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177 lines
8.6 KiB
177 lines
8.6 KiB
--- |
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comments: true |
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description: VisionEye View Object Mapping using Ultralytics YOLOv8 |
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keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, VisionEye, Computer Vision, Notebook, IPython Kernel, CLI, Python SDK |
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--- |
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# VisionEye View Object Mapping using Ultralytics YOLOv8 🚀 |
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## What is VisionEye Object Mapping? |
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[Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics/) VisionEye offers the capability for computers to identify and pinpoint objects, simulating the observational precision of the human eye. This functionality enables computers to discern and focus on specific objects, much like the way the human eye observes details from a particular viewpoint. |
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## Samples |
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| VisionEye View | VisionEye View With Object Tracking | VisionEye View With Distance Calculation | |
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|:------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| |
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|  |  |  | |
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| VisionEye View Object Mapping using Ultralytics YOLOv8 | VisionEye View Object Mapping with Object Tracking using Ultralytics YOLOv8 | VisionEye View with Distance Calculation using Ultralytics YOLOv8 | |
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!!! Example "VisionEye Object Mapping using YOLOv8" |
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=== "VisionEye Object Mapping" |
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```python |
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import cv2 |
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from ultralytics import YOLO |
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from ultralytics.utils.plotting import colors, Annotator |
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model = YOLO("yolov8n.pt") |
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names = model.model.names |
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cap = cv2.VideoCapture("path/to/video/file.mp4") |
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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('visioneye-pinpoint.avi', cv2.VideoWriter_fourcc(*'MJPG'), fps, (w, h)) |
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center_point = (-10, h) |
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while True: |
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ret, im0 = cap.read() |
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if not ret: |
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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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results = model.predict(im0) |
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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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annotator = Annotator(im0, line_width=2) |
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for box, cls in zip(boxes, clss): |
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annotator.box_label(box, label=names[int(cls)], color=colors(int(cls))) |
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annotator.visioneye(box, center_point) |
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out.write(im0) |
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cv2.imshow("visioneye-pinpoint", im0) |
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if cv2.waitKey(1) & 0xFF == ord('q'): |
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break |
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out.release() |
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cap.release() |
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cv2.destroyAllWindows() |
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``` |
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=== "VisionEye Object Mapping with Object Tracking" |
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```python |
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import cv2 |
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from ultralytics import YOLO |
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from ultralytics.utils.plotting import colors, Annotator |
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model = YOLO("yolov8n.pt") |
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cap = cv2.VideoCapture("path/to/video/file.mp4") |
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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('visioneye-pinpoint.avi', cv2.VideoWriter_fourcc(*'MJPG'), fps, (w, h)) |
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center_point = (-10, h) |
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while True: |
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ret, im0 = cap.read() |
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if not ret: |
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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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annotator = Annotator(im0, line_width=2) |
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results = model.track(im0, persist=True) |
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boxes = results[0].boxes.xyxy.cpu() |
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if results[0].boxes.id is not None: |
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track_ids = results[0].boxes.id.int().cpu().tolist() |
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for box, track_id in zip(boxes, track_ids): |
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annotator.box_label(box, label=str(track_id), color=colors(int(track_id))) |
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annotator.visioneye(box, center_point) |
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out.write(im0) |
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cv2.imshow("visioneye-pinpoint", im0) |
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if cv2.waitKey(1) & 0xFF == ord('q'): |
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break |
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out.release() |
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cap.release() |
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cv2.destroyAllWindows() |
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``` |
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=== "VisionEye with Distance Calculation" |
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```python |
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import cv2 |
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import math |
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from ultralytics import YOLO |
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from ultralytics.utils.plotting import Annotator, colors |
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model = YOLO("yolov8s.pt") |
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cap = cv2.VideoCapture("Path/to/video/file.mp4") |
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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('visioneye-distance-calculation.avi', cv2.VideoWriter_fourcc(*'MJPG'), fps, (w, h)) |
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center_point = (0, h) |
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pixel_per_meter = 10 |
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txt_color, txt_background, bbox_clr = ((0, 0, 0), (255, 255, 255), (255, 0, 255)) |
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while True: |
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ret, im0 = cap.read() |
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if not ret: |
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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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annotator = Annotator(im0, line_width=2) |
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results = model.track(im0, persist=True) |
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boxes = results[0].boxes.xyxy.cpu() |
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if results[0].boxes.id is not None: |
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track_ids = results[0].boxes.id.int().cpu().tolist() |
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for box, track_id in zip(boxes, track_ids): |
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annotator.box_label(box, label=str(track_id), color=bbox_clr) |
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annotator.visioneye(box, center_point) |
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x1, y1 = int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2) # Bounding box centroid |
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distance = (math.sqrt((x1 - center_point[0]) ** 2 + (y1 - center_point[1]) ** 2))/pixel_per_meter |
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text_size, _ = cv2.getTextSize(f"Distance: {distance:.2f} m", cv2.FONT_HERSHEY_SIMPLEX,1.2, 3) |
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cv2.rectangle(im0, (x1, y1 - text_size[1] - 10),(x1 + text_size[0] + 10, y1), txt_background, -1) |
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cv2.putText(im0, f"Distance: {distance:.2f} m",(x1, y1 - 5), cv2.FONT_HERSHEY_SIMPLEX, 1.2,txt_color, 3) |
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out.write(im0) |
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cv2.imshow("visioneye-distance-calculation", im0) |
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if cv2.waitKey(1) & 0xFF == ord('q'): |
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break |
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out.release() |
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cap.release() |
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cv2.destroyAllWindows() |
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``` |
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### `visioneye` Arguments |
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| Name | Type | Default | Description | |
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|---------------|---------|------------------|--------------------------------------------------| |
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| `color` | `tuple` | `(235, 219, 11)` | Line and object centroid color | |
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| `pin_color` | `tuple` | `(255, 0, 255)` | VisionEye pinpoint color | |
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| `thickness` | `int` | `2` | pinpoint to object line thickness | |
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| `pins_radius` | `int` | `10` | Pinpoint and object centroid point circle radius | |
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## Note |
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For any inquiries, feel free to post your questions in the [Ultralytics Issue Section](https://github.com/ultralytics/ultralytics/issues/new/choose) or the discussion section mentioned below.
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