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Add multiple lines graph support in `analytics` 8.2.26 (#13214)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
pull/13264/head v8.2.26
Muhammad Rizwan Munawar 6 months ago committed by GitHub
parent fbd8fdb53e
commit f67f5d707b
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3 changed files with 128 additions and 18 deletions
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  1. 91
      docs/en/guides/analytics.md
  2. 2
      ultralytics/__init__.py
  3. 53
      ultralytics/solutions/analytics.py

91
docs/en/guides/analytics.md
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@ -71,6 +71,66 @@ This guide provides a comprehensive overview of three fundamental types of data
out.release()
cv2.destroyAllWindows()
```
=== "Multiple Lines"
```python
import cv2
from ultralytics import YOLO, solutions
model = YOLO("yolov8s.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))
out = cv2.VideoWriter("multiple_line_plot.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
analytics = solutions.Analytics(
type="line",
writer=out,
im0_shape=(w, h),
view_img=True,
max_points=200,
)
frame_count = 0
data = {}
labels = []
while cap.isOpened():
success, frame = cap.read()
if success:
frame_count += 1
results = model.track(frame, persist=True)
if results[0].boxes.id is not None:
boxes = results[0].boxes.xyxy.cpu()
track_ids = results[0].boxes.id.int().cpu().tolist()
clss = results[0].boxes.cls.cpu().tolist()
for box, track_id, cls in zip(boxes, track_ids, clss):
# Store each class label
if model.names[int(cls)] not in labels:
labels.append(model.names[int(cls)])
# Store each class count
if model.names[int(cls)] in data:
data[model.names[int(cls)]] += 1
else:
data[model.names[int(cls)]] = 0
# update lines every frame
analytics.update_multiple_lines(data, labels, frame_count)
data = {} # clear the data list for next frame
else:
break
cap.release()
out.release()
cv2.destroyAllWindows()
```
=== "Pie Chart"
@ -174,21 +234,22 @@ This guide provides a comprehensive overview of three fundamental types of data
Here's a table with the `Analytics` arguments:
| Name | Type | Default | Description |
|--------------|-------------------|---------------|-------------------------------------|
| `type` | `str` | `None` | Type of data or object. |
| `im0_shape` | `tuple` | `None` | Shape of the initial image. |
| `writer` | `cv2.VideoWriter` | `None` | Object for writing video files. |
| `title` | `str` | `ultralytics` | Title for the visualization. |
| `x_label` | `str` | `x` | Label for the x-axis. |
| `y_label` | `str` | `y` | Label for the y-axis. |
| `bg_color` | `str` | `white` | Background color. |
| `fg_color` | `str` | `black` | Foreground color. |
| `line_color` | `str` | `yellow` | Color of the lines. |
| `line_width` | `int` | `2` | Width of the lines. |
| `fontsize` | `int` | `13` | Font size for text. |
| `view_img` | `bool` | `False` | Flag to display the image or video. |
| `save_img` | `bool` | `True` | Flag to save the image or video. |
| Name | Type | Default | Description |
|--------------|-------------------|---------------|----------------------------------------------------------------------------------|
| `type` | `str` | `None` | Type of data or object. |
| `im0_shape` | `tuple` | `None` | Shape of the initial image. |
| `writer` | `cv2.VideoWriter` | `None` | Object for writing video files. |
| `title` | `str` | `ultralytics` | Title for the visualization. |
| `x_label` | `str` | `x` | Label for the x-axis. |
| `y_label` | `str` | `y` | Label for the y-axis. |
| `bg_color` | `str` | `white` | Background color. |
| `fg_color` | `str` | `black` | Foreground color. |
| `line_color` | `str` | `yellow` | Color of the lines. |
| `line_width` | `int` | `2` | Width of the lines. |
| `fontsize` | `int` | `13` | Font size for text. |
| `view_img` | `bool` | `False` | Flag to display the image or video. |
| `save_img` | `bool` | `True` | Flag to save the image or video. |
| `max_points` | `int` | `50` | For multiple lines, total points drawn on frame, before deleting initial points. |
### Arguments `model.track`

2
ultralytics/__init__.py
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@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = "8.2.25"
__version__ = "8.2.26"
import os

53
ultralytics/solutions/analytics.py
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@ -1,5 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
import warnings
from itertools import cycle
import cv2
@ -27,6 +28,7 @@ class Analytics:
fontsize=13,
view_img=False,
save_img=True,
max_points=50,
):
"""
Initialize the Analytics class with various chart types.
@ -45,6 +47,7 @@ class Analytics:
fontsize (int): Font size for chart text.
view_img (bool): Whether to display the image.
save_img (bool): Whether to save the image.
max_points (int): Specifies when to remove the oldest points in a graph for multiple lines.
"""
self.bg_color = bg_color
@ -53,12 +56,14 @@ class Analytics:
self.save_img = save_img
self.title = title
self.writer = writer
self.max_points = max_points
# Set figure size based on image shape
figsize = (im0_shape[0] / 100, im0_shape[1] / 100)
if type == "line":
# Initialize line plot
self.lines = {}
fig = Figure(facecolor=self.bg_color, figsize=figsize)
self.canvas = FigureCanvas(fig)
self.ax = fig.add_subplot(111, facecolor=self.bg_color)
@ -112,9 +117,53 @@ class Analytics:
self.ax.autoscale_view()
self.canvas.draw()
im0 = np.array(self.canvas.renderer.buffer_rgba())
im0 = cv2.cvtColor(im0[:, :, :3], cv2.COLOR_RGBA2BGR)
self.write_and_display_line(im0)
# Display and save the updated graph
def update_multiple_lines(self, counts_dict, labels_list, frame_number):
"""
Update the line graph with multiple classes.
Args:
counts_dict (int): Dictionary include each class counts.
labels_list (int): list include each classes names.
frame_number (int): The current frame number.
"""
warnings.warn("Display is not supported for multiple lines, output will be stored normally!")
for obj in labels_list:
if obj not in self.lines:
(line,) = self.ax.plot([], [], label=obj, marker="o", markersize=15)
self.lines[obj] = line
x_data = self.lines[obj].get_xdata()
y_data = self.lines[obj].get_ydata()
# Remove the initial point if the number of points exceeds max_points
if len(x_data) >= self.max_points:
x_data = np.delete(x_data, 0)
y_data = np.delete(y_data, 0)
x_data = np.append(x_data, float(frame_number)) # Ensure frame_number is converted to float
y_data = np.append(y_data, float(counts_dict.get(obj, 0))) # Ensure total_count is converted to float
self.lines[obj].set_data(x_data, y_data)
self.ax.relim()
self.ax.autoscale_view()
self.ax.legend()
self.canvas.draw()
im0 = np.array(self.canvas.renderer.buffer_rgba())
self.view_img = False # for multiple line view_img not supported yet, coming soon!
self.write_and_display_line(im0)
def write_and_display_line(self, im0):
"""
Write and display the line graph
Args:
im0 (ndarray): Image for processing
"""
# convert image to BGR format
im0 = cv2.cvtColor(im0[:, :, :3], cv2.COLOR_RGBA2BGR)
cv2.imshow(self.title, im0) if self.view_img else None
self.writer.write(im0) if self.save_img else None

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