lyxok1/Tiny-DSOD
Tiny-DSOD: Lightweight Object Detection for Resource-Restricted Usage
This project helps you accurately identify and locate objects within images or video feeds, even on devices with limited computing power. You feed in images or video, and it outputs bounding boxes around detected objects with labels. This is ideal for engineers deploying computer vision solutions in embedded systems, drones, or edge devices.
231 stars. No commits in the last 6 months.
Use this if you need robust object detection for real-time applications on resource-constrained hardware like mobile devices, surveillance cameras, or automotive systems.
Not ideal if your application prioritizes the absolute highest detection accuracy above all else and has access to ample computational resources.
Stars
231
Forks
56
Language
C++
License
—
Category
Last pushed
Jun 07, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/lyxok1/Tiny-DSOD"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
IBM/MAX-Object-Detector
Localize and identify multiple objects in a single image.
LSH9832/edgeyolo
an edge-real-time anchor-free object detector with decent performance
stephanecharette/DarkMark
Marking up images for use with Darknet.
amdegroot/ssd.pytorch
A PyTorch Implementation of Single Shot MultiBox Detector
aditya-vora/FCHD-Fully-Convolutional-Head-Detector
Code for FCHD - A fast and accurate head detector