ID: 5da4adb138f2ba0c90c7bab3
Image Segmentation(PSP Net)
by SHIVAM GARG
Image Segmentation using PSP Net
License: MIT license
Tags:
Model stats and performance
| Dataset Used | PASCAL VOC |
| Framework | Tensorflow |
| OS Used | Linux |
| Publication | View |
Inference time in seconds per sample.
Screenshots
PSP NET FOR IMAGE SEGMENTATION
WHAT IS IT?
PSPNet (Pyramid Scene Parsing Network) is a state-of-art segmentation network. It will not only detect object but also detect the outline of object, partition the image into several segments. With the pyramid pooling module Given an input image a pretrained ResNet model is used with the dilated network strategy [3, 40] to extract the feature map. The final feature map size is 1/8 of the input image.
HOW TO USE?
To run The Inference Script run this command
python run.py input_image_path
SAMPLE COMMAND
python run.py ./input/test1.png
| ARGUMENTS | DETAILS | HELP OPTIONS |
|---|---|---|
| -input_image_path | INPUT IMAGE | Mention the input image path |
WHAT ARE THE REQUIREMENTS?
To get all the requirements and dependencies installed run the command
For GPU - pip install -r gpu_requirements.txt
For CPU - pip install -r cpu_requirements.txt
Author View Profile
Views
A philosophy student cleverly disguised as a Coax Deep Learning engineer spending whole day, practically every day, experimenting with TensorFlow,Pytorch, and Caffe; dabbling with Python and C++; and drinking a wide variety of Coffee everyday.
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