HongChuang/ultralytics-ascend
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 3

Add instance segmentation and vision-eye mapping in Docs + Fix minor code bug in other real-world-projects (#6972)

Browse source 
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
This commit is contained in:
Muhammad Rizwan Munawar 2023-12-18 20:41:33 +05:00 • committed by GitHub
parent e9def85f1f
commit 34b10b2db3
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
10 changed files with 385 additions and 56 deletions
Download patch file Download diff file Expand all files Collapse all files

127
docs/en/guides/vision-eye.md Normal file
View file

@ -0,0 +1,127 @@
---
comments: true
description: VisionEye View Object Mapping using Ultralytics YOLOv8
keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, VisionEye, Computer Vision, Notebook, IPython Kernel, CLI, Python SDK
---
# VisionEye View Object Mapping using Ultralytics YOLOv8 🚀
## What is VisionEye Object Mapping?
[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.
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/in6xF7KgF7Q"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> VisionEye Mapping using Ultralytics YOLOv8
</p>
## Samples
| VisionEye View | VisionEye View With Object Tracking |
|:------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| ![VisionEye View Object Mapping using Ultralytics YOLOv8](https://github.com/RizwanMunawar/ultralytics/assets/62513924/7d593acc-2e37-41b0-ad0e-92b4ffae6647) | ![VisionEye View Object Mapping with Object Tracking using Ultralytics YOLOv8](https://github.com/RizwanMunawar/ultralytics/assets/62513924/fcd85952-390f-451e-8fb0-b82e943af89c) |
| VisionEye View Object Mapping using Ultralytics YOLOv8 | VisionEye View Object Mapping with Object Tracking using Ultralytics YOLOv8 |
!!! Example "VisionEye Object Mapping using YOLOv8"
=== "VisionEye Object Mapping"
```python
import cv2
from ultralytics import YOLO
from ultralytics.utils.plotting import colors, Annotator
model = YOLO("yolov8n.pt")
names = model.model.names
cap = cv2.VideoCapture("path/to/video/file.mp4")
out = cv2.VideoWriter('visioneye-pinpoint.avi', cv2.VideoWriter_fourcc(*'MJPG'),
30, (int(cap.get(3)), int(cap.get(4))))
center_point = (-10, int(cap.get(4)))
while True:
ret, im0 = cap.read()
if not ret:
print("Video frame is empty or video processing has been successfully completed.")
break
results = model.predict(im0)
boxes = results[0].boxes.xyxy.cpu()
clss = results[0].boxes.cls.cpu().tolist()
annotator = Annotator(im0, line_width=2)
for box, cls in zip(boxes, clss):
annotator.box_label(box, label=names[int(cls)], color=colors(int(cls)))
annotator.visioneye(box, center_point)
out.write(im0)
cv2.imshow("visioneye-pinpoint", im0)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
out.release()
cap.release()
cv2.destroyAllWindows()
```
=== "VisionEye Object Mapping with Object Tracking"
```python
import cv2
from ultralytics import YOLO
from ultralytics.utils.plotting import colors, Annotator
model = YOLO("yolov8n.pt")
cap = cv2.VideoCapture("path/to/video/file.mp4")
out = cv2.VideoWriter('visioneye-pinpoint.avi', cv2.VideoWriter_fourcc(*'MJPG'),
30, (int(cap.get(3)), int(cap.get(4))))
center_point = (-10, int(cap.get(4)))
while True:
ret, im0 = cap.read()
if not ret:
print("Video frame is empty or video processing has been successfully completed.")
break
results = model.track(im0, persist=True)
boxes = results[0].boxes.xyxy.cpu()
track_ids = results[0].boxes.id.int().cpu().tolist()
annotator = Annotator(im0, line_width=2)
for box, track_id in zip(boxes, track_ids):
annotator.box_label(box, label=str(track_id), color=colors(int(track_id)))
annotator.visioneye(box, center_point)
out.write(im0)
cv2.imshow("visioneye-pinpoint", im0)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
out.release()
cap.release()
cv2.destroyAllWindows()
```
### `visioneye` Arguments
| Name | Type | Default | Description |
|---------------|---------|------------------|--------------------------------------------------|
| `color` | `tuple` | `(235, 219, 11)` | Line and object centroid color |
| `pin_color` | `tuple` | `(255, 0, 255)` | VisionEye pinpoint color |
| `thickness` | `int` | `2` | pinpoint to object line thickness |
| `pins_radius` | `int` | `10` | Pinpoint and object centroid point circle radius |
## Note
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.