Fix Docs calls to model.benchmark() (#18391)
Signed-off-by: UltralyticsAssistant <web@ultralytics.com> Signed-off-by: Kishan Pankajbhai Pipariya <39761387+KishanPipariya@users.noreply.github.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Kishan Pankajbhai Pipariya <39761387+KishanPipariya@users.noreply.github.com>
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4 changed files with 5 additions and 5 deletions
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@ -574,7 +574,7 @@ To reproduce the above Ultralytics benchmarks on all export [formats](../modes/e
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model = YOLO("yolo11n.pt")
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model = YOLO("yolo11n.pt")
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# Benchmark YOLO11n speed and accuracy on the COCO8 dataset for all all export formats
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# Benchmark YOLO11n speed and accuracy on the COCO8 dataset for all all export formats
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results = model.benchmarks(data="coco8.yaml", imgsz=640)
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results = model.benchmark(data="coco8.yaml", imgsz=640)
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```
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```
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=== "CLI"
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=== "CLI"
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@ -201,7 +201,7 @@ To reproduce the above Ultralytics benchmarks on all [export formats](../modes/e
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model = YOLO("yolo11n.pt")
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model = YOLO("yolo11n.pt")
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# Benchmark YOLO11n speed and accuracy on the COCO8 dataset for all all export formats
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# Benchmark YOLO11n speed and accuracy on the COCO8 dataset for all all export formats
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results = model.benchmarks(data="coco8.yaml", imgsz=640)
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results = model.benchmark(data="coco8.yaml", imgsz=640)
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```
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```
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=== "CLI"
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=== "CLI"
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@ -352,7 +352,7 @@ To reproduce the Ultralytics benchmarks above on all export [formats](../modes/e
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model = YOLO("yolov8n.pt")
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model = YOLO("yolov8n.pt")
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# Benchmark YOLOv8n speed and accuracy on the COCO8 dataset for all export formats
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# Benchmark YOLOv8n speed and accuracy on the COCO8 dataset for all export formats
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results = model.benchmarks(data="coco8.yaml")
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results = model.benchmark(data="coco8.yaml")
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```
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```
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=== "CLI"
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=== "CLI"
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@ -466,7 +466,7 @@ Yes, you can benchmark YOLOv8 models in various formats including PyTorch, Torch
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model = YOLO("yolov8n.pt")
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model = YOLO("yolov8n.pt")
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# Benchmark YOLOv8n speed and [accuracy](https://www.ultralytics.com/glossary/accuracy) on the COCO8 dataset for all export formats
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# Benchmark YOLOv8n speed and [accuracy](https://www.ultralytics.com/glossary/accuracy) on the COCO8 dataset for all export formats
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results = model.benchmarks(data="coco8.yaml")
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results = model.benchmark(data="coco8.yaml")
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```
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```
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=== "CLI"
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=== "CLI"
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@ -150,7 +150,7 @@ class Inference:
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while cap.isOpened():
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while cap.isOpened():
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success, frame = cap.read()
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success, frame = cap.read()
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if not success:
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if not success:
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st.warning("Failed to read frame from webcam. Please make sure the webcam is connected properly.")
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self.st.warning("Failed to read frame from webcam. Please verify the webcam is connected properly.")
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break
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break
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prev_time = time.time() # Store initial time for FPS calculation
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prev_time = time.time() # Store initial time for FPS calculation
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