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Reformat Markdown code blocks (#12795)

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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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39
docs/en/guides/security-alarm-system.md
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@ -30,15 +30,16 @@ The Security Alarm System Project utilizing Ultralytics YOLOv8 integrates advanc
#### Import Libraries
```python
import torch
import numpy as np
import cv2
from time import time
from ultralytics import YOLO
from ultralytics.utils.plotting import Annotator, colors
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from time import time
import cv2
import numpy as np
import torch
from ultralytics import YOLO
from ultralytics.utils.plotting import Annotator, colors
```
#### Set up the parameters of the message
@ -58,7 +59,7 @@ to_email = "" # receiver email
#### Server creation and authentication
```python
server = smtplib.SMTP('smtp.gmail.com: 587')
server = smtplib.SMTP("smtp.gmail.com: 587")
server.starttls()
server.login(from_email, password)
```
@ -69,13 +70,13 @@ server.login(from_email, password)
def send_email(to_email, from_email, object_detected=1):
"""Sends an email notification indicating the number of objects detected; defaults to 1 object."""
message = MIMEMultipart()
message['From'] = from_email
message['To'] = to_email
message['Subject'] = "Security Alert"
message["From"] = from_email
message["To"] = to_email
message["Subject"] = "Security Alert"
# Add in the message body
message_body = f'ALERT - {object_detected} objects has been detected!!'
message_body = f"ALERT - {object_detected} objects has been detected!!"
message.attach(MIMEText(message_body, 'plain'))
message.attach(MIMEText(message_body, "plain"))
server.sendmail(from_email, to_email, message.as_string())
```
@ -97,7 +98,7 @@ class ObjectDetection:
self.end_time = 0
# device information
self.device = 'cuda' if torch.cuda.is_available() else 'cpu'
self.device = "cuda" if torch.cuda.is_available() else "cpu"
def predict(self, im0):
"""Run prediction using a YOLO model for the input image `im0`."""
@ -108,10 +109,16 @@ class ObjectDetection:
"""Displays the FPS on an image `im0` by calculating and overlaying as white text on a black rectangle."""
self.end_time = time()
fps = 1 / np.round(self.end_time - self.start_time, 2)
text = f'FPS: {int(fps)}'
text = f"FPS: {int(fps)}"
text_size = cv2.getTextSize(text, cv2.FONT_HERSHEY_SIMPLEX, 1.0, 2)[0]
gap = 10
cv2.rectangle(im0, (20 - gap, 70 - text_size[1] - gap), (20 + text_size[0] + gap, 70 + gap), (255, 255, 255), -1)
cv2.rectangle(
im0,
(20 - gap, 70 - text_size[1] - gap),
(20 + text_size[0] + gap, 70 + gap),
(255, 255, 255),
-1,
)
cv2.putText(im0, text, (20, 70), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 0), 2)
def plot_bboxes(self, results, im0):
@ -148,7 +155,7 @@ class ObjectDetection:
self.email_sent = False
self.display_fps(im0)
cv2.imshow('YOLOv8 Detection', im0)
cv2.imshow("YOLOv8 Detection", im0)
frame_count += 1
if cv2.waitKey(5) & 0xFF == 27:
break