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