yolov5-fire-detection and fire-detection-from-images
These are **complements** — one detects fire in video streams using object detection models (YOLOv5/YOLOv9), while the other detects fire in static images using neural networks, allowing users to choose based on their input modality (video vs. images).
About yolov5-fire-detection
spacewalk01/yolov5-fire-detection
Training YOLOv5/YOLOv9 to detect fire in a video
This tool helps automate the detection of fire or flames within video footage by drawing a box around identified fire hazards. It takes a video file as input and outputs a video with highlighted fire locations. This is designed for safety and security professionals, or anyone who needs to monitor areas for fire.
About fire-detection-from-images
robmarkcole/fire-detection-from-images
Detect fire in images using neural nets
This tool helps automate the early detection of fires in monitored areas like kitchens, garages, or outdoor fire pits. By analyzing camera images, it can pinpoint the exact location and size of a fire with a bounding box, rather than just detecting smoke. Security professionals, operations managers, or safety engineers responsible for monitoring specific environments would find this useful for improved response times and situational awareness.
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