add requirements

condition/midas/midas/vit.py

@@ -192,12 +192,12 @@ def _make_vit_b16_backbone(
     pretrained = nn.Module()
 
     pretrained.model = model
-    pretrained.model.blocks[hooks[0]].register_forward_hook(get_activation("1"))
-    pretrained.model.blocks[hooks[1]].register_forward_hook(get_activation("2"))
-    pretrained.model.blocks[hooks[2]].register_forward_hook(get_activation("3"))
-    pretrained.model.blocks[hooks[3]].register_forward_hook(get_activation("4"))
+    # pretrained.model.blocks[hooks[0]].register_forward_hook(get_activation("1"))
+    # pretrained.model.blocks[hooks[1]].register_forward_hook(get_activation("2"))
+    # pretrained.model.blocks[hooks[2]].register_forward_hook(get_activation("3"))
+    # pretrained.model.blocks[hooks[3]].register_forward_hook(get_activation("4"))
 
-    pretrained.activations = activations
+    # pretrained.activations = activations
 
     readout_oper = get_readout_oper(vit_features, features, use_readout, start_index)
 
@@ -354,21 +354,21 @@ def _make_vit_b_rn50_backbone(
 
     pretrained.model = model
 
-    if use_vit_only == True:
-        pretrained.model.blocks[hooks[0]].register_forward_hook(get_activation("1"))
-        pretrained.model.blocks[hooks[1]].register_forward_hook(get_activation("2"))
-    else:
-        pretrained.model.patch_embed.backbone.stages[0].register_forward_hook(
-            get_activation("1")
-        )
-        pretrained.model.patch_embed.backbone.stages[1].register_forward_hook(
-            get_activation("2")
-        )
-
-    pretrained.model.blocks[hooks[2]].register_forward_hook(get_activation("3"))
-    pretrained.model.blocks[hooks[3]].register_forward_hook(get_activation("4"))
-
-    pretrained.activations = activations
+    # if use_vit_only == True:
+    #     pretrained.model.blocks[hooks[0]].register_forward_hook(get_activation("1"))
+    #     pretrained.model.blocks[hooks[1]].register_forward_hook(get_activation("2"))
+    # else:
+    #     pretrained.model.patch_embed.backbone.stages[0].register_forward_hook(
+    #         get_activation("1")
+    #     )
+    #     pretrained.model.patch_embed.backbone.stages[1].register_forward_hook(
+    #         get_activation("2")
+    #     )
+
+    # pretrained.model.blocks[hooks[2]].register_forward_hook(get_activation("3"))
+    # pretrained.model.blocks[hooks[3]].register_forward_hook(get_activation("4"))
+
+    # pretrained.activations = activations
 
     readout_oper = get_readout_oper(vit_features, features, use_readout, start_index)
 

model.py

@@ -92,7 +92,7 @@ class Model:
         return t5_model
 
     @torch.no_grad()
-    @spaces.GPU(enable_queue=False)
+    @spaces.GPU(enable_queue=True)
     def process_canny(
         self,
         image: np.ndarray,
@@ -168,7 +168,7 @@ class Model:
         return samples
 
     @torch.no_grad()
-    @spaces.GPU(enable_queue=False)
+    @spaces.GPU(enable_queue=True)
     def process_depth(
         self,
         image: np.ndarray,