[to #43133921] visual try-on Task

虚拟试衣修改输入为tuple格式
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9561416

    * change input to tuple

* support dict or tuple input

* Merge branch 'master' into cv/virtual_tryon

* Merge remote-tracking branch 'origin/master' into cv/virtual_tryon

modelscope/pipelines/cv/virtual_tryon_pipeline.py

@@ -1,7 +1,7 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 
 import os.path as osp
-from typing import Any, Dict
+from typing import Any, Dict, Union
 
 import cv2
 import numpy as np
@@ -71,20 +71,31 @@ class VirtualTryonPipeline(Pipeline):
             transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
         ])
 
-    def preprocess(self, input: Dict[str, Any]) -> Dict[str, Any]:
-        if isinstance(input['masked_model'], str):
-            img_agnostic = load_image(input['masked_model'])
-            pose = load_image(input['pose'])
-            cloth_img = load_image(input['cloth'])
-        elif isinstance(input['masked_model'], PIL.Image.Image):
-            img_agnostic = img_agnostic.convert('RGB')
-            pose = pose.convert('RGB')
-            cloth_img = cloth_img.convert('RGB')
-        elif isinstance(input['masked_model'], np.ndarray):
+    def preprocess(self, input: Union[Dict[str, Any],
+                                      tuple]) -> Dict[str, Any]:
+        if isinstance(input, tuple):
+            index_model = 0
+            index_pose = 1
+            index_cloth = 2
+        else:
+            index_model = 'masked_model'
+            index_pose = 'pose'
+            index_cloth = 'cloth'
+        if isinstance(input[index_model], str):
+            img_agnostic = load_image(input[index_model])
+            pose = load_image(input[index_pose])
+            cloth_img = load_image(input[index_cloth])
+        elif isinstance(input[index_model], PIL.Image.Image):
+            img_agnostic = input[index_model].convert('RGB')
+            pose = input[index_pose].convert('RGB')
+            cloth_img = input[index_cloth].convert('RGB')
+        elif isinstance(input[index_model], np.ndarray):
             if len(input.shape) == 2:
-                img_agnostic = cv2.cvtColor(img_agnostic, cv2.COLOR_GRAY2BGR)
-                pose = cv2.cvtColor(pose, cv2.COLOR_GRAY2BGR)
-                cloth_img = cv2.cvtColor(cloth_img, cv2.COLOR_GRAY2BGR)
+                img_agnostic = cv2.cvtColor(input[index_model],
+                                            cv2.COLOR_GRAY2BGR)
+                pose = cv2.cvtColor(input[index_pose], cv2.COLOR_GRAY2BGR)
+                cloth_img = cv2.cvtColor(input[index_cloth],
+                                         cv2.COLOR_GRAY2BGR)
             img_agnostic = Image.fromarray(
                 img_agnostic[:, :, ::-1].astype('uint8')).convert('RGB')
             pose = Image.fromarray(

tests/pipelines/test_virtual_tryon.py

@@ -3,6 +3,7 @@ import unittest
 
 import cv2
 import numpy as np
+from PIL import Image
 
 from modelscope.outputs import OutputKeys
 from modelscope.pipelines import pipeline
@@ -12,11 +13,10 @@ from modelscope.utils.test_utils import test_level
 
 class VirtualTryonTest(unittest.TestCase):
     model_id = 'damo/cv_daflow_virtual-tryon_base'
-    input_imgs = {
-        'masked_model': 'data/test/images/virtual_tryon_model.jpg',
-        'pose': 'data/test/images/virtual_tryon_pose.jpg',
-        'cloth': 'data/test/images/virtual_tryon_cloth.jpg'
-    }
+    masked_model = Image.open('data/test/images/virtual_tryon_model.jpg')
+    pose = Image.open('data/test/images/virtual_tryon_pose.jpg')
+    cloth = Image.open('data/test/images/virtual_tryon_cloth.jpg')
+    input_imgs = (masked_model, pose, cloth)
 
     @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_run_with_model_name(self):