Reformat Markdown code blocks (#12795)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-05-18 18:58:06 +02:00 committed by GitHub
parent 2af71d15a6
commit fceea033ad
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128 changed files with 1067 additions and 1018 deletions

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@ -24,14 +24,14 @@ keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, Vi
```python
import cv2
from ultralytics import YOLO
from ultralytics.utils.plotting import colors, Annotator
from ultralytics.utils.plotting import Annotator, colors
model = YOLO("yolov8n.pt")
names = model.model.names
cap = cv2.VideoCapture("path/to/video/file.mp4")
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('visioneye-pinpoint.avi', cv2.VideoWriter_fourcc(*'MJPG'), fps, (w, h))
out = cv2.VideoWriter("visioneye-pinpoint.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
center_point = (-10, h)
@ -54,7 +54,7 @@ keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, Vi
out.write(im0)
cv2.imshow("visioneye-pinpoint", im0)
if cv2.waitKey(1) & 0xFF == ord('q'):
if cv2.waitKey(1) & 0xFF == ord("q"):
break
out.release()
@ -67,13 +67,13 @@ keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, Vi
```python
import cv2
from ultralytics import YOLO
from ultralytics.utils.plotting import colors, Annotator
from ultralytics.utils.plotting import Annotator, colors
model = YOLO("yolov8n.pt")
cap = cv2.VideoCapture("path/to/video/file.mp4")
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('visioneye-pinpoint.avi', cv2.VideoWriter_fourcc(*'MJPG'), fps, (w, h))
out = cv2.VideoWriter("visioneye-pinpoint.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
center_point = (-10, h)
@ -98,7 +98,7 @@ keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, Vi
out.write(im0)
cv2.imshow("visioneye-pinpoint", im0)
if cv2.waitKey(1) & 0xFF == ord('q'):
if cv2.waitKey(1) & 0xFF == ord("q"):
break
out.release()
@ -109,55 +109,56 @@ keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, Vi
=== "VisionEye with Distance Calculation"
```python
import cv2
import math
import cv2
from ultralytics import YOLO
from ultralytics.utils.plotting import Annotator, colors
model = YOLO("yolov8s.pt")
cap = cv2.VideoCapture("Path/to/video/file.mp4")
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('visioneye-distance-calculation.avi', cv2.VideoWriter_fourcc(*'MJPG'), fps, (w, h))
out = cv2.VideoWriter("visioneye-distance-calculation.avi", cv2.VideoWriter_fourcc(*"MJPG"), fps, (w, h))
center_point = (0, h)
pixel_per_meter = 10
txt_color, txt_background, bbox_clr = ((0, 0, 0), (255, 255, 255), (255, 0, 255))
while True:
ret, im0 = cap.read()
if not ret:
print("Video frame is empty or video processing has been successfully completed.")
break
annotator = Annotator(im0, line_width=2)
results = model.track(im0, persist=True)
boxes = results[0].boxes.xyxy.cpu()
if results[0].boxes.id is not None:
track_ids = results[0].boxes.id.int().cpu().tolist()
for box, track_id in zip(boxes, track_ids):
annotator.box_label(box, label=str(track_id), color=bbox_clr)
annotator.visioneye(box, center_point)
x1, y1 = int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2) # Bounding box centroid
distance = (math.sqrt((x1 - center_point[0]) ** 2 + (y1 - center_point[1]) ** 2))/pixel_per_meter
text_size, _ = cv2.getTextSize(f"Distance: {distance:.2f} m", cv2.FONT_HERSHEY_SIMPLEX,1.2, 3)
cv2.rectangle(im0, (x1, y1 - text_size[1] - 10),(x1 + text_size[0] + 10, y1), txt_background, -1)
cv2.putText(im0, f"Distance: {distance:.2f} m",(x1, y1 - 5), cv2.FONT_HERSHEY_SIMPLEX, 1.2,txt_color, 3)
x1, y1 = int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2) # Bounding box centroid
distance = (math.sqrt((x1 - center_point[0]) ** 2 + (y1 - center_point[1]) ** 2)) / pixel_per_meter
text_size, _ = cv2.getTextSize(f"Distance: {distance:.2f} m", cv2.FONT_HERSHEY_SIMPLEX, 1.2, 3)
cv2.rectangle(im0, (x1, y1 - text_size[1] - 10), (x1 + text_size[0] + 10, y1), txt_background, -1)
cv2.putText(im0, f"Distance: {distance:.2f} m", (x1, y1 - 5), cv2.FONT_HERSHEY_SIMPLEX, 1.2, txt_color, 3)
out.write(im0)
cv2.imshow("visioneye-distance-calculation", im0)
if cv2.waitKey(1) & 0xFF == ord('q'):
if cv2.waitKey(1) & 0xFF == ord("q"):
break
out.release()
cap.release()
cv2.destroyAllWindows()