,7 @@ class HumanWholebodyKeypointsPipeline(EasyCVPipeline):
             OutputKeys.BOXES: output['boxes']
         } for output in outputs]
 
+        if self._is_single_inputs(inputs):
+            results = results[0]
+
         return results

tests/pipelines/test_face_2d_keypoints.py

@@ -18,7 +18,7 @@ class EasyCVFace2DKeypointsPipelineTest(unittest.TestCase):
 
         face_2d_keypoints_align = pipeline(
             task=Tasks.face_2d_keypoints, model=model_id)
-        output = face_2d_keypoints_align(img_path)[0]
+        output = face_2d_keypoints_align(img_path)
 
         output_keypoints = output[OutputKeys.KEYPOINTS]
         output_pose = output[OutputKeys.POSES]

tests/pipelines/test_hand_2d_keypoints.py

@@ -15,10 +15,8 @@ class Hand2DKeypointsPipelineTest(unittest.TestCase):
         model_id = 'damo/cv_hrnetw18_hand-pose-keypoints_coco-wholebody'
 
         hand_keypoint = pipeline(task=Tasks.hand_2d_keypoints, model=model_id)
-        outputs = hand_keypoint(img_path)
-        self.assertEqual(len(outputs), 1)
+        results = hand_keypoint(img_path)
 
-        results = outputs[0]
         self.assertIn(OutputKeys.KEYPOINTS, results.keys())
         self.assertIn(OutputKeys.BOXES, results.keys())
         self.assertEqual(results[OutputKeys.KEYPOINTS].shape[1], 21)
@@ -30,10 +28,7 @@ class Hand2DKeypointsPipelineTest(unittest.TestCase):
         img_path = 'data/test/images/hand_keypoints.jpg'
 
         hand_keypoint = pipeline(task=Tasks.hand_2d_keypoints)
-        outputs = hand_keypoint(img_path)
-        self.assertEqual(len(outputs), 1)
-
-        results = outputs[0]
+        results = hand_keypoint(img_path)
         self.assertIn(OutputKeys.KEYPOINTS, results.keys())
         self.assertIn(OutputKeys.BOXES, results.keys())
         self.assertEqual(results[OutputKeys.KEYPOINTS].shape[1], 21)

tests/pipelines/test_human_wholebody_keypoint.py

@@ -18,7 +18,7 @@ class EasyCVFace2DKeypointsPipelineTest(unittest.TestCase):
 
         human_wholebody_keypoint_pipeline = pipeline(
             task=Tasks.human_wholebody_keypoint, model=model_id)
-        output = human_wholebody_keypoint_pipeline(img_path)[0]
+        output = human_wholebody_keypoint_pipeline(img_path)
 
         output_keypoints = output[OutputKeys.KEYPOINTS]
         output_pose = output[OutputKeys.BOXES]

tests/pipelines/test_object_detection.py

@@ -55,7 +55,7 @@ class ObjectDetectionTest(unittest.TestCase, DemoCompatibilityCheck):
         image_object_detection_auto = pipeline(
             Tasks.image_object_detection, model=model_id)
 
-        result = image_object_detection_auto(test_image)[0]
+        result = image_object_detection_auto(test_image)
         image_object_detection_auto.show_result(test_image, result,
                                                 'auto_demo_ret.jpg')