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This commit is contained in:
Gabriel Grant 2025-02-15 21:12:08 -05:00
parent 593f7d05d6
commit fea64fa93a
5 changed files with 87 additions and 75 deletions
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4
frigate/config/camera/camera.py
View File

@ -63,9 +63,7 @@ class CameraConfig(FrigateBaseModel):
motion: Optional[MotionConfig] = Field(
None, title="Motion detection configuration."
)
motion_paths: Optional[MotionPathConfig] = Field(
None, title="Enable motion paths."
)
motion_paths: Optional[MotionPathConfig] = Field(None, title="Enable motion paths.")
objects: ObjectConfig = Field(
default_factory=ObjectConfig, title="Object configuration."
)

6
frigate/config/camera/motion_path.py
View File

@ -26,10 +26,10 @@ class MotionPathConfig(FrigateBaseModel):
def serialize_raw_mask(self, value: Any, info):
return None
@validator('max_history')
@validator("max_history")
def max_history_range(cls, v):
if v < 2:
raise ValueError('max_history must be >= 2')
raise ValueError("max_history must be >= 2")
if v > 100:
raise ValueError('max_history must be <= 100')
raise ValueError("max_history must be <= 100")
return v

42
frigate/motion/path_visualizer.py
View File

@ -3,6 +3,7 @@ import numpy as np
from typing import Dict, List, Tuple
from filterpy.kalman import KalmanFilter
class PathVisualizer:
def __init__(self, history_length: int = 30, prediction_length: int = 15):
self.history_length = history_length
@ -12,21 +13,22 @@ class PathVisualizer:
def _init_kalman(self, object_id: str, initial_pos: Tuple[int, int]):
"""Initialize Kalman filter for new object with position and velocity state"""
kf = KalmanFilter(dim_x=4, dim_z=2) # State: [x, y, vx, vy], Measurement: [x, y]
kf = KalmanFilter(
dim_x=4, dim_z=2
) # State: [x, y, vx, vy], Measurement: [x, y]
# State transition matrix
kf.F = np.array([
[1, 0, 1, 0], # x = x + vx
[0, 1, 0, 1], # y = y + vy
[0, 0, 1, 0], # vx = vx
[0, 0, 0, 1], # vy = vy
])
kf.F = np.array(
[
[1, 0, 1, 0], # x = x + vx
[0, 1, 0, 1], # y = y + vy
[0, 0, 1, 0], # vx = vx
[0, 0, 0, 1], # vy = vy
]
)
# Measurement matrix
kf.H = np.array([
[1, 0, 0, 0],
[0, 1, 0, 0]
])
kf.H = np.array([[1, 0, 0, 0], [0, 1, 0, 0]])
# Measurement noise
kf.R = np.eye(2) * 5
@ -60,9 +62,13 @@ class PathVisualizer:
# Trim history
if len(self.position_history[object_id]) > self.history_length:
self.position_history[object_id] = self.position_history[object_id][-self.history_length:]
self.position_history[object_id] = self.position_history[object_id][
-self.history_length :
]
def predict_path(self, object_id: str, frame_shape: Tuple[int, int]) -> List[Tuple[int, int]]:
def predict_path(
self, object_id: str, frame_shape: Tuple[int, int]
) -> List[Tuple[int, int]]:
"""Predict future path using Kalman filter"""
if object_id not in self.kalman_filters:
return []
@ -106,12 +112,12 @@ class PathVisualizer:
# Color transitions from blue to green (past to present)
alpha = i / len(positions)
color = (
int(255 * (1-alpha)), # Blue
int(255 * alpha), # Green
0 # Red
int(255 * (1 - alpha)), # Blue
int(255 * alpha), # Green
0, # Red
)
start_pos = positions[i-1]
start_pos = positions[i - 1]
end_pos = positions[i]
# Draw line with anti-aliasing
@ -124,7 +130,7 @@ class PathVisualizer:
alpha = 1 - (i / len(predictions))
color = (0, 0, 255) # Red
start_pos = predictions[i-1]
start_pos = predictions[i - 1]
end_pos = predictions[i]
# Create overlay for alpha blending

16
frigate/object_processing.py
View File

@ -236,7 +236,8 @@ class CameraState:
if draw_options.get("motion_paths"):
# Update and draw paths for non-stationary objects
active_objects = [
obj_id for obj_id, obj in tracked_objects.items()
obj_id
for obj_id, obj in tracked_objects.items()
if not obj["stationary"] and obj["frame_time"] == frame_time
]
@ -245,7 +246,7 @@ class CameraState:
obj = tracked_objects[obj_id]
centroid = (
int((obj["box"][0] + obj["box"][2]) / 2), # x center
int((obj["box"][1] + obj["box"][3]) / 2) # y center
int((obj["box"][1] + obj["box"][3]) / 2), # y center
)
self.path_visualizer.update_position(obj_id, centroid)
@ -445,7 +446,9 @@ class CameraState:
def update_paths(self, id: str, obj: TrackedObject):
"""Store motion path data globally if movement exceeds motion threshold."""
motion_paths_config = self.camera_config.motion_paths or self.config.motion_paths
motion_paths_config = (
self.camera_config.motion_paths or self.config.motion_paths
)
if motion_paths_config is None:
return
@ -455,16 +458,15 @@ class CameraState:
current_box = obj.obj_data["box"]
current_centroid = (
int((current_box[0] + current_box[2]) / 2),
int((current_box[1] + current_box[3]) / 2)
int((current_box[1] + current_box[3]) / 2),
)
history = self.path_history[self.name][id]
if history and len(history) > 0:
prev_pos = history[-1]
# Calculate motion delta
delta = (
abs(current_centroid[0] - prev_pos[0]) +
abs(current_centroid[1] - prev_pos[1])
delta = abs(current_centroid[0] - prev_pos[0]) + abs(
current_centroid[1] - prev_pos[1]
)
if delta > motion_threshold:
history.append(current_centroid)

16
frigate/track/tracked_object.py
View File

@ -395,7 +395,13 @@ class TrackedObject:
return None
def get_jpg_bytes(
self, timestamp=False, bounding_box=False, motion_paths=False, crop=False, height=None, quality=70
self,
timestamp=False,
bounding_box=False,
motion_paths=False,
crop=False,
height=None,
quality=70,
):
if self.thumbnail_data is None:
return None
@ -455,14 +461,14 @@ class TrackedObject:
if len(positions) > 1:
# Draw lines connecting positions
for i in range(1, len(positions)):
start_pos = positions[i-1]
start_pos = positions[i - 1]
end_pos = positions[i]
# Color transitions from blue to green (past to present)
alpha = i / len(positions)
color = (
int(255 * (1-alpha)), # Blue
int(255 * alpha), # Green
0 # Red
int(255 * (1 - alpha)), # Blue
int(255 * alpha), # Green
0, # Red
)
cv2.line(best_frame, start_pos, end_pos, color, 2, cv2.LINE_AA)