---
comments: true
description: Optimize your fitness routine with real-time workouts monitoring using Ultralytics YOLO11. Track and improve your exercise form and performance.
keywords: workouts monitoring, Ultralytics YOLO11, pose estimation, fitness tracking, exercise assessment, real-time feedback, exercise form, performance metrics
---
# Workouts Monitoring using Ultralytics YOLO11
Monitoring workouts through pose estimation with [Ultralytics YOLO11](https://github.com/ultralytics/ultralytics/) 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: Workouts Monitoring using Ultralytics YOLO11 | Push-ups, Pull-ups, Ab Workouts
## Advantages of Workouts Monitoring
- **Optimized Performance:** Tailoring workouts based on monitoring data for better results.
- **Goal Achievement:** Track and adjust fitness goals for measurable progress.
- **Personalization:** Customized workout plans based on individual data for effectiveness.
- **Health Awareness:** Early detection of patterns indicating health issues or over-training.
- **Informed Decisions:** Data-driven decisions for adjusting routines and setting realistic goals.
## Real World Applications
| Workouts Monitoring | Workouts Monitoring |
| :------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------: |
|  |  |
| 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/file.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/file.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
```
### KeyPoints Map
### `AIGym` Arguments
Here'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"]) }}
## FAQ
### How do I monitor my workouts using Ultralytics YOLO11?
To monitor your workouts using Ultralytics YOLO11, you can utilize the [pose estimation capabilities](https://docs.ultralytics.com/tasks/pose/) 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:
```python
import cv2
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))
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](#aigym-arguments) section in the documentation.
### What are the benefits of using Ultralytics YOLO11 for workout monitoring?
Using Ultralytics YOLO11 for workout monitoring provides several key benefits:
- **Optimized Performance:** By tailoring workouts based on monitoring data, you can achieve better results.
- **Goal Achievement:** Easily track and adjust fitness goals for measurable progress.
- **Personalization:** Get customized workout plans based on your individual data for optimal effectiveness.
- **Health Awareness:** Early detection of patterns that indicate potential health issues or over-training.
- **Informed Decisions:** Make data-driven decisions to adjust routines and set realistic goals.
You can watch a [YouTube video demonstration](https://www.youtube.com/watch?v=LGGxqLZtvuw) to see these benefits in action.
### How accurate is Ultralytics YOLO11 in detecting and tracking exercises?
Ultralytics YOLO11 is highly accurate in detecting and tracking exercises due to its state-of-the-art [pose estimation](https://www.ultralytics.com/blog/how-to-use-ultralytics-yolo11-for-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](https://www.ultralytics.com/glossary/precision) and reliability. For real-world examples, check out the [real-world applications](#real-world-applications) section in the documentation, which showcases push-ups and pull-ups counting.
### Can I use Ultralytics YOLO11 for custom workout routines?
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:
```python
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`](#aigym-arguments) section. This flexibility allows you to monitor various exercises and customize routines based on your [fitness goals](https://www.ultralytics.com/blog/ai-in-our-day-to-day-health-and-fitness).
### How can I save the workout monitoring output using Ultralytics YOLO11?
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:
```python
import cv2
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 = 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.
