fix: predict output type, filter by ratio

adetailer/common.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from collections import OrderedDict
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from pathlib import Path
 from typing import Optional, Union
 
@@ -13,8 +13,8 @@ repo_id = "Bingsu/adetailer"
 
 @dataclass
 class PredictOutput:
-    bboxes: Optional[list[list[int]]] = None
-    masks: Optional[list[Image.Image]] = None
+    bboxes: list[list[float]] = field(default_factory=list)
+    masks: list[Image.Image] = field(default_factory=list)
     preview: Optional[Image.Image] = None
 
 

adetailer/mask.py

@@ -84,7 +84,7 @@ def bbox_area(bbox: list[float]):
 
 
 def mask_preprocess(
-    masks: list[Image.Image] | None,
+    masks: list[Image.Image],
     kernel: int = 0,
     x_offset: int = 0,
     y_offset: int = 0,
@@ -95,7 +95,7 @@ def mask_preprocess(
 
     Parameters
     ----------
-        masks: list[Image.Image] | None
+        masks: list[Image.Image]
             A list of masks
         kernel: int
             kernel size of dilation or erosion
@@ -109,14 +109,16 @@ def mask_preprocess(
         list[Image.Image]
             A list of processed masks
     """
-    if masks is None:
+    if not masks:
         return []
 
-    masks = [dilate_erode(m, kernel) for m in masks]
-    masks = [m for m in masks if not is_all_black(m)]
     if x_offset != 0 or y_offset != 0:
         masks = [offset(m, x_offset, y_offset) for m in masks]
 
+    if kernel != 0:
+        masks = [dilate_erode(m, kernel) for m in masks]
+        masks = [m for m in masks if not is_all_black(m)]
+
     return masks
 
 
@@ -163,7 +165,7 @@ def _key_area(bbox: list[float]) -> float:
 def sort_bboxes(
     pred: PredictOutput, order: int | SortBy = SortBy.NONE
 ) -> PredictOutput:
-    if order == SortBy.NONE or not pred.bboxes:
+    if order == SortBy.NONE or len(pred.bboxes) <= 1:
         return pred
 
     if order == SortBy.LEFT_TO_RIGHT:
@@ -182,3 +184,22 @@ def sort_bboxes(
     pred.bboxes = [pred.bboxes[i] for i in idx]
     pred.masks = [pred.masks[i] for i in idx]
     return pred
+
+
+# Filter by ratio
+def is_in_ratio(bbox: list[float], low: float, high: float, orig_area: int) -> bool:
+    area = bbox_area(bbox)
+    return low <= area / orig_area <= high
+
+
+def filter_by_ratio(pred: PredictOutput, low: float, high: float) -> PredictOutput:
+    if not pred.bboxes:
+        return pred
+
+    w, h = pred.preview.size
+    orig_area = w * h
+    items = len(pred.bboxes)
+    idx = [i for i in range(items) if is_in_ratio(pred.bboxes[i], low, high, orig_area)]
+    pred.bboxes = [pred.bboxes[i] for i in idx]
+    pred.masks = [pred.masks[i] for i in idx]
+    return pred