Update analytics solution (#16823)
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
This commit is contained in:
Muhammad Rizwan Munawar
GitHub
parent
06adc476a1
commit
1b52e5e693
3 changed files with 296 additions and 484 deletions
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@ -40,103 +40,32 @@ This guide provides a comprehensive overview of three fundamental types of [data
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```python
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import cv2
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from ultralytics import YOLO, solutions
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model = YOLO("yolo11n.pt")
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from ultralytics import solutions
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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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out = cv2.VideoWriter("line_plot.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
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analytics = solutions.Analytics(
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type="line",
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writer=out,
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im0_shape=(w, h),
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view_img=True,
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out = cv2.VideoWriter(
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"ultralytics_analytics.avi",
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cv2.VideoWriter_fourcc(*"MJPG"),
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fps,
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(1920, 1080), # This is fixed
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)
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total_counts = 0
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frame_count = 0
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while cap.isOpened():
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success, frame = cap.read()
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if success:
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frame_count += 1
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results = model.track(frame, persist=True, verbose=True)
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if results[0].boxes.id is not None:
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boxes = results[0].boxes.xyxy.cpu()
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for box in boxes:
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total_counts += 1
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analytics.update_line(frame_count, total_counts)
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total_counts = 0
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if cv2.waitKey(1) & 0xFF == ord("q"):
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break
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else:
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break
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cap.release()
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out.release()
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cv2.destroyAllWindows()
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```
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=== "Multiple Lines"
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```python
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import cv2
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from ultralytics import YOLO, solutions
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model = YOLO("yolo11n.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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out = cv2.VideoWriter("multiple_line_plot.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
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analytics = solutions.Analytics(
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type="line",
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writer=out,
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im0_shape=(w, h),
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view_img=True,
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max_points=200,
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analytics_type="line",
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show=True,
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)
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frame_count = 0
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data = {}
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labels = []
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while cap.isOpened():
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success, frame = cap.read()
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success, im0 = cap.read()
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if success:
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frame_count += 1
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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.xyxy.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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for box, track_id, cls in zip(boxes, track_ids, clss):
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# Store each class label
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if model.names[int(cls)] not in labels:
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labels.append(model.names[int(cls)])
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# Store each class count
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if model.names[int(cls)] in data:
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data[model.names[int(cls)]] += 1
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else:
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data[model.names[int(cls)]] = 0
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# update lines every frame
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analytics.update_multiple_lines(data, labels, frame_count)
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data = {} # clear the data list for next frame
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im0 = analytics.process_data(im0, frame_count) # update analytics graph every frame
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out.write(im0) # write the video file
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else:
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break
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@ -150,43 +79,32 @@ This guide provides a comprehensive overview of three fundamental types of [data
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```python
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import cv2
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from ultralytics import YOLO, solutions
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model = YOLO("yolo11n.pt")
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from ultralytics import solutions
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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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out = cv2.VideoWriter("pie_chart.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
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analytics = solutions.Analytics(
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type="pie",
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writer=out,
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im0_shape=(w, h),
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view_img=True,
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out = cv2.VideoWriter(
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"ultralytics_analytics.avi",
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cv2.VideoWriter_fourcc(*"MJPG"),
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fps,
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(1920, 1080), # This is fixed
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)
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clswise_count = {}
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analytics = solutions.Analytics(
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analytics_type="pie",
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show=True,
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)
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frame_count = 0
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while cap.isOpened():
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success, frame = cap.read()
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success, im0 = cap.read()
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if success:
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results = model.track(frame, persist=True, verbose=True)
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if results[0].boxes.id is not None:
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boxes = results[0].boxes.xyxy.cpu()
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clss = results[0].boxes.cls.cpu().tolist()
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for box, cls in zip(boxes, clss):
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if model.names[int(cls)] in clswise_count:
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clswise_count[model.names[int(cls)]] += 1
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else:
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clswise_count[model.names[int(cls)]] = 1
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analytics.update_pie(clswise_count)
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clswise_count = {}
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if cv2.waitKey(1) & 0xFF == ord("q"):
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break
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frame_count += 1
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im0 = analytics.process_data(im0, frame_count) # update analytics graph every frame
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out.write(im0) # write the video file
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else:
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break
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@ -200,43 +118,32 @@ This guide provides a comprehensive overview of three fundamental types of [data
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```python
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import cv2
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from ultralytics import YOLO, solutions
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model = YOLO("yolo11n.pt")
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from ultralytics import solutions
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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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out = cv2.VideoWriter("bar_plot.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
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analytics = solutions.Analytics(
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type="bar",
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writer=out,
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im0_shape=(w, h),
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view_img=True,
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out = cv2.VideoWriter(
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"ultralytics_analytics.avi",
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cv2.VideoWriter_fourcc(*"MJPG"),
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fps,
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(1920, 1080), # This is fixed
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)
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clswise_count = {}
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analytics = solutions.Analytics(
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analytics_type="bar",
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show=True,
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)
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frame_count = 0
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while cap.isOpened():
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success, frame = cap.read()
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success, im0 = cap.read()
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if success:
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results = model.track(frame, persist=True, verbose=True)
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if results[0].boxes.id is not None:
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boxes = results[0].boxes.xyxy.cpu()
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clss = results[0].boxes.cls.cpu().tolist()
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for box, cls in zip(boxes, clss):
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if model.names[int(cls)] in clswise_count:
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clswise_count[model.names[int(cls)]] += 1
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else:
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clswise_count[model.names[int(cls)]] = 1
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analytics.update_bar(clswise_count)
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clswise_count = {}
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if cv2.waitKey(1) & 0xFF == ord("q"):
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break
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frame_count += 1
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im0 = analytics.process_data(im0, frame_count) # update analytics graph every frame
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out.write(im0) # write the video file
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else:
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break
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@ -250,46 +157,32 @@ This guide provides a comprehensive overview of three fundamental types of [data
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```python
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import cv2
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from ultralytics import YOLO, solutions
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from ultralytics import solutions
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model = YOLO("yolo11n.pt")
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cap = cv2.VideoCapture("path/to/video/file.mp4")
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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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out = cv2.VideoWriter("area_plot.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
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analytics = solutions.Analytics(
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type="area",
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writer=out,
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im0_shape=(w, h),
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view_img=True,
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out = cv2.VideoWriter(
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"ultralytics_analytics.avi",
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cv2.VideoWriter_fourcc(*"MJPG"),
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fps,
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(1920, 1080), # This is fixed
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)
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clswise_count = {}
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frame_count = 0
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analytics = solutions.Analytics(
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analytics_type="area",
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show=True,
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)
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frame_count = 0
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while cap.isOpened():
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success, frame = cap.read()
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success, im0 = cap.read()
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if success:
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frame_count += 1
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results = model.track(frame, persist=True, verbose=True)
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if results[0].boxes.id is not None:
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boxes = results[0].boxes.xyxy.cpu()
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clss = results[0].boxes.cls.cpu().tolist()
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for box, cls in zip(boxes, clss):
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if model.names[int(cls)] in clswise_count:
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clswise_count[model.names[int(cls)]] += 1
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else:
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clswise_count[model.names[int(cls)]] = 1
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analytics.update_area(frame_count, clswise_count)
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clswise_count = {}
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if cv2.waitKey(1) & 0xFF == ord("q"):
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break
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im0 = analytics.process_data(im0, frame_count) # update analytics graph every frame
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out.write(im0) # write the video file
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else:
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break
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@ -302,23 +195,12 @@ This guide provides a comprehensive overview of three fundamental types of [data
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Here's a table with the `Analytics` arguments:
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| Name | Type | Default | Description |
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| -------------- | ----------------- | ------------- | -------------------------------------------------------------------------------- |
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| `type` | `str` | `None` | Type of data or object. |
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| `im0_shape` | `tuple` | `None` | Shape of the initial image. |
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| `writer` | `cv2.VideoWriter` | `None` | Object for writing video files. |
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| `title` | `str` | `ultralytics` | Title for the visualization. |
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| `x_label` | `str` | `x` | Label for the x-axis. |
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| `y_label` | `str` | `y` | Label for the y-axis. |
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| `bg_color` | `str` | `white` | Background color. |
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| `fg_color` | `str` | `black` | Foreground color. |
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| `line_color` | `str` | `yellow` | Color of the lines. |
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| `line_width` | `int` | `2` | Width of the lines. |
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| `fontsize` | `int` | `13` | Font size for text. |
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| `view_img` | `bool` | `False` | Flag to display the image or video. |
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| `save_img` | `bool` | `True` | Flag to save the image or video. |
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| `max_points` | `int` | `50` | For multiple lines, total points drawn on frame, before deleting initial points. |
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| `points_width` | `int` | `15` | Width of line points highlighter. |
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| Name | Type | Default | Description |
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| ---------------- | ------ | ------- | ---------------------------------------------------- |
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| `analytics_type` | `str` | `line` | Type of graph i.e "line", "bar", "area", "pie" |
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| `model` | `str` | `None` | Path to Ultralytics YOLO Model File |
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| `line_width` | `int` | `2` | Line thickness for bounding boxes. |
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| `show` | `bool` | `False` | Flag to control whether to display the video stream. |
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### Arguments `model.track`
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@ -344,21 +226,33 @@ Example:
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```python
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import cv2
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from ultralytics import YOLO, solutions
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from ultralytics import solutions
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model = YOLO("yolo11n.pt")
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cap = cv2.VideoCapture("Path/to/video/file.mp4")
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out = cv2.VideoWriter("line_plot.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
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assert cap.isOpened(), "Error reading video file"
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analytics = solutions.Analytics(type="line", writer=out, im0_shape=(w, h), view_img=True)
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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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out = cv2.VideoWriter(
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"ultralytics_analytics.avi",
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cv2.VideoWriter_fourcc(*"MJPG"),
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fps,
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(1920, 1080), # This is fixed
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)
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analytics = solutions.Analytics(
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analytics_type="line",
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show=True,
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)
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frame_count = 0
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while cap.isOpened():
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success, frame = cap.read()
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success, im0 = cap.read()
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if success:
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results = model.track(frame, persist=True)
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total_counts = sum([1 for box in results[0].boxes.xyxy])
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analytics.update_line(frame_count, total_counts)
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if cv2.waitKey(1) & 0xFF == ord("q"):
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frame_count += 1
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im0 = analytics.process_data(im0, frame_count) # update analytics graph every frame
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out.write(im0) # write the video file
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else:
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break
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cap.release()
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@ -382,24 +276,33 @@ Use the following example to generate a bar plot:
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```python
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import cv2
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from ultralytics import YOLO, solutions
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from ultralytics import solutions
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model = YOLO("yolo11n.pt")
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cap = cv2.VideoCapture("Path/to/video/file.mp4")
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out = cv2.VideoWriter("bar_plot.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
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assert cap.isOpened(), "Error reading video file"
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analytics = solutions.Analytics(type="bar", writer=out, im0_shape=(w, h), view_img=True)
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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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out = cv2.VideoWriter(
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"ultralytics_analytics.avi",
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cv2.VideoWriter_fourcc(*"MJPG"),
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fps,
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(1920, 1080), # This is fixed
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)
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analytics = solutions.Analytics(
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analytics_type="bar",
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show=True,
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)
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frame_count = 0
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while cap.isOpened():
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success, frame = cap.read()
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success, im0 = cap.read()
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if success:
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results = model.track(frame, persist=True)
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clswise_count = {
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model.names[int(cls)]: boxes.size(0)
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for cls, boxes in zip(results[0].boxes.cls.tolist(), results[0].boxes.xyxy)
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}
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analytics.update_bar(clswise_count)
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if cv2.waitKey(1) & 0xFF == ord("q"):
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frame_count += 1
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im0 = analytics.process_data(im0, frame_count) # update analytics graph every frame
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out.write(im0) # write the video file
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else:
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break
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cap.release()
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@ -423,24 +326,33 @@ Here's a quick example:
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```python
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import cv2
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from ultralytics import YOLO, solutions
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from ultralytics import solutions
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model = YOLO("yolo11n.pt")
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cap = cv2.VideoCapture("Path/to/video/file.mp4")
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out = cv2.VideoWriter("pie_chart.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
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assert cap.isOpened(), "Error reading video file"
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analytics = solutions.Analytics(type="pie", writer=out, im0_shape=(w, h), view_img=True)
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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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out = cv2.VideoWriter(
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"ultralytics_analytics.avi",
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cv2.VideoWriter_fourcc(*"MJPG"),
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fps,
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(1920, 1080), # This is fixed
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)
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analytics = solutions.Analytics(
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analytics_type="pie",
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show=True,
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)
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frame_count = 0
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while cap.isOpened():
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success, frame = cap.read()
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success, im0 = cap.read()
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if success:
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results = model.track(frame, persist=True)
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clswise_count = {
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model.names[int(cls)]: boxes.size(0)
|
||||
for cls, boxes in zip(results[0].boxes.cls.tolist(), results[0].boxes.xyxy)
|
||||
}
|
||||
analytics.update_pie(clswise_count)
|
||||
if cv2.waitKey(1) & 0xFF == ord("q"):
|
||||
frame_count += 1
|
||||
im0 = analytics.process_data(im0, frame_count) # update analytics graph every frame
|
||||
out.write(im0) # write the video file
|
||||
else:
|
||||
break
|
||||
|
||||
cap.release()
|
||||
|
|
@ -459,21 +371,33 @@ Example for tracking and updating a line graph:
|
|||
```python
|
||||
import cv2
|
||||
|
||||
from ultralytics import YOLO, solutions
|
||||
from ultralytics import solutions
|
||||
|
||||
model = YOLO("yolo11n.pt")
|
||||
cap = cv2.VideoCapture("Path/to/video/file.mp4")
|
||||
out = cv2.VideoWriter("line_plot.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
|
||||
assert cap.isOpened(), "Error reading video file"
|
||||
|
||||
analytics = solutions.Analytics(type="line", writer=out, im0_shape=(w, h), view_img=True)
|
||||
w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))
|
||||
|
||||
out = cv2.VideoWriter(
|
||||
"ultralytics_analytics.avi",
|
||||
cv2.VideoWriter_fourcc(*"MJPG"),
|
||||
fps,
|
||||
(1920, 1080), # This is fixed
|
||||
)
|
||||
|
||||
analytics = solutions.Analytics(
|
||||
analytics_type="line",
|
||||
show=True,
|
||||
)
|
||||
|
||||
frame_count = 0
|
||||
while cap.isOpened():
|
||||
success, frame = cap.read()
|
||||
success, im0 = cap.read()
|
||||
if success:
|
||||
results = model.track(frame, persist=True)
|
||||
total_counts = sum([1 for box in results[0].boxes.xyxy])
|
||||
analytics.update_line(frame_count, total_counts)
|
||||
if cv2.waitKey(1) & 0xFF == ord("q"):
|
||||
frame_count += 1
|
||||
im0 = analytics.process_data(im0, frame_count) # update analytics graph every frame
|
||||
out.write(im0) # write the video file
|
||||
else:
|
||||
break
|
||||
|
||||
cap.release()
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue