Fix HRNet dimension error on images with alpha channel (#5570)

This is pretty much the same fix applied to f-BRS in #5384. We've been
using HRNet for a while and now an then we receive "500 errors" just as
reported in #5299 when someone forgets to drop the alpha-channel from
our images.

### Motivation and context
The RuntimeError is a little bit different, but comes from the same
issue: RGBA instead of RGB images:
> RuntimeError: Given groups=1, weight of size [16, 3, 1, 1], expected
input[*, 4, *, *] to have 3 channels, but got 4 channels instead.

### How has this been tested?
I created a task with images with and w/o alpha channel, and the
interactor works on both now.

CHANGELOG.md

@@ -35,6 +35,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 - Helm: Empty password for Redis (<https://github.com/opencv/cvat/pull/5520>)
+- Fixed HRNet serverless function runtime error on images with alpha channel (<https://github.com/opencv/cvat/pull/5570>)
 - Preview & chunk cache settings are ignored (<https://github.com/opencv/cvat/pull/5569>)
 
 ### Security

serverless/pytorch/saic-vul/hrnet/nuclio/main.py

@@ -24,7 +24,7 @@ def handler(context, event):
     neg_points = data["neg_points"]
     threshold = data.get("threshold", 0.5)
     buf = io.BytesIO(base64.b64decode(data["image"]))
-    image = Image.open(buf)
+    image = Image.open(buf).convert('RGB')
 
     mask, polygon = context.user_data.model.handle(image, pos_points,
         neg_points, threshold)