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comments | description | keywords |
---|---|---|
true | Optimize your fitness routine with real-time workouts monitoring using Ultralytics YOLO11. Track and improve your exercise form and performance. | workouts monitoring, Ultralytics YOLO11, pose estimation, fitness tracking, exercise assessment, real-time feedback, exercise form, performance metrics |
Monitoring workouts through pose estimation with Ultralytics YOLO11 enhances exercise assessment by accurately tracking key body landmarks and joints in real-time. This technology provides instant feedback on exercise form, tracks workout routines, and measures performance metrics, optimizing training sessions for users and trainers alike.
Watch: How to Monitor Workout Exercises with Ultralytics YOLO | Squats, Leg Extension, Pushups and More
Workouts Monitoring | Workouts Monitoring |
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PushUps Counting | PullUps Counting |
!!! example "Workouts Monitoring using Ultralytics YOLO"
=== "CLI"
```bash
# Run a workout example
yolo solutions workout show=True
# Pass a source video
yolo solutions workout source="path/to/video.mp4"
# Use keypoints for pushups
yolo solutions workout kpts="[6, 8, 10]"
```
=== "Python"
```python
import cv2
from ultralytics import solutions
cap = cv2.VideoCapture("path/to/video.mp4")
assert cap.isOpened(), "Error reading video file"
# Video writer
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("workouts_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
# Init AIGym
gym = solutions.AIGym(
show=True, # display the frame
kpts=[6, 8, 10], # keypoints for monitoring specific exercise, by default it's for pushup
model="yolo11n-pose.pt", # path to the YOLO11 pose estimation model file
# line_width=2, # adjust the line width for bounding boxes and text display
)
# Process video
while cap.isOpened():
success, im0 = cap.read()
if not success:
print("Video frame is empty or processing is complete.")
break
results = gym(im0)
# print(results) # access the output
video_writer.write(results.plot_im) # write the processed frame.
cap.release()
video_writer.release()
cv2.destroyAllWindows() # destroy all opened windows
```
AIGym
ArgumentsHere's a table with the AIGym
arguments:
{% from "macros/solutions-args.md" import param_table %} {{ param_table(["model", "up_angle", "down_angle", "kpts"]) }}
The AIGym
solution also supports a range of object tracking parameters:
{% from "macros/track-args.md" import param_table %} {{ param_table(["tracker", "conf", "iou", "classes", "verbose", "device"]) }}
Additionally, the following visualization settings can be applied:
{% from "macros/visualization-args.md" import param_table %} {{ param_table(["show", "line_width", "show_conf", "show_labels"]) }}
To monitor your workouts using Ultralytics YOLO11, you can utilize the pose estimation capabilities to track and analyze key body landmarks and joints in real-time. This allows you to receive instant feedback on your exercise form, count repetitions, and measure performance metrics. You can start by using the provided example code for push-ups, pull-ups, or ab workouts as shown:
import cv2
from ultralytics import solutions
cap = cv2.VideoCapture("path/to/video.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))
gym = solutions.AIGym(
line_width=2,
show=True,
kpts=[6, 8, 10],
)
while cap.isOpened():
success, im0 = cap.read()
if not success:
print("Video frame is empty or processing is complete.")
break
results = gym(im0)
cv2.destroyAllWindows()
For further customization and settings, you can refer to the AIGym section in the documentation.
Using Ultralytics YOLO11 for workout monitoring provides several key benefits:
You can watch a YouTube video demonstration to see these benefits in action.
Ultralytics YOLO11 is highly accurate in detecting and tracking exercises due to its state-of-the-art pose estimation capabilities. It can accurately track key body landmarks and joints, providing real-time feedback on exercise form and performance metrics. The model's pretrained weights and robust architecture ensure high precision and reliability. For real-world examples, check out the real-world applications section in the documentation, which showcases push-ups and pull-ups counting.
Yes, Ultralytics YOLO11 can be adapted for custom workout routines. The AIGym
class supports different pose types such as pushup
, pullup
, and abworkout
. You can specify keypoints and angles to detect specific exercises. Here is an example setup:
from ultralytics import solutions
gym = solutions.AIGym(
line_width=2,
show=True,
kpts=[6, 8, 10], # For pushups - can be customized for other exercises
)
For more details on setting arguments, refer to the Arguments AIGym
section. This flexibility allows you to monitor various exercises and customize routines based on your fitness goals.
To save the workout monitoring output, you can modify the code to include a video writer that saves the processed frames. Here's an example:
import cv2
from ultralytics import solutions
cap = cv2.VideoCapture("path/to/video.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 = cv2.VideoWriter("workouts.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
gym = solutions.AIGym(
line_width=2,
show=True,
kpts=[6, 8, 10],
)
while cap.isOpened():
success, im0 = cap.read()
if not success:
print("Video frame is empty or processing is complete.")
break
results = gym(im0)
video_writer.write(results.plot_im)
cap.release()
video_writer.release()
cv2.destroyAllWindows()
This setup writes the monitored video to an output file, allowing you to review your workout performance later or share it with trainers for additional feedback.
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