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ultralytics 8.0.216
fix hard-coded batch=64
cls loss (#6523)
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: HDW AI group <huzhongshan@gmail.com>
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@ -82,7 +82,7 @@ YOLOv3 श्रृंखला, इनमें YOLOv3, YOLOv3-Ultralytics औ
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अगर आप अपने शोध में YOLOv3 का उपयोग करते हैं, तो कृपया मूल YOLO पेपर्स और Ultralytics YOLOv3 रिपॉज़िटरी को उद्धृत करें।
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!!! उध्दरण ""
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!!! Quote ""
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=== "BibTeX"
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@ -72,8 +72,7 @@ YOLOv5u वस्तु ज्ञापन के तरीकों में
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model.info()
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# COCO8 प्रायोगिक उदाहरण डेटासेट पर 100 एपॉक के लिए मॉडल
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ka प्रशिक्षित करें results = model.train(data='coco8.yaml', epochs=100, imgsz=640)
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results = model.train(data='coco8.yaml', epochs=100, imgsz=640)
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# YOLOv5n मॉडल के साथ 'bus.jpg' छविमें ज्ञापन चलाएं
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results = model('path/to/bus.jpg')
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@ -36,7 +36,7 @@ Yएक मॉडल के हर मानक, विशिष्ट कार
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## प्रदर्शन की मापदंड
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!!! प्रदर्शन
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!!! Note "प्रदर्शन"
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=== "वस्तुनिर्धारण (COCO)"
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@ -188,6 +188,17 @@ nav:
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- الوضعية: tasks/pose.md
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- النماذج:
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- models/index.md
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- YOLOv3: models/yolov3.md
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- YOLOv4: models/yolov4.md
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- YOLOv5: models/yolov5.md
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- YOLOv6: models/yolov6.md
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- YOLOv7: models/yolov7.md
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- YOLOv8: models/yolov8.md
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- SAM (Segment Anything Model): models/sam.md
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- MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md
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- FastSAM (Fast Segment Anything Model): models/fast-sam.md
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- YOLO-NAS (Neural Architecture Search): models/yolo-nas.md
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- RT-DETR (Realtime Detection Transformer): models/rtdetr.md
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- المجموعات البيانية:
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- datasets/index.md
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@ -188,6 +188,17 @@ nav:
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- Pose: tasks/pose.md
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- Modelle:
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- models/index.md
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- YOLOv3: models/yolov3.md
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- YOLOv4: models/yolov4.md
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- YOLOv5: models/yolov5.md
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- YOLOv6: models/yolov6.md
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- YOLOv7: models/yolov7.md
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- YOLOv8: models/yolov8.md
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- SAM (Segment Anything Model): models/sam.md
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- MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md
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- FastSAM (Fast Segment Anything Model): models/fast-sam.md
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- YOLO-NAS (Neural Architecture Search): models/yolo-nas.md
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- RT-DETR (Realtime Detection Transformer): models/rtdetr.md
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- Datensätze:
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- datasets/index.md
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@ -188,6 +188,17 @@ nav:
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- Pose: tasks/pose.md
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- Modelos:
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- models/index.md
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- YOLOv3: models/yolov3.md
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- YOLOv4: models/yolov4.md
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- YOLOv5: models/yolov5.md
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- YOLOv6: models/yolov6.md
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- YOLOv7: models/yolov7.md
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- YOLOv8: models/yolov8.md
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- SAM (Segment Anything Model): models/sam.md
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- MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md
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- FastSAM (Fast Segment Anything Model): models/fast-sam.md
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- YOLO-NAS (Neural Architecture Search): models/yolo-nas.md
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- RT-DETR (Realtime Detection Transformer): models/rtdetr.md
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- Conjuntos de datos:
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- datasets/index.md
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@ -188,6 +188,17 @@ nav:
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- Pose: tasks/pose.md
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- Modèles:
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- models/index.md
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- YOLOv3: models/yolov3.md
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- YOLOv4: models/yolov4.md
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- YOLOv5: models/yolov5.md
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- YOLOv6: models/yolov6.md
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- YOLOv7: models/yolov7.md
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- YOLOv8: models/yolov8.md
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- SAM (Segment Anything Model): models/sam.md
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- MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md
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- FastSAM (Fast Segment Anything Model): models/fast-sam.md
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- YOLO-NAS (Neural Architecture Search): models/yolo-nas.md
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- RT-DETR (Realtime Detection Transformer): models/rtdetr.md
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- Jeux de données:
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- datasets/index.md
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@ -188,6 +188,17 @@ nav:
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- मुद्रा: tasks/pose.md
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- मॉडल:
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- models/index.md
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- YOLOv3: models/yolov3.md
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- YOLOv4: models/yolov4.md
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- YOLOv5: models/yolov5.md
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- YOLOv6: models/yolov6.md
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- YOLOv7: models/yolov7.md
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- YOLOv8: models/yolov8.md
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- SAM (Segment Anything Model): models/sam.md
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- MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md
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- FastSAM (Fast Segment Anything Model): models/fast-sam.md
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- YOLO-NAS (Neural Architecture Search): models/yolo-nas.md
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- RT-DETR (Realtime Detection Transformer): models/rtdetr.md
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- डेटासेट्स:
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- datasets/index.md
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@ -188,6 +188,17 @@ nav:
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- ポーズ: tasks/pose.md
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- モデル:
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- models/index.md
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- YOLOv3: models/yolov3.md
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- YOLOv4: models/yolov4.md
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- YOLOv5: models/yolov5.md
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- YOLOv6: models/yolov6.md
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- YOLOv7: models/yolov7.md
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- YOLOv8: models/yolov8.md
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- SAM (Segment Anything Model): models/sam.md
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- MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md
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- FastSAM (Fast Segment Anything Model): models/fast-sam.md
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- YOLO-NAS (Neural Architecture Search): models/yolo-nas.md
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- RT-DETR (Realtime Detection Transformer): models/rtdetr.md
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- データセット:
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- datasets/index.md
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@ -188,6 +188,17 @@ nav:
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- 포즈: tasks/pose.md
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- 모델:
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- models/index.md
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- YOLOv3: models/yolov3.md
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- YOLOv4: models/yolov4.md
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- YOLOv5: models/yolov5.md
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- YOLOv6: models/yolov6.md
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- YOLOv7: models/yolov7.md
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- YOLOv8: models/yolov8.md
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- SAM (Segment Anything Model): models/sam.md
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- MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md
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- FastSAM (Fast Segment Anything Model): models/fast-sam.md
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- YOLO-NAS (Neural Architecture Search): models/yolo-nas.md
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- RT-DETR (Realtime Detection Transformer): models/rtdetr.md
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- 데이터셋:
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- datasets/index.md
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- Pose: tasks/pose.md
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- Modelos:
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- models/index.md
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- YOLOv3: models/yolov3.md
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- YOLOv4: models/yolov4.md
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- YOLOv5: models/yolov5.md
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- YOLOv6: models/yolov6.md
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- YOLOv7: models/yolov7.md
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- YOLOv8: models/yolov8.md
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- SAM (Segment Anything Model): models/sam.md
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- MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md
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- FastSAM (Fast Segment Anything Model): models/fast-sam.md
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- YOLO-NAS (Neural Architecture Search): models/yolo-nas.md
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- RT-DETR (Realtime Detection Transformer): models/rtdetr.md
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- Conjuntos de Dados:
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- datasets/index.md
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- Поза: tasks/pose.md
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- Модели:
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- models/index.md
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- YOLOv3: models/yolov3.md
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- YOLOv4: models/yolov4.md
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- YOLOv5: models/yolov5.md
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- YOLOv6: models/yolov6.md
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- YOLOv7: models/yolov7.md
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- YOLOv8: models/yolov8.md
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- SAM (Segment Anything Model): models/sam.md
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- MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md
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- FastSAM (Fast Segment Anything Model): models/fast-sam.md
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- YOLO-NAS (Neural Architecture Search): models/yolo-nas.md
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- RT-DETR (Realtime Detection Transformer): models/rtdetr.md
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- Данные:
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- datasets/index.md
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- 姿态: tasks/pose.md
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- 模型:
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- models/index.md
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- YOLOv3: models/yolov3.md
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- YOLOv4: models/yolov4.md
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- YOLOv5: models/yolov5.md
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- YOLOv6: models/yolov6.md
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- YOLOv7: models/yolov7.md
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- YOLOv8: models/yolov8.md
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- SAM (Segment Anything Model): models/sam.md
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- MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md
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- FastSAM (Fast Segment Anything Model): models/fast-sam.md
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- YOLO-NAS (Neural Architecture Search): models/yolo-nas.md
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- RT-DETR (Realtime Detection Transformer): models/rtdetr.md
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- 数据集:
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- datasets/index.md
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@ -1,6 +1,6 @@
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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__version__ = '8.0.215'
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__version__ = '8.0.216'
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from ultralytics.models import RTDETR, SAM, YOLO
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from ultralytics.models.fastsam import FastSAM
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@ -523,6 +523,6 @@ class v8ClassificationLoss:
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def __call__(self, preds, batch):
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"""Compute the classification loss between predictions and true labels."""
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loss = torch.nn.functional.cross_entropy(preds, batch['cls'], reduction='sum') / 64
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loss = torch.nn.functional.cross_entropy(preds, batch['cls'], reduction='mean')
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loss_items = loss.detach()
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return loss, loss_items
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