Refactor all Ultralytics Solutions (#12790)
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
GitHub
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a2ecb24176
commit
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134 changed files with 845 additions and 1020 deletions
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@ -51,42 +51,39 @@ Object counting with [Ultralytics YOLOv8](https://github.com/ultralytics/ultraly
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=== "Count in Region"
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```python
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from ultralytics import YOLO
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from ultralytics.solutions import object_counter
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import cv2
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from ultralytics import YOLO, solutions
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model = YOLO("yolov8n.pt")
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cap = cv2.VideoCapture("path/to/video/file.mp4")
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assert cap.isOpened(), "Error reading video file"
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w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))
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# Define region points
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region_points = [(20, 400), (1080, 404), (1080, 360), (20, 360)]
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# Video writer
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video_writer = cv2.VideoWriter("object_counting_output.avi",
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cv2.VideoWriter_fourcc(*'mp4v'),
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fps,
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(w, h))
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video_writer = cv2.VideoWriter("object_counting_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
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# Init Object Counter
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counter = object_counter.ObjectCounter()
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counter.set_args(view_img=True,
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reg_pts=region_points,
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classes_names=model.names,
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draw_tracks=True,
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line_thickness=2)
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counter = solutions.ObjectCounter(
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view_img=True,
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reg_pts=region_points,
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classes_names=model.names,
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draw_tracks=True,
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line_thickness=2,
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)
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while cap.isOpened():
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success, im0 = cap.read()
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if not success:
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print("Video frame is empty or video processing has been successfully completed.")
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break
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tracks = model.track(im0, persist=True, show=False)
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im0 = counter.start_counting(im0, tracks)
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video_writer.write(im0)
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cap.release()
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video_writer.release()
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cv2.destroyAllWindows()
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@ -95,9 +92,8 @@ Object counting with [Ultralytics YOLOv8](https://github.com/ultralytics/ultraly
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=== "Count in Polygon"
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```python
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from ultralytics import YOLO
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from ultralytics.solutions import object_counter
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import cv2
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from ultralytics import YOLO, solutions
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model = YOLO("yolov8n.pt")
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cap = cv2.VideoCapture("path/to/video/file.mp4")
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@ -108,18 +104,16 @@ Object counting with [Ultralytics YOLOv8](https://github.com/ultralytics/ultraly
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region_points = [(20, 400), (1080, 404), (1080, 360), (20, 360), (20, 400)]
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# Video writer
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video_writer = cv2.VideoWriter("object_counting_output.avi",
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cv2.VideoWriter_fourcc(*'mp4v'),
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fps,
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(w, h))
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video_writer = cv2.VideoWriter("object_counting_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
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# Init Object Counter
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counter = object_counter.ObjectCounter()
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counter.set_args(view_img=True,
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reg_pts=region_points,
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classes_names=model.names,
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draw_tracks=True,
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line_thickness=2)
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counter = solutions.ObjectCounter(
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view_img=True,
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reg_pts=region_points,
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classes_names=model.names,
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draw_tracks=True,
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line_thickness=2,
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)
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while cap.isOpened():
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success, im0 = cap.read()
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@ -139,42 +133,39 @@ Object counting with [Ultralytics YOLOv8](https://github.com/ultralytics/ultraly
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=== "Count in Line"
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```python
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from ultralytics import YOLO
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from ultralytics.solutions import object_counter
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import cv2
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from ultralytics import YOLO, solutions
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model = YOLO("yolov8n.pt")
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cap = cv2.VideoCapture("path/to/video/file.mp4")
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assert cap.isOpened(), "Error reading video file"
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w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))
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# Define line points
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line_points = [(20, 400), (1080, 400)]
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# Video writer
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video_writer = cv2.VideoWriter("object_counting_output.avi",
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cv2.VideoWriter_fourcc(*'mp4v'),
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fps,
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(w, h))
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video_writer = cv2.VideoWriter("object_counting_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
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# Init Object Counter
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counter = object_counter.ObjectCounter()
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counter.set_args(view_img=True,
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reg_pts=line_points,
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classes_names=model.names,
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draw_tracks=True,
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line_thickness=2)
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counter = solutions.ObjectCounter(
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view_img=True,
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reg_pts=line_points,
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classes_names=model.names,
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draw_tracks=True,
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line_thickness=2,
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)
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while cap.isOpened():
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success, im0 = cap.read()
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if not success:
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print("Video frame is empty or video processing has been successfully completed.")
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break
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tracks = model.track(im0, persist=True, show=False)
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im0 = counter.start_counting(im0, tracks)
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video_writer.write(im0)
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cap.release()
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video_writer.release()
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cv2.destroyAllWindows()
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@ -183,43 +174,39 @@ Object counting with [Ultralytics YOLOv8](https://github.com/ultralytics/ultraly
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=== "Specific Classes"
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```python
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from ultralytics import YOLO
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from ultralytics.solutions import object_counter
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import cv2
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from ultralytics import YOLO, solutions
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model = YOLO("yolov8n.pt")
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cap = cv2.VideoCapture("path/to/video/file.mp4")
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assert cap.isOpened(), "Error reading video file"
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w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))
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line_points = [(20, 400), (1080, 400)] # line or region points
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classes_to_count = [0, 2] # person and car classes for count
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# Video writer
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video_writer = cv2.VideoWriter("object_counting_output.avi",
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cv2.VideoWriter_fourcc(*'mp4v'),
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fps,
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(w, h))
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video_writer = cv2.VideoWriter("object_counting_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
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# Init Object Counter
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counter = object_counter.ObjectCounter()
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counter.set_args(view_img=True,
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reg_pts=line_points,
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classes_names=model.names,
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draw_tracks=True,
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line_thickness=2)
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counter = solutions.ObjectCounter(
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view_img=True,
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reg_pts=line_points,
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classes_names=model.names,
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draw_tracks=True,
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line_thickness=2,
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)
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while cap.isOpened():
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success, im0 = cap.read()
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if not success:
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print("Video frame is empty or video processing has been successfully completed.")
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break
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tracks = model.track(im0, persist=True, show=False,
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classes=classes_to_count)
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tracks = model.track(im0, persist=True, show=False, classes=classes_to_count)
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im0 = counter.start_counting(im0, tracks)
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video_writer.write(im0)
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cap.release()
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video_writer.release()
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cv2.destroyAllWindows()
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@ -229,24 +216,27 @@ Object counting with [Ultralytics YOLOv8](https://github.com/ultralytics/ultraly
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You can move the region anywhere in the frame by clicking on its edges
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### Optional Arguments `set_args`
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### Argument `ObjectCounter`
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| Name | Type | Default | Description |
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|--------------------|-------------|----------------------------|--------------------------------------------------|
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| `view_img` | `bool` | `False` | Display frames with counts |
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| `view_in_counts` | `bool` | `True` | Display in-counts only on video frame |
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| `view_out_counts` | `bool` | `True` | Display out-counts only on video frame |
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| `line_thickness` | `int` | `2` | Increase bounding boxes and count text thickness |
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| `reg_pts` | `list` | `[(20, 400), (1260, 400)]` | Points defining the Region Area |
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| `classes_names` | `dict` | `model.model.names` | Dictionary of Class Names |
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| `count_reg_color` | `RGB Color` | `(255, 0, 255)` | Color of the Object counting Region or Line |
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| `track_thickness` | `int` | `2` | Thickness of Tracking Lines |
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| `draw_tracks` | `bool` | `False` | Enable drawing Track lines |
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| `track_color` | `RGB Color` | `(0, 255, 0)` | Color for each track line |
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| `line_dist_thresh` | `int` | `15` | Euclidean Distance threshold for line counter |
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| `count_txt_color` | `RGB Color` | `(255, 255, 255)` | Foreground color for Object counts text |
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| `region_thickness` | `int` | `5` | Thickness for object counter region or line |
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| `count_bg_color` | `RGB Color` | `(255, 255, 255)` | Count highlighter color |
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Here's a table with the `ObjectCounter` arguments:
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| Name | Type | Default | Description |
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|----------------------|---------|----------------------------|------------------------------------------------------------------------|
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| `classes_names` | `dict` | `None` | Dictionary of class names. |
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| `reg_pts` | `list` | `[(20, 400), (1260, 400)]` | List of points defining the counting region. |
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| `count_reg_color` | `tuple` | `(255, 0, 255)` | RGB color of the counting region. |
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| `count_txt_color` | `tuple` | `(0, 0, 0)` | RGB color of the count text. |
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| `count_bg_color` | `tuple` | `(255, 255, 255)` | RGB color of the count text background. |
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| `line_thickness` | `int` | `2` | Line thickness for bounding boxes. |
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| `track_thickness` | `int` | `2` | Thickness of the track lines. |
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| `view_img` | `bool` | `False` | Flag to control whether to display the video stream. |
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| `view_in_counts` | `bool` | `True` | Flag to control whether to display the in counts on the video stream. |
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| `view_out_counts` | `bool` | `True` | Flag to control whether to display the out counts on the video stream. |
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| `draw_tracks` | `bool` | `False` | Flag to control whether to draw the object tracks. |
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| `track_color` | `tuple` | `None` | RGB color of the tracks. |
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| `region_thickness` | `int` | `5` | Thickness of the object counting region. |
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| `line_dist_thresh` | `int` | `15` | Euclidean distance threshold for line counter. |
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| `cls_txtdisplay_gap` | `int` | `50` | Display gap between each class count. |
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### Arguments `model.track`
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