Fix latent preview downscaling.

By setting the downscale cutoff for latent previews to 512, it wound up
never getting tested. Animate diff has a target resolution of 512 and
newer video models only have conversion with latent2rgb,

The code for downscaling preview frames that are greater than 512 has
now been fixed and tested.

Resolves #361

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-videohelpersuite"
 description = "Nodes related to video workflows"
-version = "1.4.5"
+version = "1.4.6"
 license = { file = "LICENSE" }
 dependencies = ["opencv-python", "imageio-ffmpeg"]
 

videohelpersuite/latent_preview.py

@@ -39,6 +39,8 @@ def decode_latent_to_preview_image(self, preview_format, x0):
         self.last_time = self.last_time + num_previews/self.rate
         if num_previews > num_images:
             num_previews = num_images
+        elif num_previews <= 0:
+            return None
         if self.first_preview:
             self.first_preview = False
             serv.send_sync('VHS_latentpreview', {'length':num_images, 'rate': self.rate})
@@ -54,13 +56,14 @@ def decode_latent_to_preview_image(self, preview_format, x0):
     def process_previews(self, image_tensor, ind, leng):
         image_tensor = self.decode_latent_to_preview(image_tensor)
         if image_tensor.size(1) > 512 or image_tensor.size(2) > 512:
-            n = image.size(0)
-            if image_tensor.size(1) > image_tensor.size(2):
-                height = (512 * image_tensor.size(2)) // image_tensor.size(1)
-                image_tensor = F.interpolate(image_tensor, (512,height,3), mode='bilinear')
+            image_tensor = image_tensor.movedim(-1,0)
+            if image_tensor.size(2) < image_tensor.size(3):
+                height = (512 * image_tensor.size(2)) // image_tensor.size(3)
+                image_tensor = F.interpolate(image_tensor, (height,512), mode='bilinear')
             else:
-                width = (512 * image_tensor.size(1)) // image_tensor.size(2)
-                image_tensor = F.interpolate(image_tensor, (width, 512,3), mode='bilinear')
+                width = (512 * image_tensor.size(3)) // image_tensor.size(2)
+                image_tensor = F.interpolate(image_tensor, (512, width), mode='bilinear')
+            image_tensor = image_tensor.movedim(0,-1)
         previews_ubyte = (((image_tensor + 1.0) / 2.0).clamp(0, 1)  # change scale from -1..1 to 0..1
                          .mul(0xFF)  # to 0..255
                          ).to(device="cpu", dtype=torch.uint8)