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66 lines
3.9 KiB
66 lines
3.9 KiB
1 year ago
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---
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comments: true
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description: Workouts Monitoring Using Ultralytics YOLOv8
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keywords: Ultralytics, YOLOv8, Object Detection, Pose Estimation, PushUps, PullUps, Ab workouts, Notebook, IPython Kernel, CLI, Python SDK
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---
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# Workouts Monitoring using Ultralytics YOLOv8 🚀
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Monitoring workouts through pose estimation with [Ultralytics YOLOv8](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.
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## Advantages of Workouts Monitoring?
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- **Optimized Performance:** Tailoring workouts based on monitoring data for better results.
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- **Goal Achievement:** Track and adjust fitness goals for measurable progress.
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- **Personalization:** Customized workout plans based on individual data for effectiveness.
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- **Health Awareness:** Early detection of patterns indicating health issues or overtraining.
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- **Informed Decisions:** Data-driven decisions for adjusting routines and setting realistic goals.
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## Real World Applications
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| Workouts Monitoring | Workouts Monitoring |
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|:----------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------------:|
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|  |  |
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| PushUps Counting | PullUps Counting |
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## Example
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```python
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from ultralytics import YOLO
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from ultralytics.solutions import ai_gym
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import cv2
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model = YOLO("yolov8n-pose.pt")
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cap = cv2.VideoCapture("path/to/video.mp4")
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gym_object = ai_gym.AIGym() # init AI GYM module
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gym_object.set_args(line_thickness=2, view_img=True, pose_type="pushup", kpts_to_check=[6, 8, 10])
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frame_count = 0
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while cap.isOpened():
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success, frame = cap.read()
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if not success: exit(0)
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frame_count += 1
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results = model.predict(frame, verbose=False)
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gym_object.start_counting(frame, results, frame_count)
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```
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???+ tip "Support"
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"pushup", "pullup" and "abworkout" supported
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### KeyPoints Map
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### Arguments `set_args`
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| Name | Type | Default | Description |
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|-----------------|--------|----------|----------------------------------------------------------------------------------------|
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| kpts_to_check | `list` | `None` | List of three keypoints index, for counting specific workout, followed by keypoint Map |
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| view_img | `bool` | `False` | Display the frame with counts |
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| line_thickness | `int` | `2` | Increase the thickness of count value |
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| pose_type | `str` | `pushup` | Pose that need to be monitored, "pullup" and "abworkout" also supported |
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| pose_up_angle | `int` | `145` | Pose Up Angle value |
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| pose_down_angle | `int` | `90` | Pose Down Angle value |
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