You can deploy this model and start earning money today!

Faizan6100-amu/
edge_detection_Fai

Name: edge_detection_Fai
Availability: InStock

onnx

Views

No views yet

DexiNed

DexiNed is a Convolutional Neural Network (CNN) architecture for edge detection.

Notes:

Model source: ONNX.
Model source: .pth.
This ONNX model has fixed input shape, but OpenCV DNN infers on the exact shape of input image. See https://github.com/opencv/opencv_zoo/issues/44 for more information.

Requirements

Install latest OpenCV >=5.0.0 and CMake >= 3.22.2 to get started with.

Demo

Python

Run the following command to try the demo:

shell

# detect on camera input
python demo.py
# detect on an image
python demo.py --input /path/to/image

# get help regarding various parameters
python demo.py --help

C++

shell

# A typical and default installation path of OpenCV is /usr/local
cmake -B build -D OPENCV_INSTALLATION_PATH=/path/to/opencv/installation .
cmake --build build

# detect on camera input
./build/demo
# detect on an image
./build/demo --input=/path/to/image
# get help messages
./build/demo -h

Example outputs

License

All files in this directory are licensed under MIT License.

Reference

https://github.com/xavysp/DexiNed

Faizan6100-amu/edge_detection_Fai