init

2025-07-10 21:52:14 +08:00
commit 0893a7bf71
740 changed files with 103955 additions and 0 deletions
@@ -0,0 +1,56 @@
+from ..utils import common_annotator_call, INPUT, define_preprocessor_inputs
+import comfy.model_management as model_management
+
+class Depth_Anything_V2_Preprocessor:
+    @classmethod
+    def INPUT_TYPES(s):
+        return define_preprocessor_inputs(
+            ckpt_name=INPUT.COMBO(
+                ["depth_anything_v2_vitg.pth", "depth_anything_v2_vitl.pth", "depth_anything_v2_vitb.pth", "depth_anything_v2_vits.pth"],
+                default="depth_anything_v2_vitl.pth"
+            ),
+            resolution=INPUT.RESOLUTION()
+        )
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "execute"
+
+    CATEGORY = "ControlNet Preprocessors/Normal and Depth Estimators"
+
+    def execute(self, image, ckpt_name="depth_anything_v2_vitl.pth", resolution=512, **kwargs):
+        from custom_controlnet_aux.depth_anything_v2 import DepthAnythingV2Detector
+
+        model = DepthAnythingV2Detector.from_pretrained(filename=ckpt_name).to(model_management.get_torch_device())
+        out = common_annotator_call(model, image, resolution=resolution, max_depth=1)
+        del model
+        return (out, )
+
+""" class Depth_Anything_Metric_V2_Preprocessor:
+    @classmethod
+    def INPUT_TYPES(s):
+        return create_node_input_types(
+            environment=(["indoor", "outdoor"], {"default": "indoor"}),
+            max_depth=("FLOAT", {"min": 0, "max": 100, "default": 20.0, "step": 0.01})
+        )
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "execute"
+
+    CATEGORY = "ControlNet Preprocessors/Normal and Depth Estimators"
+
+    def execute(self, image, environment, resolution=512, max_depth=20.0, **kwargs):
+        from custom_controlnet_aux.depth_anything_v2 import DepthAnythingV2Detector
+        filename = dict(indoor="depth_anything_v2_metric_hypersim_vitl.pth", outdoor="depth_anything_v2_metric_vkitti_vitl.pth")[environment]
+        model = DepthAnythingV2Detector.from_pretrained(filename=filename).to(model_management.get_torch_device())
+        out = common_annotator_call(model, image, resolution=resolution, max_depth=max_depth)
+        del model
+        return (out, ) """
+
+NODE_CLASS_MAPPINGS = {
+    "DepthAnythingV2Preprocessor": Depth_Anything_V2_Preprocessor,
+    #"Metric_DepthAnythingV2Preprocessor": Depth_Anything_Metric_V2_Preprocessor
+}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "DepthAnythingV2Preprocessor": "Depth Anything V2 - Relative",
+    #"Metric_DepthAnythingV2Preprocessor": "Depth Anything V2 - Metric"
+}