Fix presence of segmentation images and tensor causing generation of …

…root space view (#3681)

### What

* Fixes #3677

Definitely need to come up with something better to steer the heuristics
- we made good strides in space view refactor and recent advances in
System heuristics, but there's still a lot to be desired!

In the test scene there's still the issue of a unexplicably large
accumulated bounding box which causes the camera to zoom out a lot. This
is most likely caused by an initially bad heuristic for the frustum
length. I suspect this is a problem we already had in 0.8 and might be
fairly hard to solve until we fixup our blueprint & object property
story.


Before:

![image](https://github.com/rerun-io/rerun/assets/1220815/fa3e3867-aa52-47da-b0a9-83eae9436429)

After:

![image](https://github.com/rerun-io/rerun/assets/1220815/2dd20446-bc68-4c22-99ab-0465f64262dc)


Test code:
```py
"""Log a pinhole and a random image."""
import numpy as np
import rerun as rr

rr.init("rerun_example_pinhole", spawn=True)
rng = np.random.default_rng(12345)

image = rng.uniform(0, 255, size=[3, 3, 3])
rr.log("world/camera/image", rr.Pinhole(focal_length=3, width=3, height=3))
rr.log("world/camera/image", rr.Image(image))

image = rng.uniform(0, 255, size=[3, 3, 1])
rr.log("seg", rr.SegmentationImage(image))
```

Also made sure this doesn't regress the fix in #3583 (which touched this
code last!)

### Checklist
* [x] I have read and agree to [Contributor
Guide](https://github.com/rerun-io/rerun/blob/main/CONTRIBUTING.md) and
the [Code of
Conduct](https://github.com/rerun-io/rerun/blob/main/CODE_OF_CONDUCT.md)
* [x] I've included a screenshot or gif (if applicable)
* [x] I have tested [demo.rerun.io](https://demo.rerun.io/pr/3681) (if
applicable)

- [PR Build Summary](https://build.rerun.io/pr/3681)
- [Docs
preview](https://rerun.io/preview/a29d7764be26c9cc746a726c589a284ef7efad8f/docs)
<!--DOCS-PREVIEW-->
- [Examples
preview](https://rerun.io/preview/a29d7764be26c9cc746a726c589a284ef7efad8f/examples)
<!--EXAMPLES-PREVIEW-->
- [Recent benchmark results](https://ref.rerun.io/dev/bench/)
- [Wasm size tracking](https://ref.rerun.io/dev/sizes/)

---------

Co-authored-by: Emil Ernerfeldt <[email protected]>

crates/re_viewport/src/space_view_heuristics.rs

@@ -4,9 +4,11 @@ use nohash_hasher::{IntMap, IntSet};
 
 use re_arrow_store::{LatestAtQuery, Timeline};
 use re_data_store::EntityPath;
-use re_types::archetypes::Image;
-use re_types::components::{DisconnectedSpace, TensorData};
-use re_types::{Archetype, ComponentNameSet};
+use re_types::{
+    archetypes::{Image, SegmentationImage},
+    components::{DisconnectedSpace, TensorData},
+    Archetype, ComponentNameSet,
+};
 use re_viewer_context::{
     AutoSpawnHeuristic, SpaceViewClassName, ViewContextCollection, ViewPartCollection,
     ViewSystemName, ViewerContext,
@@ -129,7 +131,9 @@ fn contains_any_image(ent_path: &EntityPath, store: &re_arrow_store::DataStore)
         .all_components(&Timeline::log_time(), ent_path)
         .unwrap_or_default()
         .iter()
-        .any(|comp| *comp == Image::indicator().name())
+        .any(|comp| {
+            *comp == SegmentationImage::indicator().name() || *comp == Image::indicator().name()
+        })
 }
 
 fn is_interesting_space_view_at_root(
@@ -142,6 +146,8 @@ fn is_interesting_space_view_at_root(
         return false;
     }
 
+    // TODO(andreas): We have to figure out how to do this kind of heuristic in a more generic way without deep knowledge of re_types.
+    //
     // If there are any images directly under the root, don't create root space either.
     // -> For images we want more fine grained control and resort to child-of-root spaces only.
     for entity_path in &candidate.contents.root_group().entities {

examples/python/controlnet/main.py

@@ -6,7 +6,7 @@
 
 Run
 ```sh
-python 3 examples/python/controlnet/main.py
+examples/python/controlnet/main.py
 ```
 """
 from __future__ import annotations

examples/python/face_tracking/main.py

@@ -140,7 +140,9 @@ def detect_and_log(self, image: npt.NDArray[np.uint8], frame_time_nano: int) ->
             # log bounding box
             rr.log(
                 f"video/detector/faces/{i}/bbox",
-                rr.Boxes2D(array=[bbox.origin_x, bbox.origin_y, bbox.width, bbox.height]),
+                rr.Boxes2D(
+                    array=[bbox.origin_x, bbox.origin_y, bbox.width, bbox.height], array_format=rr.Box2DFormat.XYWH
+                ),
                 rr.AnyValues(index=index, score=score),
             )
 

examples/python/multiprocessing/main.py

@@ -33,9 +33,16 @@ def task(child_index: int) -> None:
         ),  # noqa: E501 line too long
     )
     if child_index == 0:
-        rr.log(title, rr.Boxes2D(array=[5, 5, 80, 80], labels=title))
+        rr.log(title, rr.Boxes2D(array=[5, 5, 80, 80], array_format=rr.Box2DFormat.XYWH, labels=title))
     else:
-        rr.log(title, rr.Boxes2D(array=[10 + child_index * 10, 20 + child_index * 5, 30, 40], labels=title))
+        rr.log(
+            title,
+            rr.Boxes2D(
+                array=[10 + child_index * 10, 20 + child_index * 5, 30, 40],
+                array_format=rr.Box2DFormat.XYWH,
+                labels=title,
+            ),
+        )
 
 
 def main() -> None:

examples/python/multithreading/main.py

@@ -16,7 +16,7 @@ def rect_logger(path: str, color: npt.NDArray[np.float32]) -> None:
         rects_xy = np.random.rand(5, 2) * 1024
         rects_wh = np.random.rand(5, 2) * (1024 - rects_xy + 1)
         rects = np.hstack((rects_xy, rects_wh))
-        rr.log(path, rr.Boxes2D(array=rects, colors=color))
+        rr.log(path, rr.Boxes2D(array=rects, array_format=rr.Box2DFormat.XYWH, colors=color))
 
 
 def main() -> None:

examples/python/segment_anything_model/main.py

@@ -116,7 +116,10 @@ def run_segmentation(mask_generator: SamAutomaticMaskGenerator, image: Mat) -> N
     rr.log("image/masks", rr.SegmentationImage(segmentation_img.astype(np.uint8)))
 
     mask_bbox = np.array([m["bbox"] for _, m in masks_with_ids])
-    rr.log("image/boxes", rr.Boxes2D(array=mask_bbox, class_ids=[id for id, _ in masks_with_ids]))
+    rr.log(
+        "image/boxes",
+        rr.Boxes2D(array=mask_bbox, array_format=rr.Box2DFormat.XYWH, class_ids=[id for id, _ in masks_with_ids]),
+    )
 
 
 def is_url(path: str) -> bool:

scripts/run_all.py

@@ -28,6 +28,7 @@
 }
 
 MIN_PYTHON_REQUIREMENTS: dict[str : tuple[int, int]] = {
+    "examples/python/controlnet": (3, 10),
     # pyopf requires Python 3.10
     "examples/python/open_photogrammetry_format": (3, 10),
 }