processor: pass on more Eynollah parameters…

- `device` selection
- `model_overrides` (as dict; including relative path resolution), e.g.
```JSON
{
  "binarization": {
    "":
      "models_inference_layout_v0_9_1/models_eynollah/eynollah-binarization_20210425.onnx"
  }
}
```
- `skip_layout_and_reading_order`
- `num_col_upper`
- `num_col_lower`
- `binarize` (for `input_binary`, which is a misnomer)

src/eynollah/ocrd-tool.json

@@ -6,23 +6,61 @@
     "ocrd-eynollah-segment": {
       "executable": "ocrd-eynollah-segment",
       "categories": ["Layout analysis"],
-      "description": "Segment page into regions and lines and do reading order detection with eynollah",
+      "description": "Segment page into regions and lines and detect reading order with Eynollah",
       "input_file_grp_cardinality": 1,
       "output_file_grp_cardinality": 1,
       "steps": ["layout/segmentation/region", "layout/segmentation/line"],
       "parameters": {
+        "device": {
+          "type": "string",
+          "default": "",
+          "description": "Allocate models to computation device; can be a single device name for all models, or a comma-delimited, colon-tagged mapping from model category to device name (where model categories are binarization, col_classifier, page, textline, region_1_2, region_fl_np, table, reading_order, but can be abbreviated by glob expressions), e.g. col*:CPU,page:GPU0,*:GPU1. If empty, selects the first available GPU for all models."
+        },
         "models": {
           "type": "string",
           "format": "uri",
           "content-type": "text/directory",
           "cacheable": true,
-          "description": "Directory containing models to be used (See https://qurator-data.de/eynollah)",
+          "description": "Directory containing models to be used (See https://huggingface.co/collections/SBB/eynollah-models)",
           "required": true
         },
+        "model_overrides": {
+          "type": "object",
+          "properties": {
+            "binarization": {
+              "type": "object"
+            },
+            "enhancement": {
+              "type": "object"
+            },
+            "col_classifier": {
+              "type": "object"
+            },
+            "page": {
+              "type": "object"
+            },
+            "textline": {
+              "type": "object"
+            },
+            "region_1_2": {
+              "type": "object"
+            },
+            "region_fl_np": {
+              "type": "object"
+            },
+            "table": {
+              "type": "object"
+            },
+            "reading_order": {
+              "type": "object"
+            }
+          },
+          "description": "Map model categories to mappings from model variant to model path, e.g. {'ocr': {'tr': 'path/to/my/trocr-model'}}."
+        },
         "dpi": {
           "type": "number",
           "format": "float",
-          "description": "pixel density in dots per inch (overrides any meta-data in the images); ignored if <= 0 (with fall-back 230)",
+          "description": "ignored (only for backwards-compatibility)",
           "default": 0
         },
         "full_layout": {
@@ -57,10 +95,20 @@
           "default": false,
           "description": "if true, do not attempt page frame detection (cropping)"
         },
+        "skip_layout_and_reading_order": {
+          "type": "boolean",
+          "default": false,
+          "description": "skip regions, only run textlines, stuffing them in a single text region for the entire page"
+        },
+        "binarize": {
+          "type": "boolean",
+          "default": false,
+          "description": "run adaptive thresholding on input image with dedicated model before analysis (may be useful for degraded input)."
+        },
         "allow_scaling": {
           "type": "boolean",
           "default": false,
-          "description": "check the resolution against the number of detected columns and if needed, scale the image up or down during layout detection (heuristic to improve quality and performance)"
+          "description": "ignored (only for backwards-compatibility)"
         },
         "allow_enhancement": {
           "type": "boolean",
@@ -72,6 +120,20 @@
           "default": false,
           "description": "if true, return reading order in right-to-left reading direction."
         },
+        "num_col_upper": {
+          "type": "number",
+          "format": "integer",
+          "minimum": 0,
+          "default": 0,
+          "description": "Constrain detection of number of columns by this upper boundary (ignored when zero)."
+        },
+        "num_col_lower": {
+          "type": "number",
+          "format": "integer",
+          "minimum": 0,
+          "default": 0,
+          "description": "Constrain detection of number of columns by this lower boundary (ignored when zero)."
+        },
         "headers_off": {
           "type": "boolean",
           "default": false,
@@ -159,6 +221,14 @@
         }
       },
       "resources": [
+        {
+          "url": "https://zenodo.org/records/21381102/files/models_inference_layout_v0_9_1.zip",
+          "name": "models_inference_layout_v0_9_1",
+          "type": "archive",
+	  "size": 1847700967,
+          "description": "Models for layout detection, reading order detection, textline detection, page extraction, column classification, table detection, binarization and image enhancement",
+          "version_range": ">= v0.9.0"
+        },
         {
           "url": "https://zenodo.org/records/21381102/files/models_inference_all_v0_9_1.zip",
           "name": "models_inference_all_v0_9_1",

src/eynollah/processor.py

@@ -15,7 +15,12 @@ class EynollahProcessor(Processor):
     def setup(self) -> None:
         assert self.parameter
         basedir = self.resolve_resource(self.parameter['models'])
-        model_zoo = EynollahModelZoo(basedir)
+        overrides = []
+        for category, override in self.parameter['model_overrides'].items():
+            for variant, path in override.items():
+                path = self.resolve_resource(path)
+                overrides.append((category, variant, path))
+        model_zoo = EynollahModelZoo(basedir, model_overrides=overrides)
         self.eynollah = Eynollah(
             model_zoo=model_zoo,
             allow_enhancement=self.parameter['allow_enhancement'],
@@ -23,10 +28,15 @@ class EynollahProcessor(Processor):
             right2left=self.parameter['right_to_left'],
             reading_order_machine_based=self.parameter['reading_order_machine_based'],
             ignore_page_extraction=self.parameter['ignore_page_extraction'],
+            skip_layout_and_reading_order=self.parameter['skip_layout_and_reading_order'],
             full_layout=self.parameter['full_layout'],
             allow_scaling=self.parameter['allow_scaling'],
             headers_off=self.parameter['headers_off'],
             tables=self.parameter['tables'],
+            device=self.parameter['device'],
+            input_binary=self.parameter['binarize'],
+            num_col_upper=self.parameter['num_col_upper'],
+            num_col_lower=self.parameter['num_col_lower'],
             logger=self.logger
         )
         self.eynollah.plotter = None
@@ -49,13 +59,17 @@ class EynollahProcessor(Processor):
 
         \b
         - If ``tables``, try to detect table blocks and add them as TableRegion.
-        - If ``full_layout``, then in addition to paragraphs and marginals, also
+        - If ``full_layout`` (the default), then in addition to paragraphs and marginals,
-          try to detect drop capitals and headings.
+          also try to detect drop capitals and headings.
+        - If ``ignore_page_extraction``, then attempt no cropping of the page.
         - If ``ignore_page_extraction``, then attempt no cropping of the page.
         - If ``curved_line``, then compute contour polygons for text lines
           instead of simple bounding boxes.
         - If ``reading_order_machine_based``, then detect reading order via
           data-driven model instead of geometrical heuristics.
+        - If ``binarize``, then run internal binarization on the raw image.
+        - If ``num_col_upper`` or ``num_col_lower`` are non-zero, these will
+          constrain the column detection (upper or lower bound, respectively).
 
         Produce a new output file by serialising the resulting hierarchy.
         """