216 lines
9.6 KiB
Markdown
216 lines
9.6 KiB
Markdown
---
|
|
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
|
|
|
|
<a href="https://colab.research.google.com/github/ultralytics/notebooks/blob/main/notebooks/how-to-monitor-workouts-using-ultralytics-yolo.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open Workouts Monitoring In Colab"></a>
|
|
|
|
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.
|
|
|
|
<p align="center">
|
|
<br>
|
|
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/LGGxqLZtvuw"
|
|
title="YouTube video player" frameborder="0"
|
|
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
|
|
allowfullscreen>
|
|
</iframe>
|
|
<br>
|
|
<strong>Watch:</strong> Workouts Monitoring using Ultralytics YOLO11 | Push-ups, Pull-ups, Ab Workouts
|
|
</p>
|
|
|
|
## 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.
|