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Fix Docs calls to model.benchmark() (#18391)

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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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Glenn Jocher 2024-12-25 14:11:42 +01:00 • committed by GitHub
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4 changed files with 5 additions and 5 deletions
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2
docs/en/guides/nvidia-jetson.md
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@ -574,7 +574,7 @@ To reproduce the above Ultralytics benchmarks on all export [formats](../modes/e
model = YOLO("yolo11n.pt")
# Benchmark YOLO11n speed and accuracy on the COCO8 dataset for all all export formats
results = model.benchmarks(data="coco8.yaml", imgsz=640)
results = model.benchmark(data="coco8.yaml", imgsz=640)
```
=== "CLI"

2
docs/en/guides/raspberry-pi.md
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@ -201,7 +201,7 @@ To reproduce the above Ultralytics benchmarks on all [export formats](../modes/e
model = YOLO("yolo11n.pt")
# Benchmark YOLO11n speed and accuracy on the COCO8 dataset for all all export formats
results = model.benchmarks(data="coco8.yaml", imgsz=640)
results = model.benchmark(data="coco8.yaml", imgsz=640)
```
=== "CLI"

4
docs/en/integrations/openvino.md
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@ -352,7 +352,7 @@ To reproduce the Ultralytics benchmarks above on all export [formats](../modes/e
model = YOLO("yolov8n.pt")
# Benchmark YOLOv8n speed and accuracy on the COCO8 dataset for all export formats
results = model.benchmarks(data="coco8.yaml")
results = model.benchmark(data="coco8.yaml")
```
=== "CLI"
@ -466,7 +466,7 @@ Yes, you can benchmark YOLOv8 models in various formats including PyTorch, Torch
model = YOLO("yolov8n.pt")
# Benchmark YOLOv8n speed and [accuracy](https://www.ultralytics.com/glossary/accuracy) on the COCO8 dataset for all export formats
results = model.benchmarks(data="coco8.yaml")
results = model.benchmark(data="coco8.yaml")
```
=== "CLI"

2
ultralytics/solutions/streamlit_inference.py
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@ -150,7 +150,7 @@ class Inference:
while cap.isOpened():
success, frame = cap.read()
if not success:
st.warning("Failed to read frame from webcam. Please make sure the webcam is connected properly.")
self.st.warning("Failed to read frame from webcam. Please verify the webcam is connected properly.")
break
prev_time = time.time() # Store initial time for FPS calculation