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Update workouts_monitoring solution (#16706)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
This commit is contained in:
Muhammad Rizwan Munawar 2024-10-05 18:08:37 +05:00 • committed by GitHub
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commit 73e6861d95
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7 changed files with 162 additions and 245 deletions
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4
docs/en/guides/object-counting.md
View file

@ -286,7 +286,7 @@ def count_objects_in_region(video_path, output_video_path, model_path):
if not success:
print("Video frame is empty or video processing has been successfully completed.")
break
im0 = counter.start_counting(im0)
im0 = counter.count(im0)
video_writer.write(im0)
cap.release()
@ -334,7 +334,7 @@ def count_specific_classes(video_path, output_video_path, model_path, classes_to
if not success:
print("Video frame is empty or video processing has been successfully completed.")
break
im0 = counter.start_counting(im0)
im0 = counter.count(im0)
video_writer.write(im0)
cap.release()

89
docs/en/guides/workouts-monitoring.md
View file

@ -41,18 +41,16 @@ Monitoring workouts through pose estimation with [Ultralytics YOLO11](https://gi
```python
import cv2
from ultralytics import YOLO, solutions
from ultralytics import solutions
model = YOLO("yolo11n-pose.pt")
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_object = solutions.AIGym(
line_thickness=2,
view_img=True,
pose_type="pushup",
kpts_to_check=[6, 8, 10],
gym = solutions.AIGym(
model="yolo11n-pose.pt",
show=True,
kpts=[6, 8, 10],
)
while cap.isOpened():
@ -60,9 +58,7 @@ Monitoring workouts through pose estimation with [Ultralytics YOLO11](https://gi
if not success:
print("Video frame is empty or video processing has been successfully completed.")
break
results = model.track(im0, verbose=False) # Tracking recommended
# results = model.predict(im0) # Prediction also supported
im0 = gym_object.start_counting(im0, results)
im0 = gym.monitor(im0)
cv2.destroyAllWindows()
```
@ -72,20 +68,17 @@ Monitoring workouts through pose estimation with [Ultralytics YOLO11](https://gi
```python
import cv2
from ultralytics import YOLO, solutions
from ultralytics import solutions
model = YOLO("yolo11n-pose.pt")
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_object = solutions.AIGym(
line_thickness=2,
view_img=True,
pose_type="pushup",
kpts_to_check=[6, 8, 10],
gym = solutions.AIGym(
show=True,
kpts=[6, 8, 10],
)
while cap.isOpened():
@ -93,33 +86,26 @@ Monitoring workouts through pose estimation with [Ultralytics YOLO11](https://gi
if not success:
print("Video frame is empty or video processing has been successfully completed.")
break
results = model.track(im0, verbose=False) # Tracking recommended
# results = model.predict(im0) # Prediction also supported
im0 = gym_object.start_counting(im0, results)
im0 = gym.monitor(im0)
video_writer.write(im0)
cv2.destroyAllWindows()
video_writer.release()
```
???+ tip "Support"
"pushup", "pullup" and "abworkout" supported
### KeyPoints Map
![keyPoints Order Ultralytics YOLO11 Pose](https://github.com/ultralytics/docs/releases/download/0/keypoints-order-ultralytics-yolov8-pose.avif)
### Arguments `AIGym`
| Name | Type | Default | Description |
| ----------------- | ------- | -------- | -------------------------------------------------------------------------------------- |
| `kpts_to_check` | `list` | `None` | List of three keypoints index, for counting specific workout, followed by keypoint Map |
| `line_thickness` | `int` | `2` | Thickness of the lines drawn. |
| `view_img` | `bool` | `False` | Flag to display the image. |
| `pose_up_angle` | `float` | `145.0` | Angle threshold for the 'up' pose. |
| `pose_down_angle` | `float` | `90.0` | Angle threshold for the 'down' pose. |
| `pose_type` | `str` | `pullup` | Type of pose to detect (`'pullup`', `pushup`, `abworkout`, `squat`). |
| Name | Type | Default | Description |
| ------------ | ------- | ------- | -------------------------------------------------------------------------------------- |
| `kpts` | `list` | `None` | List of three keypoints index, for counting specific workout, followed by keypoint Map |
| `line_width` | `int` | `2` | Thickness of the lines drawn. |
| `show` | `bool` | `False` | Flag to display the image. |
| `up_angle` | `float` | `145.0` | Angle threshold for the 'up' pose. |
| `down_angle` | `float` | `90.0` | Angle threshold for the 'down' pose. |
### Arguments `model.predict`
@ -138,18 +124,16 @@ To monitor your workouts using Ultralytics YOLO11, you can utilize the pose esti
```python
import cv2
from ultralytics import YOLO, solutions
from ultralytics import solutions
model = YOLO("yolo11n-pose.pt")
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_object = solutions.AIGym(
line_thickness=2,
view_img=True,
pose_type="pushup",
kpts_to_check=[6, 8, 10],
gym = solutions.AIGym(
line_width=2,
show=True,
kpts=[6, 8, 10],
)
while cap.isOpened():
@ -157,8 +141,7 @@ while cap.isOpened():
if not success:
print("Video frame is empty or video processing has been successfully completed.")
break
results = model.track(im0, verbose=False)
im0 = gym_object.start_counting(im0, results)
im0 = gym.monitor(im0)
cv2.destroyAllWindows()
```
@ -188,11 +171,10 @@ Yes, Ultralytics YOLO11 can be adapted for custom workout routines. The `AIGym`
```python
from ultralytics import solutions
gym_object = solutions.AIGym(
line_thickness=2,
view_img=True,
pose_type="squat",
kpts_to_check=[6, 8, 10],
gym = solutions.AIGym(
line_width=2,
show=True,
kpts=[6, 8, 10],
)
```
@ -205,20 +187,18 @@ To save the workout monitoring output, you can modify the code to include a vide
```python
import cv2
from ultralytics import YOLO, solutions
from ultralytics import solutions
model = YOLO("yolo11n-pose.pt")
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_object = solutions.AIGym(
line_thickness=2,
view_img=True,
pose_type="pushup",
kpts_to_check=[6, 8, 10],
gym = solutions.AIGym(
line_width=2,
show=True,
kpts=[6, 8, 10],
)
while cap.isOpened():
@ -226,8 +206,7 @@ while cap.isOpened():
if not success:
print("Video frame is empty or video processing has been successfully completed.")
break
results = model.track(im0, verbose=False)
im0 = gym_object.start_counting(im0, results)
im0 = gym.monitor(im0)
video_writer.write(im0)
cv2.destroyAllWindows()