41 lines
1.7 KiB
Python
41 lines
1.7 KiB
Python
import os.path
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from ultralytics import YOLO
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'''
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注意修改配置文件中的文件夹路径
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'''
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model = YOLO('/home/admin-root/haotian/python哈汽锻8安全帽识别/HelmetHeadBAC/trainHardHatsV1HelmetHeadShoe2/weights/best.pt')
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# images_path = '/home/admin-root/haotian/锻8/tensorrtx/yolov8/images'
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# images_path = '/home/admin-root/haotian/锻8/tensorrtx/yolov8/images_20250623'
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# images_path = '/home/admin-root/haotian/python哈汽锻8安全帽识别/test_images/duan8_real'
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images_path = '/home/admin-root/haotian/锻8/tensorrtx/yolov8/images_20250624105822'
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# save_path = '/home/admin-root/haotian/python哈汽锻8安全帽识别/output/outputHardHatsV1HelmetHeadShoe2_20250623'
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save_path = '/home/admin-root/haotian/python哈汽锻8安全帽识别/output/outputHardHatsV1HelmetHeadShoe2_202506624105822'
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all_images = [os.path.join(images_path, t) for t in os.listdir(images_path)]
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for i in range(len(all_images)):
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# conf 置信度在.
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results = model(all_images[i],
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conf = 0.2, device=0)
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# # Process results list
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# = 0
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# for result in results:
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# boxes = result.boxes # Boxes object for bounding box outputs
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# # masks = result.masks # Masks object for segmentation masks outputs
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# # keypoints = result.keypoints # Keypoints object for pose outputs
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# # 属于这个类的置信度
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# probs = result.probs # Probs object for classification outputs
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# # obb = result.obb # Oriented boxes object for OBB outputs
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# print(boxes,' ',probs)
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# # result.show() # display to screen
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results[0].save(filename=f"{save_path}/result_{i}.jpg") # save to disk
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# i += 1 |