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import argparse
from collections import defaultdict
from pathlib import Path
import cv2
import numpy as np
from shapely.geometry import Polygon
from shapely.geometry.point import Point
from ultralytics import YOLO
from ultralytics.utils.files import increment_path
from ultralytics.utils.plotting import Annotator, colors
track_history = defaultdict(list)
current_region = None
counting_regions = [
{
'name': 'YOLOv8 Polygon Region',
'polygon': Polygon([(50, 80), (250, 20), (450, 80), (400, 350), (100, 350)]), # Polygon points
'counts': 0,
'dragging': False,
'region_color': (255, 42, 4), # BGR Value
'text_color': (255, 255, 255) # Region Text Color
},
{
'name': 'YOLOv8 Rectangle Region',
'polygon': Polygon([(200, 250), (440, 250), (440, 550), (200, 550)]), # Polygon points
'counts': 0,
'dragging': False,
'region_color': (37, 255, 225), # BGR Value
'text_color': (0, 0, 0), # Region Text Color
}, ]
def mouse_callback(event, x, y, flags, param):
"""Mouse call back event."""
global current_region
# Mouse left button down event
if event == cv2.EVENT_LBUTTONDOWN:
for region in counting_regions:
if region['polygon'].contains(Point((x, y))):
current_region = region
current_region['dragging'] = True
current_region['offset_x'] = x
current_region['offset_y'] = y
# Mouse move event
elif event == cv2.EVENT_MOUSEMOVE:
if current_region is not None and current_region['dragging']:
dx = x - current_region['offset_x']
dy = y - current_region['offset_y']
current_region['polygon'] = Polygon([
(p[0] + dx, p[1] + dy) for p in current_region['polygon'].exterior.coords])
current_region['offset_x'] = x
current_region['offset_y'] = y
# Mouse left button up event
elif event == cv2.EVENT_LBUTTONUP:
if current_region is not None and current_region['dragging']:
current_region['dragging'] = False
def run(
weights='yolov8n.pt',
source=None,
device='cpu',
view_img=False,
save_img=False,
exist_ok=False,
classes=None,
line_thickness=2,
track_thickness=2,
region_thickness=2,
):
"""
Run Region counting on a video using YOLOv8 and ByteTrack.
Supports movable region for real time counting inside specific area.
Supports multiple regions counting.
Regions can be Polygons or rectangle in shape
Args:
weights (str): Model weights path.
source (str): Video file path.
device (str): processing device cpu, 0, 1
view_img (bool): Show results.
save_img (bool): Save results.
exist_ok (bool): Overwrite existing files.
classes (list): classes to detect and track
line_thickness (int): Bounding box thickness.
track_thickness (int): Tracking line thickness
region_thickness (int): Region thickness.
"""
vid_frame_count = 0
# Check source path
if not Path(source).exists():
raise FileNotFoundError(f"Source path '{source}' does not exist.")
# Setup Model
model = YOLO(f'{weights}')
model.to('cuda') if device == '0' else model.to('cpu')
# Extract classes names
names = model.model.names
# Video setup
videocapture = cv2.VideoCapture(source)
frame_width, frame_height = int(videocapture.get(3)), int(videocapture.get(4))
fps, fourcc = int(videocapture.get(5)), cv2.VideoWriter_fourcc(*'mp4v')
# Output setup
save_dir = increment_path(Path('ultralytics_rc_output') / 'exp', exist_ok)
save_dir.mkdir(parents=True, exist_ok=True)
video_writer = cv2.VideoWriter(str(save_dir / f'{Path(source).stem}.mp4'), fourcc, fps, (frame_width, frame_height))
# Iterate over video frames
while videocapture.isOpened():
success, frame = videocapture.read()
if not success:
break
vid_frame_count += 1
# Extract the results
results = model.track(frame, persist=True, classes=classes)
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()
annotator = Annotator(frame, line_width=line_thickness, example=str(names))
for box, track_id, cls in zip(boxes, track_ids, clss):
annotator.box_label(box, str(names[cls]), color=colors(cls, True))
bbox_center = (box[0] + box[2]) / 2, (box[1] + box[3]) / 2 # Bbox center
track = track_history[track_id] # Tracking Lines plot
track.append((float(bbox_center[0]), float(bbox_center[1])))
if len(track) > 30:
track.pop(0)
points = np.hstack(track).astype(np.int32).reshape((-1, 1, 2))
cv2.polylines(frame, [points], isClosed=False, color=colors(cls, True), thickness=track_thickness)
# Check if detection inside region
for region in counting_regions:
if region['polygon'].contains(Point((bbox_center[0], bbox_center[1]))):
region['counts'] += 1
# Draw regions (Polygons/Rectangles)
for region in counting_regions:
region_label = str(region['counts'])
region_color = region['region_color']
region_text_color = region['text_color']
polygon_coords = np.array(region['polygon'].exterior.coords, dtype=np.int32)
centroid_x, centroid_y = int(region['polygon'].centroid.x), int(region['polygon'].centroid.y)
text_size, _ = cv2.getTextSize(region_label,
cv2.FONT_HERSHEY_SIMPLEX,
fontScale=0.7,
thickness=line_thickness)
text_x = centroid_x - text_size[0] // 2
text_y = centroid_y + text_size[1] // 2
cv2.rectangle(frame, (text_x - 5, text_y - text_size[1] - 5), (text_x + text_size[0] + 5, text_y + 5),
region_color, -1)
cv2.putText(frame, region_label, (text_x, text_y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, region_text_color,
line_thickness)
cv2.polylines(frame, [polygon_coords], isClosed=True, color=region_color, thickness=region_thickness)
if view_img:
if vid_frame_count == 1:
cv2.namedWindow('Ultralytics YOLOv8 Region Counter Movable')
cv2.setMouseCallback('Ultralytics YOLOv8 Region Counter Movable', mouse_callback)
cv2.imshow('Ultralytics YOLOv8 Region Counter Movable', frame)
if save_img:
video_writer.write(frame)
for region in counting_regions: # Reinitialize count for each region
region['counts'] = 0
if cv2.waitKey(1) & 0xFF == ord('q'):
break
del vid_frame_count
video_writer.release()
videocapture.release()
cv2.destroyAllWindows()
def parse_opt():
"""Parse command line arguments."""
parser = argparse.ArgumentParser()
parser.add_argument('--weights', type=str, default='yolov8n.pt', help='initial weights path')
parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu')
parser.add_argument('--source', type=str, required=True, help='video file path')
parser.add_argument('--view-img', action='store_true', help='show results')
parser.add_argument('--save-img', action='store_true', help='save results')
parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment')
parser.add_argument('--classes', nargs='+', type=int, help='filter by class: --classes 0, or --classes 0 2 3')
parser.add_argument('--line-thickness', type=int, default=2, help='bounding box thickness')
parser.add_argument('--track-thickness', type=int, default=2, help='Tracking line thickness')
parser.add_argument('--region-thickness', type=int, default=4, help='Region thickness')
return parser.parse_args()
def main(opt):
"""Main function."""
run(**vars(opt))
if __name__ == '__main__':
opt = parse_opt()
main(opt)