Update app.py

app.py

@@ -10,6 +10,7 @@ from diffusers.utils import export_to_video, load_video
 from torchvision import transforms
 import random
 from controlnet_aux import CannyDetector
+from image_gen_aux import DepthPreprocessor
 
 dtype = torch.bfloat16 
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -21,6 +22,7 @@ pipe_upsample.to(device)
 pipeline.vae.enable_tiling()
 
 canny_processor = CannyDetector()
+depth_processor = DepthPreprocessor.from_pretrained("LiheYoung/depth-anything-large-hf")
 
 CONTROL_LORAS = {
     "canny": {
@@ -98,19 +100,19 @@ def process_video_for_canny(video):
     canny_video = []
     for frame in video: 
         # TODO: change resolution logic
-        canny_video.append(processor(frame, low_threshold=50, high_threshold=200, detect_resolution=1024, image_resolution=1024))
+        canny_video.append(canny_processor(frame, low_threshold=50, high_threshold=200, detect_resolution=1024, image_resolution=1024))
      
     return canny_video
 
 def process_video_for_depth(video):
     """
     Process video for depth control.
-    Placeholder function - will return video as-is for now.
-    TODO: Implement depth estimation processing
     """
     print("Processing video for depth control...")
-   
-    return video_tensor
+       dapth_video = []
+    for frame in video: 
+        dapth_video.append(depth_processor(frame)[0].convert("RGB"))
+    return dapth_video
 
 def process_video_for_pose(video):
     """