regression: no model for tags type=default

[bertsky]

In trying to reproduce #525, I encountered this:

kraken --input 1694884104_0010.jpg 1694884104_0010.txt segment --baseline ocr --model $XDG_DATA_HOME/ocrd-resources/ocrd-kraken-recognize/austriannewspapers.mlmodel
Loading ANN /data/ocr-d/kraken/kraken/blla.mlmodel	✓
Loading ANN /data/ocr-d/ocrd_all/venv38/share/ocrd-resources/ocrd-kraken-recognize/austriannewspapers.mlmodel	✓
Segmenting	✓
Processing ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0/81 -:--:-- 0:00:00
[01/17/24 11:27:07] ERROR    Failed processing 1694884104_0010.jpg: No model for tags {'type': 'default'}                       kraken.py:426

Looks like the cause is somewhere in 8ff27d1.

[bertsky]

But if I switch the branching of the conditional:

--- a/kraken/rpred.py
+++ b/kraken/rpred.py
@@ -336,10 +336,10 @@ def _resolve_tags_to_model(tags: Optional[Sequence[Dict[str, str]]],
     """
     if not tags and default:
         return ('type', 'default'), default
+    elif tags and default:
+        return next(tags.values()), default
     elif tags:
         for tag in tags.items():
             if tag in model_map:
                 return tag, model_map[tag]
-    elif tags and default:
-        return next(tags.values()), default
     raise KrakenInputException(f'No model for tags {tags}')

then I get

'dict_values' object is not an iterator

so the moved line also needs an extra iter(...).

But then, still, I get lots of segmentation errors:

Tensor conversion failed with 'default'. Emitting empty record.

and the text result is empty.

[bertsky]

thx!

[mittagessen]

On 24/01/17 04:15AM, Robert Sachunsky wrote: But if I switch the branching of the conditional: ```diff --- a/kraken/rpred.py +++ b/kraken/rpred.py @@ -336,10 +336,10 @@ def _resolve_tags_to_model(tags: Optional[Sequence[Dict[str, str]]], """ if not tags and default: return ('type', 'default'), default + elif tags and default: + return next(tags.values()), default elif tags: for tag in tags.items(): if tag in model_map: return tag, model_map[tag] - elif tags and default: - return next(tags.values()), default raise KrakenInputException(f'No model for tags {tags}') ```

I've fixed it in main (your change isn't correct as the last check should run if the `elif tags` branch falls through).

But then, still, I get lots of segmentation errors: ``` Tensor conversion failed with 'default'. Emitting empty record. ``` and the text result is empty.

Also fixed in main. I've switched from using only the value of tags to (key, value) pairs so the `next(iter(...` part was also incorrect. PS: Regarding the scikit-image thing. I was mistaken, newer scikit-image up to 0.21.x works with scipy 0.10.x as the simplices attribute existed concurrently with the removed vertices one. Current main has the requisite patches for py38 compatibility.