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Refactor all Ultralytics Solutions (#12790)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: RizwanMunawar <chr043416@gmail.com>
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Glenn Jocher 2024-05-18 18:14:42 +02:00 • committed by GitHub
parent a2ecb24176
commit 2af71d15a6
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134 changed files with 845 additions and 1020 deletions
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118
ultralytics/solutions/speed_estimation.py
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@ -11,73 +11,52 @@ from ultralytics.utils.plotting import Annotator, colors
class SpeedEstimator:
"""A class to estimation speed of objects in real-time video stream based on their tracks."""
"""A class to estimate the speed of objects in a real-time video stream based on their tracks."""
def __init__(self):
"""Initializes the speed-estimator class with default values for Visual, Image, track and speed parameters."""
def __init__(self, names, reg_pts=None, view_img=False, line_thickness=2, region_thickness=5, spdl_dist_thresh=10):
"""
Initializes the SpeedEstimator with the given parameters.
# Visual & im0 information
Args:
names (dict): Dictionary of class names.
reg_pts (list, optional): List of region points for speed estimation. Defaults to [(20, 400), (1260, 400)].
view_img (bool, optional): Whether to display the image with annotations. Defaults to False.
line_thickness (int, optional): Thickness of the lines for drawing boxes and tracks. Defaults to 2.
region_thickness (int, optional): Thickness of the region lines. Defaults to 5.
spdl_dist_thresh (int, optional): Distance threshold for speed calculation. Defaults to 10.
"""
# Visual & image information
self.im0 = None
self.annotator = None
self.view_img = False
self.view_img = view_img
# Region information
self.reg_pts = [(20, 400), (1260, 400)]
self.region_thickness = 3
self.reg_pts = reg_pts if reg_pts is not None else [(20, 400), (1260, 400)]
self.region_thickness = region_thickness
# Predict/track information
# Tracking information
self.clss = None
self.names = None
self.names = names
self.boxes = None
self.trk_ids = None
self.trk_pts = None
self.line_thickness = 2
self.line_thickness = line_thickness
self.trk_history = defaultdict(list)
# Speed estimator information
# Speed estimation information
self.current_time = 0
self.dist_data = {}
self.trk_idslist = []
self.spdl_dist_thresh = 10
self.spdl_dist_thresh = spdl_dist_thresh
self.trk_previous_times = {}
self.trk_previous_points = {}
# Check if environment support imshow
# Check if the environment supports imshow
self.env_check = check_imshow(warn=True)
def set_args(
self,
reg_pts,
names,
view_img=False,
line_thickness=2,
region_thickness=5,
spdl_dist_thresh=10,
):
"""
Configures the speed estimation and display parameters.
Args:
reg_pts (list): Initial list of points defining the speed calculation region.
names (dict): object detection classes names
view_img (bool): Flag indicating frame display
line_thickness (int): Line thickness for bounding boxes.
region_thickness (int): Speed estimation region thickness
spdl_dist_thresh (int): Euclidean distance threshold for speed line
"""
if reg_pts is None:
print("Region points not provided, using default values")
else:
self.reg_pts = reg_pts
self.names = names
self.view_img = view_img
self.line_thickness = line_thickness
self.region_thickness = region_thickness
self.spdl_dist_thresh = spdl_dist_thresh
def extract_tracks(self, tracks):
"""
Extracts results from the provided data.
Extracts results from the provided tracking data.
Args:
tracks (list): List of tracks obtained from the object tracking process.
@ -88,11 +67,14 @@ class SpeedEstimator:
def store_track_info(self, track_id, box):
"""
Store track data.
Stores track data.
Args:
track_id (int): object track id.
box (list): object bounding box data
track_id (int): Object track id.
box (list): Object bounding box data.
Returns:
(list): Updated tracking history for the given track_id.
"""
track = self.trk_history[track_id]
bbox_center = (float((box[0] + box[2]) / 2), float((box[1] + box[3]) / 2))
@ -106,43 +88,39 @@ class SpeedEstimator:
def plot_box_and_track(self, track_id, box, cls, track):
"""
Plot track and bounding box.
Plots track and bounding box.
Args:
track_id (int): object track id.
box (list): object bounding box data
cls (str): object class name
track (list): tracking history for tracks path drawing
track_id (int): Object track id.
box (list): Object bounding box data.
cls (str): Object class name.
track (list): Tracking history for drawing tracks path.
"""
speed_label = f"{int(self.dist_data[track_id])}km/ph" if track_id in self.dist_data else self.names[int(cls)]
speed_label = f"{int(self.dist_data[track_id])} km/h" if track_id in self.dist_data else self.names[int(cls)]
bbox_color = colors(int(track_id)) if track_id in self.dist_data else (255, 0, 255)
self.annotator.box_label(box, speed_label, bbox_color)
cv2.polylines(self.im0, [self.trk_pts], isClosed=False, color=(0, 255, 0), thickness=1)
cv2.circle(self.im0, (int(track[-1][0]), int(track[-1][1])), 5, bbox_color, -1)
def calculate_speed(self, trk_id, track):
"""
Calculation of object speed.
Calculates the speed of an object.
Args:
trk_id (int): object track id.
track (list): tracking history for tracks path drawing
trk_id (int): Object track id.
track (list): Tracking history for drawing tracks path.
"""
if not self.reg_pts[0][0] < track[-1][0] < self.reg_pts[1][0]:
return
if self.reg_pts[1][1] - self.spdl_dist_thresh < track[-1][1] < self.reg_pts[1][1] + self.spdl_dist_thresh:
direction = "known"
elif self.reg_pts[0][1] - self.spdl_dist_thresh < track[-1][1] < self.reg_pts[0][1] + self.spdl_dist_thresh:
direction = "known"
else:
direction = "unknown"
if self.trk_previous_times[trk_id] != 0 and direction != "unknown" and trk_id not in self.trk_idslist:
if self.trk_previous_times.get(trk_id) != 0 and direction != "unknown" and trk_id not in self.trk_idslist:
self.trk_idslist.append(trk_id)
time_difference = time() - self.trk_previous_times[trk_id]
@ -156,21 +134,24 @@ class SpeedEstimator:
def estimate_speed(self, im0, tracks, region_color=(255, 0, 0)):
"""
Calculate object based on tracking data.
Estimates the speed of objects based on tracking data.
Args:
im0 (nd array): Image
im0 (ndarray): Image.
tracks (list): List of tracks obtained from the object tracking process.
region_color (tuple): Color to use when drawing regions.
region_color (tuple, optional): Color to use when drawing regions. Defaults to (255, 0, 0).
Returns:
(ndarray): The image with annotated boxes and tracks.
"""
self.im0 = im0
if tracks[0].boxes.id is None:
if self.view_img and self.env_check:
self.display_frames()
return im0
self.extract_tracks(tracks)
self.annotator = Annotator(self.im0, line_width=2)
self.extract_tracks(tracks)
self.annotator = Annotator(self.im0, line_width=self.line_thickness)
self.annotator.draw_region(reg_pts=self.reg_pts, color=region_color, thickness=self.region_thickness)
for box, trk_id, cls in zip(self.boxes, self.trk_ids, self.clss):
@ -188,11 +169,12 @@ class SpeedEstimator:
return im0
def display_frames(self):
"""Display frame."""
"""Displays the current frame."""
cv2.imshow("Ultralytics Speed Estimation", self.im0)
if cv2.waitKey(1) & 0xFF == ord("q"):
return
if __name__ == "__main__":
SpeedEstimator()
names = {0: "person", 1: "car"} # example class names
speed_estimator = SpeedEstimator(names)