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https://github.com/Bing-su/adetailer.git
synced 2026-04-24 08:19:19 +00:00
fix: example → preview
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@@ -12,7 +12,7 @@ from PIL import Image, ImageDraw
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class PredictOutput:
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bboxes: list[list[int]] | None = None
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masks: list[Image.Image] | None = None
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example: Image.Image | None = None
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preview: Image.Image | None = None
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def get_models(model_dir: str | Path) -> OrderedDict[str, str | None]:
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@@ -1,7 +1,7 @@
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from __future__ import annotations
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import numpy as np
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import mediapipe as mp
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import numpy as np
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from PIL import Image
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from adetailer import PredictOutput
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@@ -26,11 +26,11 @@ def mediapipe_predict(
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if pred.detections is None:
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return PredictOutput()
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example_array = img_array.copy()
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preview_array = img_array.copy()
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bboxes = []
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for detection in pred.detections:
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draw_util.draw_detection(example_array, detection)
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draw_util.draw_detection(preview_array, detection)
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bbox = detection.location_data.relative_bounding_box
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x1 = bbox.xmin * img_width
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@@ -43,6 +43,6 @@ def mediapipe_predict(
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bboxes.append([x1, y1, x2, y2])
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masks = create_mask_from_bbox(image, bboxes)
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example = Image.fromarray(example_array)
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preview = Image.fromarray(preview_array)
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return PredictOutput(bboxes=bboxes, masks=masks, example=example)
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return PredictOutput(bboxes=bboxes, masks=masks, preview=preview)
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@@ -23,8 +23,8 @@ def ultralytics_predict(
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return PredictOutput()
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masks = create_mask_from_bbox(image, bboxes)
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example = pred[0].plot()
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example = cv2.cvtColor(example, cv2.COLOR_BGR2RGB)
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example = Image.fromarray(example)
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preview = pred[0].plot()
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preview = cv2.cvtColor(preview, cv2.COLOR_BGR2RGB)
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preview = Image.fromarray(preview)
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return PredictOutput(bboxes=bboxes, masks=masks, example=example)
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return PredictOutput(bboxes=bboxes, masks=masks, preview=preview)
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