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Techon Pixel डिलीवरी

Real-time video anomaly detection with automated evidence alerts

Final recorded accuracy of 95.1% before delivery on the trained detection scope.

A Django web application that analyses webcam and uploaded video frame by frame with trained YOLO models, captures anomalies with timestamps and sends automated email alerts, with remote web access.

An applied computer-vision product for monitoring video sources and flagging anomalous events for human review. Detection scope is limited to the classes the model was trained on; this is anomaly detection, not a certified law-enforcement system.

भूमिका: Machine-learning and web-application engineering

सिस्टम

वास्तव में क्या बनाया गया

  • Webcam and uploaded-video input paths
  • Frame-by-frame analysis with trained Ultralytics YOLO models
  • Anomaly capture with detection timestamps
  • Automated email notification with captured evidence
  • Remote web access to review detections

यह कठिन क्यों था

इंजीनियरिंग जटिलता

  • Keeping frame-by-frame inference responsive on commodity hardware
  • Reducing false positives to a level operators can trust

प्रोडक्ट अनुभव

डिलीवर किए गए सिस्टम से

Screens of the Automatic Crime Detector web application: the project landing screen, and a detection view showing a live webcam feed beside a detected-anomaly panel
Detection screenshots pending owner export

तकनीक

सत्यापित स्टैक

केवल वही तकनीकें सूचीबद्ध हैं जिनकी पुष्टि सोर्स कोड, प्रोजेक्ट दस्तावेज़ों या live deployment में हुई है।

  • Python
  • Django
  • OpenCV
  • Ultralytics YOLO
  • Email notification integration

डिलीवरी

ज़िम्मेदारी का दायरा

  • Model training and evaluation
  • Detection pipeline and alerts
  • Web application

इसी स्तर की जटिलता वाला सिस्टम बनवाएँ

30 मिनट का निःशुल्क परामर्श बुक करें, या हमें लिखें — आप हमेशा सीधे उसी व्यक्ति से बात करेंगे जो आपका प्रोडक्ट बनाता है।

Techon Pixel · info@techonpixel.com