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Standardize default region points in docs (#17721)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2024-11-25 14:57:28 +05:00 • committed by GitHub
parent 9470f91c4d
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6 changed files with 17 additions and 17 deletions
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8
docs/en/guides/heatmaps.md
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@ -49,7 +49,7 @@ A heatmap generated with [Ultralytics YOLO11](https://github.com/ultralytics/ult
yolo solutions heatmap colormap=cv2.COLORMAP_INFERNO yolo solutions heatmap colormap=cv2.COLORMAP_INFERNO
# Heatmaps + object counting # Heatmaps + object counting
yolo solutions heatmap region=[(20, 400), (1080, 404), (1080, 360), (20, 360)] yolo solutions heatmap region=[(20, 400), (1080, 400), (1080, 360), (20, 360)]
``` ```
=== "Python" === "Python"
@ -67,9 +67,9 @@ A heatmap generated with [Ultralytics YOLO11](https://github.com/ultralytics/ult
video_writer = cv2.VideoWriter("heatmap_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h)) video_writer = cv2.VideoWriter("heatmap_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
# In case you want to apply object counting + heatmaps, you can pass region points. # In case you want to apply object counting + heatmaps, you can pass region points.
# region_points = [(20, 400), (1080, 404)] # Define line points # region_points = [(20, 400), (1080, 400)] # Define line points
# region_points = [(20, 400), (1080, 404), (1080, 360), (20, 360)] # Define region points # region_points = [(20, 400), (1080, 400), (1080, 360), (20, 360)] # Define region points
# region_points = [(20, 400), (1080, 404), (1080, 360), (20, 360), (20, 400)] # Define polygon points # region_points = [(20, 400), (1080, 400), (1080, 360), (20, 360), (20, 400)] # Define polygon points
# Init heatmap # Init heatmap
heatmap = solutions.Heatmap( heatmap = solutions.Heatmap(

8
docs/en/guides/object-counting.md
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@ -58,7 +58,7 @@ Object counting with [Ultralytics YOLO11](https://github.com/ultralytics/ultraly
yolo solutions count source="path/to/video/file.mp4" yolo solutions count source="path/to/video/file.mp4"
# Pass region coordinates # Pass region coordinates
yolo solutions count region=[(20, 400), (1080, 404), (1080, 360), (20, 360)] yolo solutions count region=[(20, 400), (1080, 400), (1080, 360), (20, 360)]
``` ```
=== "Python" === "Python"
@ -74,8 +74,8 @@ Object counting with [Ultralytics YOLO11](https://github.com/ultralytics/ultraly
# Define region points # Define region points
# region_points = [(20, 400), (1080, 400)] # For line counting # region_points = [(20, 400), (1080, 400)] # For line counting
region_points = [(20, 400), (1080, 404), (1080, 360), (20, 360)] # For rectangle region counting region_points = [(20, 400), (1080, 400), (1080, 360), (20, 360)] # For rectangle region counting
# region_points = [(20, 400), (1080, 404), (1080, 360), (20, 360), (20, 400)] # For polygon region counting # region_points = [(20, 400), (1080, 400), (1080, 360), (20, 360), (20, 400)] # For polygon region counting
# Video writer # Video writer
video_writer = cv2.VideoWriter("object_counting_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h)) video_writer = cv2.VideoWriter("object_counting_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
@ -148,7 +148,7 @@ def count_objects_in_region(video_path, output_video_path, model_path):
w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS)) 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 = cv2.VideoWriter(output_video_path, cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h)) video_writer = cv2.VideoWriter(output_video_path, cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
region_points = [(20, 400), (1080, 404), (1080, 360), (20, 360)] region_points = [(20, 400), (1080, 400), (1080, 360), (20, 360)]
counter = solutions.ObjectCounter(show=True, region=region_points, model=model_path) counter = solutions.ObjectCounter(show=True, region=region_points, model=model_path)
while cap.isOpened(): while cap.isOpened():

8
docs/en/guides/queue-management.md
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@ -45,7 +45,7 @@ Queue management using [Ultralytics YOLO11](https://github.com/ultralytics/ultra
yolo solutions queue source="path/to/video/file.mp4" yolo solutions queue source="path/to/video/file.mp4"
# Pass queue coordinates # Pass queue coordinates
yolo solutions queue region=[(20, 400), (1080, 404), (1080, 360), (20, 360)] yolo solutions queue region=[(20, 400), (1080, 400), (1080, 360), (20, 360)]
``` ```
=== "Python" === "Python"
@ -64,8 +64,8 @@ Queue management using [Ultralytics YOLO11](https://github.com/ultralytics/ultra
video_writer = cv2.VideoWriter("queue_management.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h)) video_writer = cv2.VideoWriter("queue_management.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
# Define queue region points # Define queue region points
queue_region = [(20, 400), (1080, 404), (1080, 360), (20, 360)] # Define queue region points queue_region = [(20, 400), (1080, 400), (1080, 360), (20, 360)] # Define queue region points
# queue_region = [(20, 400), (1080, 404), (1080, 360), (20, 360), (20, 400)] # Define queue polygon points # queue_region = [(20, 400), (1080, 400), (1080, 360), (20, 360), (20, 400)] # Define queue polygon points
# Init Queue Manager # Init Queue Manager
queue = solutions.QueueManager( queue = solutions.QueueManager(
@ -126,7 +126,7 @@ import cv2
from ultralytics import solutions from ultralytics import solutions
cap = cv2.VideoCapture("path/to/video.mp4") cap = cv2.VideoCapture("path/to/video.mp4")
queue_region = [(20, 400), (1080, 404), (1080, 360), (20, 360)] queue_region = [(20, 400), (1080, 400), (1080, 360), (20, 360)]
queue = solutions.QueueManager( queue = solutions.QueueManager(
model="yolo11n.pt", model="yolo11n.pt",

2
docs/en/guides/region-counting.md
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@ -47,7 +47,7 @@ keywords: object counting, regions, YOLOv8, computer vision, Ultralytics, effici
w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS)) w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))
# Define region points # Define region points
# region_points = [(20, 400), (1080, 404), (1080, 360), (20, 360)] # Pass region as list # region_points = [(20, 400), (1080, 400), (1080, 360), (20, 360)] # Pass region as list
# pass region as dictionary # pass region as dictionary
region_points = { region_points = {

4
docs/en/guides/speed-estimation.md
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@ -50,7 +50,7 @@ keywords: Ultralytics YOLO11, speed estimation, object tracking, computer vision
yolo solutions speed source="path/to/video/file.mp4" yolo solutions speed source="path/to/video/file.mp4"
# Pass region coordinates # Pass region coordinates
yolo solutions speed region=[(20, 400), (1080, 404), (1080, 360), (20, 360)] yolo solutions speed region=[(20, 400), (1080, 400), (1080, 360), (20, 360)]
``` ```
=== "Python" === "Python"
@ -68,7 +68,7 @@ keywords: Ultralytics YOLO11, speed estimation, object tracking, computer vision
video_writer = cv2.VideoWriter("speed_management.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h)) video_writer = cv2.VideoWriter("speed_management.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
# Define speed region points # Define speed region points
speed_region = [(20, 400), (1080, 404), (1080, 360), (20, 360)] speed_region = [(20, 400), (1080, 400), (1080, 360), (20, 360)]
speed = solutions.SpeedEstimator( speed = solutions.SpeedEstimator(
show=True, # Display the output show=True, # Display the output

4
ultralytics/cfg/__init__.py
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@ -83,13 +83,13 @@ SOLUTIONS_HELP_MSG = f"""
See all ARGS at https://docs.ultralytics.com/usage/cfg or with 'yolo cfg' See all ARGS at https://docs.ultralytics.com/usage/cfg or with 'yolo cfg'
1. Call object counting solution 1. Call object counting solution
yolo solutions count source="path/to/video/file.mp4" region=[(20, 400), (1080, 404), (1080, 360), (20, 360)] yolo solutions count source="path/to/video/file.mp4" region=[(20, 400), (1080, 400), (1080, 360), (20, 360)]
2. Call heatmaps solution 2. Call heatmaps solution
yolo solutions heatmap colormap=cv2.COLORMAP_PARAULA model=yolo11n.pt yolo solutions heatmap colormap=cv2.COLORMAP_PARAULA model=yolo11n.pt
3. Call queue management solution 3. Call queue management solution
yolo solutions queue region=[(20, 400), (1080, 404), (1080, 360), (20, 360)] model=yolo11n.pt yolo solutions queue region=[(20, 400), (1080, 400), (1080, 360), (20, 360)] model=yolo11n.pt
4. Call workouts monitoring solution for push-ups 4. Call workouts monitoring solution for push-ups
yolo solutions workout model=yolo11n-pose.pt kpts=[6, 8, 10] yolo solutions workout model=yolo11n-pose.pt kpts=[6, 8, 10]