OpenCV dummy objects

Author: hlky

src/diffusers/__init__.py

@@ -22,6 +22,7 @@
     is_torchsde_available,
     is_transformers_available,
 )
+from .utils.import_utils import is_opencv_available
 
 
 # Lazy Import based on
@@ -352,7 +353,6 @@
             "CogView3PlusPipeline",
             "CogView4ControlPipeline",
             "CogView4Pipeline",
-            "ConsisIDPipeline",
             "CycleDiffusionPipeline",
             "EasyAnimateControlPipeline",
             "EasyAnimateInpaintPipeline",
@@ -518,6 +518,25 @@
         ]
     )
 
+
+try:
+    if not (is_torch_available() and is_transformers_available() and is_opencv_available()):
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    from .utils import dummy_torch_and_transformers_and_opencv_objects  # noqa F403
+
+    _import_structure["utils.dummy_torch_and_transformers_and_opencv_objects"] = [
+        name for name in dir(dummy_torch_and_transformers_and_opencv_objects) if not name.startswith("_")
+    ]
+
+else:
+    _import_structure["pipelines"].extend(
+        [
+            "ConsisIDPipeline",
+        ]
+    )
+
+
 try:
     if not (is_torch_available() and is_transformers_available() and is_k_diffusion_available()):
         raise OptionalDependencyNotAvailable()
@@ -1073,6 +1092,16 @@
             WuerstchenPriorPipeline,
         )
 
+    try:
+        if not (is_torch_available() and is_transformers_available() and is_opencv_available()):
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        from .utils.dummy_torch_and_transformers_and_opencv_objects import *  # noqa F403
+    else:
+        from .pipelines import (
+            ConsisIDPipeline,
+        )
+
     try:
         if not (is_torch_available() and is_transformers_available() and is_k_diffusion_available()):
             raise OptionalDependencyNotAvailable()

src/diffusers/pipelines/consisid/__init__.py

@@ -8,29 +8,30 @@
     is_torch_available,
     is_transformers_available,
 )
+from ...utils.import_utils import is_opencv_available
 
 
 _dummy_objects = {}
 _import_structure = {}
 
 
 try:
-    if not (is_transformers_available() and is_torch_available()):
+    if not (is_transformers_available() and is_torch_available() and is_opencv_available()):
         raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
-    from ...utils import dummy_torch_and_transformers_objects  # noqa F403
+    from ...utils import dummy_torch_and_transformers_and_opencv_objects  # noqa F403
 
-    _dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
+    _dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_and_opencv_objects))
 else:
     _import_structure["pipeline_consisid"] = ["ConsisIDPipeline"]
 
 if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
     try:
-        if not (is_transformers_available() and is_torch_available()):
+        if not (is_transformers_available() and is_torch_available() and is_opencv_available()):
             raise OptionalDependencyNotAvailable()
 
     except OptionalDependencyNotAvailable:
-        from ...utils.dummy_torch_and_transformers_objects import *
+        from ...utils.dummy_torch_and_transformers_and_opencv_objects import *
     else:
         from .pipeline_consisid import ConsisIDPipeline
 

src/diffusers/utils/dummy_torch_and_transformers_and_opencv_objects.py

@@ -392,21 +392,6 @@ def from_pretrained(cls, *args, **kwargs):
         requires_backends(cls, ["torch", "transformers"])
 
 
-class ConsisIDPipeline(metaclass=DummyObject):
-    _backends = ["torch", "transformers"]
-
-    def __init__(self, *args, **kwargs):
-        requires_backends(self, ["torch", "transformers"])
-
-    @classmethod
-    def from_config(cls, *args, **kwargs):
-        requires_backends(cls, ["torch", "transformers"])
-
-    @classmethod
-    def from_pretrained(cls, *args, **kwargs):
-        requires_backends(cls, ["torch", "transformers"])
-
-
 class CycleDiffusionPipeline(metaclass=DummyObject):
     _backends = ["torch", "transformers"]