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预训练调整
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2
demo.py
2
demo.py
@ -6,6 +6,6 @@ import numpy as np
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model = YOLOv10('ckpts/20250630/best_gift_v10n.pt')
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# result = model.predict('./data/bandage.jpg', save=True, imgsz=[224, 224], conf=0.1)
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result = model.predict('/home/lc/data_center/gift/trace_subimgs/predict_actual_test/gift', save=True, imgsz=[224, 224], conf=0.1)
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result = model.predict('/home/lc/data_center/gift/trace_subimgs/predict_actual_test/test', save=True, imgsz=[224, 224], conf=0.1)
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print(result)
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# print(result[0].boxes.conf)
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@ -68,7 +68,7 @@ embed: # (list[int], optional) return feature vectors/embeddings from given laye
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# Visualize settings ---------------------------------------------------------------------------------------------------
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show: False # (bool) show predicted images and videos if environment allows
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save_frames: False # (bool) save predicted individual video frames
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save_txt: False # (bool) save results as .txt file
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save_txt: True # (bool) save results as .txt file
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save_conf: False # (bool) save results with confidence scores
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save_crop: False # (bool) save cropped images with results
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show_labels: True # (bool) show prediction labels, i.e. 'person'
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