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Simplify Solutions Docs code examples (#17493)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Muhammad Rizwan Munawar 2024-11-12 14:57:00 +05:00 • committed by GitHub
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12
docs/en/guides/speed-estimation.md
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@ -61,16 +61,24 @@ keywords: Ultralytics YOLO11, speed estimation, object tracking, computer vision
from ultralytics import solutions
cap = cv2.VideoCapture("Path/to/video/file.mp4")
assert cap.isOpened(), "Error reading video file"
w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))
# Video writer
video_writer = cv2.VideoWriter("speed_management.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
# Define speed region points
speed_region = [(20, 400), (1080, 404), (1080, 360), (20, 360)]
speed = solutions.SpeedEstimator(model="yolo11n.pt", region=speed_region, show=True)
speed = solutions.SpeedEstimator(
show=True, # Display the output
model="yolo11n-pose.pt", # Path to the YOLO11 model file.
region=speed_region, # Pass region points
# classes=[0, 2], # If you want to estimate speed of specific classes.
# line_width=2, # Adjust the line width for bounding boxes and text display
)
# Process video
while cap.isOpened():
success, im0 = cap.read()